Description and Exploration of Middle School Students' Acceptance of Chromebooks

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Description and Exploration of Middle School Students' Acceptance of Chromebooks A Mixed Methods Study
Agacli Dogan, Nihan
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[Gainesville, Fla.]
University of Florida
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1 online resource (185 p.)

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Doctorate ( Ph.D.)
Degree Grantor:
University of Florida
Degree Disciplines:
Curriculum and Instruction
Teaching and Learning
Committee Chair:
Dawson,Kara Mariehopkins
Committee Co-Chair:
Committee Members:
Adams,Alyson Joyce
Mccray,Erica Djuan
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Subjects / Keywords:
acceptance -- chromebooks -- laptop -- mixed-methods
Teaching and Learning -- Dissertations, Academic -- UF
bibliography ( marcgt )
theses ( marcgt )
government publication (state, provincial, terriorial, dependent) ( marcgt )
born-digital ( sobekcm )
Electronic Thesis or Dissertation
Curriculum and Instruction thesis, Ph.D.


Even though there is a plethora of research on Chromebook and cloud-computing devices in education, the majority of the research focuses on their impact on various outcomes and their evaluation in terms of project implementation. Little has been documented about students' attitudes toward and actual use of Chromebooks and other cloud-computing devices at schools yet students' acceptance of Chromebook is important for successful technology initiatives and efforts. This mixed-method study uses the Technology Acceptance Model (TAM, Davis, 1989) as a framework to examine middle school students' attitudes toward and use of Chromebooks. Quantitative data were obtained with the Computer Attitude Measure for Young Students (CAMYS, Teo & Noyes, 2008) and the Current Technology Use Survey (Lei & Zhao, 2008) from middle school students (n = 182) who attend a 1:1 Chromebook school and have 24/7 access to the devices. Following the survey, qualitative data were collected through semi-structured interviews (n = 8). Data analysis included descriptive statistics, independent samples t-tests, ANOVA and thematic analysis. The results of quantitative data analysis showed that the general attitudes toward Chromebooks were very close to the highest score obtainable on the survey (M = 52.07 out of 60). Results of ANOVA analysis for the effects of age, Chromebook use in school and outside of school produced no statistically significant effects on students' general attitude toward Chromebook. Additionally, the descriptive statistics regarding the tasks completed using Chromebook indicated that most students use their Chromebooks for doing homework (98.3%) and for searching for information (98.9%). Chatting online (3.4%) and creating websites (16.9%) were the tasks with the lowest positive responses. Qualitative interviews were conducted with students who scored particularly high or low on the CAMYS. While there were few differences between how students with more positive or negative attitudes reported using Chromebooks at home or at school, these students differed in their affect toward Chromebooks and how easy they perceive these devices are to use. Both groups of students with high and low attitudes found their Chromebooks useful for academic purposes. The qualitative interviews also revealed that Chromebook use varied across their classes with some classes such as Language Arts requiring students to use them nearly all the time and other classes such as Mathematics rarely requiring students to use them. Implications for researchers and practitioners are provided. Practitioners may gain valuable information about technology inititatives by investigating student perspectives related to devices such as Chromebooks. In addition, understanding how students use school-issued devices voluntarily outside of the school may help inform how the devices can be more effectively used in school. In this study, attitudes did not differ by gender or age which is encouraging. However, several contextual factors may have contributed to these resuts including the fact that students had 24/7 access to school-issued Chromebooks and that adoption was mandatory for students in school. More research is needed in this area. There was considerable variation in how students reported using Chromebooks within their classes. This may be because different subjects lend themselves more naturally to Chromebook use, because of a need for professional development to help teachers understand how to better integrate the devices or because of other unknown reasons. More research also is needed in this area. As Chromebooks become more widespread, there are many opportunities for researchers to use this study as a launching pad for future research. For example, future studies may use more than a one-predictor model to show the relative effects of different variables because there are likely other factors that need to be taken into account when examining Chromebook attitudes such as com ( en )
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In the series University of Florida Digital Collections.
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Thesis (Ph.D.)--University of Florida, 2020.
Adviser: Dawson,Kara Mariehopkins.
Co-adviser: Antonenko,Pavlo.
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by Nihan Agacli Dogan.

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To my beloved s ; Selç uk and Poyraz


4 ACKNOWLEDGMENTS First and most of all, I would like to express my deepest appreciation to my adviser, Dr. Kara Dawson , for her great expertise, assistance, guidance, and patience throughout not only the process of writing this dissertation but also my d octoral journey. She is always very understanding and encouraging. From my very first day in the program, Dr. Dawson provided different opportunities of research, professional development and teaching, and she made me a better scholar. I also would also like to extend my gratitude to my committee members Dr. Alyson Adams for her endless support for me and my family under any circumstances , Dr. Pasha Antonenko for his invaluable insights into my dissertation and e mpathy about being an international student , and Dr. Erica McCray for her guidance especially for t he qualitative part of my study. I am also grateful to be able to work with wonderful scholars, Dr. Albert Ritzhaupt, Dr. Swapna Kumar, and Dr. Nancy Dana. They all helped me to improve my skills and knowledge in different areas. I would also thank to great teacher s of P.K. Yonge Developm ental Research School, Carla Ann Brown, and Nathaniel Courtney and the D irector of Research and O utreach, Dr. Lyn da Hayes. They all helped me to collect my data in a very short period of time. I would like to acknowledge the many friends who have supported me in this journey . Thanks should go to Dr. Wenjing Luo Ph.D friend, Zhen Xu, Anita Stephen , and Ryan Rushing for being a great company in many class projects. I would like to thank Merve B udun and Ali Budun for the joy they brought in my doctoral journey. I cannot express my thanks enough to Sema Karagoz Sahin , who took


5 care of my son when I had to go to school and became my sister from another mother and confidant. I sincerely thank my family members: my mom, Fatma, my dad, Hasan Huseyin, my brother, Oguzhan, my sister in law, Ozlem and my cute nephews, Ege and Deniz. They have always supported me although th ey are miles away. Finally, it will be very hard to express my thankfulness to my husband , Selcuk who is love of my life, best friend, and support system. Without him, I could not have begun and completed this dissertation. He encouraged me to keep writing when I lost my motivation and made me reco gnize and believe in my skills . He sacrificed many things for me and our family. He has also been the best dad ever! When I had to write , he took care of our son perfectly. I also c herish the most precious little person in my life, Poyraz . His laugh was my therap y and his love was the light of my life. He was so patient with me and never disturbed me while I was writing. He helped me to write this dissertation a lot through hitting the the


6 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ .......... 10 LIST OF FIGURES ................................ ................................ ................................ ........ 11 LIST OF ABBREVIATIONS ................................ ................................ ........................... 12 ABSTRACT ................................ ................................ ................................ ................... 13 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 17 Background ................................ ................................ ................................ ............. 17 Technology Use in Educ ation ................................ ................................ ........... 18 Laptop Use in Education ................................ ................................ .................. 18 ................................ ................................ .... 20 Ra tionale for the Study ................................ ................................ ........................... 22 Purpose Statement and Research Questions ................................ ......................... 26 Significance of the Study ................................ ................................ ........................ 27 Organization of the Study ................................ ................................ ....................... 29 2 LITERATURE REVIEW ................................ ................................ .......................... 30 Laptop Use in K 12 Settings ................................ ................................ ................... 30 Academic Outcomes regarding Laptop Use ................................ ..................... 32 Behavioral Outcomes regarding Laptop Use ................................ .................... 33 Negative and Inconclusive Findings regarding Laptop Use .............................. 34 12 Settings ................................ ................................ ............ 36 ................................ ................................ ............ 36 ................................ ................................ 38 ................................ ................................ ... 40 Theoretical Foundations for Technology Acceptance ................................ ............. 41 Defining Technology Acceptance ................................ ................................ ..... 42 Technology Acceptance Models ................................ ................................ ....... 44 Theory of reasoned action ................................ ................................ ......... 45 Theory of planned behavior ................................ ................................ ....... 46 Technology acceptance model ................................ ................................ .. 47 Foundation of Computer Attitude ................................ ................................ ............ 49 Defining Computer Attitude ................................ ................................ .............. 50 Computer Attitude in Technology Acceptance Framework ............................... 52 Analysis of Relevant Studies ................................ ................................ .................. 54 Studies on Attitudes toward Computers ................................ ........................... 54


7 12 Settings ................................ ................... 57 Studies on Laptop Use in Technology Acceptance Framework ....................... 64 3 METHOD ................................ ................................ ................................ ................ 68 Study Design ................................ ................................ ................................ .......... 68 Context ................................ ................................ ................................ ................... 70 Participants ................................ ................................ ................................ ............. 73 Instruments ................................ ................................ ................................ ............. 76 Computer Attitude Measure for Young Students ................................ .............. 77 Current Technology Use Survey ................................ ................................ ...... 78 Interview Protocol ................................ ................................ ............................. 79 Data Collection ................................ ................................ ................................ ....... 82 Survey Administration ................................ ................................ ...................... 82 Individual Interviews ................................ ................................ ......................... 83 Data Analysis ................................ ................................ ................................ .......... 84 Quantitative Data Analysis ................................ ................................ ............... 84 Qualitative Data Analysis ................................ ................................ .................. 84 Research Design and Rigor ................................ ................................ .................... 86 Quantitative Phase ................................ ................................ ........................... 86 Qualitative Phase ................................ ................................ ............................. 87 Subjectivity Statement ................................ ................................ ...................... 88 4 RESULTS ................................ ................................ ................................ ............... 92 Responses to Computer Attitude Measure for Young Students .............................. 92 Descriptive Analysis ................................ ................................ ......................... 92 Mean Comparisons ................................ ................................ .......................... 93 Gender ................................ ................................ ................................ ....... 93 Age ................................ ................................ ................................ ............ 93 Chromebo ................................ ................................ .... 95 ................................ ....................... 96 Responses to Current Technology Use Survey ................................ ...................... 97 Interview Participant Profiles ................................ ................................ ................... 98 Low Attitude Group ................................ ................................ ........................... 99 Interviewee 1: J. ................................ ................................ ......................... 99 Interviewee 2: S. ................................ ................................ ...................... 100 Interviewee 3: Al. ................................ ................................ ..................... 101 Interviewee 4: H. ................................ ................................ ...................... 101 High Attitude Group ................................ ................................ ........................ 102 Interviewee 5: D. ................................ ................................ ...................... 102 Interviewee 6: L. ................................ ................................ ....................... 103 Interviewee 7: An. ................................ ................................ .................... 104 Interviewee 8: M. ................................ ................................ ...................... 104 Findings from Interviews ................................ ................................ ....................... 105


8 School, While They were Used for both Academic and Non Academic Purposes at Home ................................ ................................ ...................... 105 There was little to no difference between how students with low attitude them at school ................................ ................................ ...................... 106 ........................ 107 There was little to no difference between how students with low attitude home ................................ ................................ ................................ ..... 108 Perceived Ease of Use and Usefulness ................................ ...................... 110 High and low attitude group students differed in terms of their affect ................................ ................................ ........ 110 High and low attitude group students differed in how easy they perceive ................................ ................................ ... 112 especially for academic purposes ................................ ......................... 115 Summary ................................ ................................ ................................ ........ 118 5 DISCUSSION ................................ ................................ ................................ ....... 121 ................................ ................................ ............................... 121 There were No Statistically Significant Differences between Different Aged ................................ ................ 123 There were No Statistically Significant Differences between Female and .............. 125 ................................ ................................ .......................... 127 ................................ ................................ ............................... 129 in Similar Ways in School ................................ ................................ ............ 130 ... 132 .. 134 The Results of the Surve y and the Findings of the Interviews did not Align for the Three TAM Indicators ................................ ................................ ....... 136 Survey and Interview Results did not always Alig n ................................ ........ 137 Students benefited from the cloud different instructional purposes ................................ ............................. 142 Implications ................................ ................................ ................................ ........... 145 Implications for Practitioners ................................ ................................ .......... 145 Implications for Researchers ................................ ................................ .......... 147 Limitations and Future Research ................................ ................................ .......... 151


9 APPENDIX A SURVEY ................................ ................................ ................................ ............... 154 B INTERVIEW PR OTOCOL ................................ ................................ ..................... 157 C OPT OUT FORM ................................ ................................ ................................ .. 159 D IRB APPROVAL ................................ ................................ ................................ ... 161 LIST OF REFERENCES ................................ ................................ ............................. 163 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 185


10 LIST OF TABLES Table page 2 1 Google Apps included in Google Classroom and their purpose ......................... 38 3 1 Overview of the research design used in this study ................................ ............ 69 3 2 Student demographics participating in the study ................................ ................ 74 3 3 Number of students interviewed ................................ ................................ ......... 76 4 1 Descriptive statistics regarding the responses to CAMYS ................................ .. 92 4 2 T ... 93 4 3 .......... 94 4 4 ............................... 94 4 5 Descriptive statistics on th ................................ ............. 95 4 6 ANOVA of general attitude toward C ................................ ........................ 95 4 7 outside of school ................................ ... 96 4 8 er a week on ................................ ............. 97 4 9 Descriptive statistics regarding the tasks completed using Chromeb ........ 98 4 10 ................................ ................................ ................................ 111 4 11 Themes and categories from the qualitative data ................................ ............. 119


11 LIST OF FIGURES Figure page 2 1 Theory of reasoned actio n model ................................ ................................ ....... 45 2 2 Theory of planned behavior ................................ ................................ ................ 46 2 3 Original technology acceptan ce model ................................ ............................... 48 2 4 Parsimonious tec hnology acceptance model ................................ ..................... 48


12 LIST OF ABBREVIATIONS ATC Affect Towards Computer BI Behavioral Intention CAMYS Computer Attitude Measure for Young Students CBAM Concerns Based Adoption Model DOI Diffusion of Innovations ICT Information and Computer Technology IESD Interactive Educational Systems Design ISTE International Society for Technology in Education LoU Levels of Use LMS Learning Management System MLTI Maine Learning Technology Initiative NCES National Center for Education Statistics OECD Organisation for Economic Co operation and Development PEU Perceived Ease of Use PU Perceived Usefulness SEM Structural Equation Modeling SoC Stages of Concern SPSS Statistical Packages for Social Sciences TAM Technology Acceptance Model TPACK Technological Pedagogical Content Knowledge TPB Theory of Planned Behavior TRA Theory of Reasoned Action UTAUT The Unified Theory of Acceptance and Use of Technology


13 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy ACCEPTANCE OF CHROMEBOOKS : A MIXED METHODS STUDY By Nihan May 2020 Chair: Kara Dawson Major: Curriculum and Instruction Even though there is a plethora of research on and cloud computing devices in education, the majority of the research focus e s on their impact on various outcomes and their evaluation in terms of project implementation. L ittle has been document ed about students attitude toward and actual use of and other cloud computing devices at schools yet s is important for successful technology initiatives and efforts. This mixed method study uses the Technol ogy Acceptance Model (TAM, Davis, 1989) as a Quantitative data were obtained with the Computer Attitude Measure for Young Students (CAMYS, Teo & Noyes, 2008) and the Cu rrent Technology Use Survey (Lei & Zhao, 2008) from middle school students (n = 182) who attend a 1:1 Chromebook school and have 24/7 access to the devices. Following the survey, qualitative data were collected through semi structured interviews (n = 8). D ata analysis included descriptive statistics, independent samples t tests, ANOVA and thematic analysis.


14 The results of quantitative data analysis showed that the general attitudes toward were very close to the highest score obtainable on the survey (M = tatistics regarding the tasks completed using Chatting online (3.4%) and creating websites (16.9%) were the tasks with the lowest positive responses. Qualitative interviews were conducted with students who scored particularly high or low on the CAMYS. While there were few differences between how students with more positive or negative attitudes reported using Chromebooks at h ome or at school, these students differed in their affect toward Chromebooks and h ow easy they perceive these devices are to use . Both groups of students with high and low attitudes found their Chromebooks u seful for academic purposes. The qualitative in terviews also revealed that Chromebook use varied across their classes wit h some classes such as Language Arts requiring students to use them nearly all the time and other classes such as Mathematics rarely requiring students to use them. Implications f or researchers and practitioners are provided. Practitioners may gain valuable information about technology inititatives by investigat ing student perspective s related to devices such as Chromebooks . In addition, understanding how students use school issued devices voluntarily outside of the school may help inform how the devices can be more effectively used in school . In this study, attitudes did not differ by gender or age which is encouraging. However, several contextual


15 factors may have cont ributed to these resuts including the fact that students had 24/7 access to school issued Chromebooks and that adoption was mandatory for students in school. More research is needed in this area. There was considerable variation in how students reported u sing Chromebooks within their classes. This may be because different subjects l end themselves more naturally to Chromebook use, because of a need for professional development to help teachers understand how to better integrate the devices or because of o ther unknown reasons . More research also is needed in this area. As Chromebooks become more widespread , there are many opportunities for researchers to use this study as a launching pad for future research . For example , future studies may use more than a one predictor model to show the relative effects of different variables because there are likely other factors that need to be taken into account when examining attitude s such as computer/ experience , and support/encouragement to use computers/ . Researchers may also use computer attitude surveys other than CAMYS which focuses only three dimensions of computer attitude or, possibly, develop a survey specific to measur ing attitudes toward Chromeboo k. Researchers could also use through observational studies. Examining which student centered use is part of their approach to integrating th em would also make important contributions to our knowledge base.




17 CHAPTER 1 INTRODUCTION Background The demands of modern society have made technology very important in our daily lives. Technology has also been getting much more attention lately in the field of education as it plays a growing role in facilitating teaching and learning. Almost all institutions aim to prepare students for the inevitable use of technology in adulthood . As Yildirim (2007) stated , technology use in education is beneficial to reformulate tasks of teaching and learning and to enhance collaboration between teachers and students. The task of schools has evolved to make students prepared for the modern world with basic literacy, numera cy, and skills like critical thinking, collaboration, creativity, and communication skills (Grundmeyer & Peter, 2016). To ensure students gain these skills , schools are changing their way of teaching by providing technological tools and knowledge. In K 12 education, technology can be used for three different purposes in the teaching and learning process: for instructional preparation, as an instructional medium , and as a learning tool (Inan & Lowther, 2010). Today, there are technological tools that can be used for these three purposes at the same time. T he types of t echnology used in education have changed over years. Whereas radios, TVs, and overhead projector s were used in the past, computers, smartboards, and projectors are used today (Akkoyunlu & Erkan, 2013). Technology has been used in classrooms in different ways since the late 1970s , but since personal computing became more accessible in the 1980s, compu ters have become a n everyday part of the classroom(Gray, Thomas, & Lewis, 2010a; 2010b; Murdock, 2004; National Center for


18 Education Statistics [NCES]; 2018; Organisation for Economic Co operation and Development [OECD], 2015). Technology Use in Educatio n Over the past two decades, extensive efforts have been made to equip schools with technological resources and to prepare teachers and students to use computers for educational purposes. From 2007 to 2015, the U.S. invested heavily in software use and inf ormation and communication technologies , increasing overall funding levels from 26% to 33% of all education spending (OECD, 2018). There were seven students to each computer in 2000 , but by 2008 , th at number had decreased to three students per computer (NC ES, 2010). According to a recent report, middle schools ha d about five computers available for every nine students in 2012 (OECD, 2015). In 2013 and 2014, more than 23 million computers were bought to be used in schools, with iPads and being the top two choices (Herold, 2016). Numerous states and federal governments have adopted policies that encourage computer use in K 12 schools , and s chool districts have begun initiatives and programs dramatically (Muniz, 2018). In parallel, well known organizations, such as the International Society for Technology in Education (ISTE), support th ese efforts and require the use of technology by students who take an active role in achieving their learning goals (ISTE, 2016). Laptop Use in Education The use of laptops has increased exponentially in recent years, with laptop initiatives and reforms b eing more commonplace than ever before. I n Idaho, for


19 example, a state funded program has provided a laptop for every high school student and teacher (Idaho State Department of Education, 2012). In 2015, t he Florida Department of Education reported that it s school districts were shifting away from desktop computers to laptops, including . Putting laptops in hands of students has many advantages , such as the flexibility to do schoolwork in the places outside of school and to complete different tasks on the same laptop (Sahin, Top, & Delen, 2016) ; affordability ; the ability to connect to wireless networks , available in most schools ; and durability (Harper & Milman, 2016). Addit ionally, their lighter weight, smaller size, and easier access to wireless connection compared to desktop computers make laptops attractive for educators across many states (Penuel, 2006). Research evidence also supports the advantages of using laptops in schools, with positive results on numerous outcomes. According to multiple studies on the effectiveness of laptop use in schools, educators respond to them positively , report ing students a re more motivated and engaged, and are more active participa nts in their own learning when they use laptops (Argueta, Huff, Tingen, & Corn, 2011; Trimmel & Bachman, 2014). Studies show the positive impacts of laptops on academic achievement in science (Fisher & Stalarchuk, 1998; Siegle & Foster, 2000), in mathematics and writing (Gulek & Demirtas, 2005; Keengwe, Schnellert, & Mills , 2012) , and on student engagement and motivation (Harper & Milman, 2016). Similarly, iPads or tablets are a viable option for devices that can be used in classrooms, with many advantages. For e xample, they are user friendly, can be turned on and off very quickly, are easy to store, and provide a wide range of app lication s (Hutchison & Beschorner,2015). But, d espite their popularity and benefits, laptops and iPads are


20 less preferred by schools s eeking more cost effective alternatives (Tabor, Capraro & Yalvac, 2017). a s an Alternative With the introduction and common use of the Internet in classrooms, school leaders look for devices that are more convenient than desktop units, provide easy ways for students to access the Internet , and offer a useful teaching medium. The 2013 introduction of the has given school and state leaders an affordable option for students (Schaffhauser, 2015). are one of the most effective and are designed to provide quick Internet access to users who want to work with web based tools. They by providing better security , a more user friendly interface , and optimized performance (Singer, 2017; Tucker, Wycoff, & Green, 2016). are often chosen over iPads by schools because of their affordability, simplicity, security, and long battery life (Tabor, Capraro, & Yalvac, 2017). According to Interactive Educational Systems Design (IESD) surveys, of more than 500 K 12 schools, 14% had adopted in 2012. And after just two years, that number had more than trebled, to 47% (Tech & Lea rning, 2014). As Herold (2014) reported , from 2012 to 2014, while iPads sales were declining to around 7% of the U.S. education market , sold in big numbers in the United States. More recent reports have pinpointed the increase in shipment s to 38% of overall PC shipments (Shah, 2017) ; one stated remained a source of significant volume growth in the education buying mid


21 reported that Chromeb sales to U.S. schools accounted for more than 50% of the total sale of all technological devices in 2015 . While its use in K 12 settings has become widespread , the price has decreased over time , from $747 before 2012 to $279 currently . But are not only chosen because of their low cost : Schoenbart (2015) mentions that booting up and logging in to is quick and easy, which helps teachers use their instructional time more effectively. As reported in Leary et al. (2016), are more preferred than other mobile devices by students because they have different keyboards than tablets. A preference for is t heir full compatibility with Google Classroo m (Lea ry et al., 2016). are powered by a cloud enabling ubiquitous, convenient, on demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and servi ces) that can be rapidly provisioned and released with minimal management effort computing in education can bring many advantages to teaching and learning (González Martín ez, Bote Lorenzo, Gómez Sánchez & Cano Parra, 2015). Cloud computing helps decrease software conflicts and the cost of learning applications and extends the range of learning tools available to students and teachers. Additionally, schools can lower the cos t software by sharing licenses legally through the cloud. (Stein, Ware, Laboy, & Schaffer, 2013).


22 More specifically, these devices can be used to differentiate instruction. As Denton (2012) exemplifies, instructors can design different activities with clo ud computing , such as assigning group projects, having students do peer assessment s through Google Documents , using Google Slides for group presentations or in class discussions, and creating rubrics with Google Spreadsheets . Moreover, , and the cloud computing they rely on, can support collaboration between students and teachers (Bruce, 2018) , who can easily access applications like email, calendar, documents. Data storage in the cloud also lowers the burden caused by the need for IT profess ionals to back up and restor e data , allowing them to focus effective, providing flexibility to teachers and students, and requiring less support from IT, continue to offer an exce llent option for educational environments. Rationale for the Study Today, computers play a significant role in instruction not only at K 12 levels but also at higher education levels. Users continuously interact with computers for educational or administrative purposes. Yet h uman computer interaction, with the necessary i nvolvement of attitudes and feelings, is complex to comprehend (Willis, 1995). As investment in computers increases , all stakeholders educators, researchers, administrators, and policy makers need to gain an understandi ng of how users interact with technology (Teo & Noyes, 2008) and recognize the importance of users attitudes toward and reaction s to computers (Davies & Brember, 2001; Teo, 2006).


23 Given the increasing popularity of movements attempting to reform the instr uctional use of computers, educators and researchers have focused, in part, on improving and use of computers (Eutsler, 2018; Penuel, 2006; Teo, 2006; Yousif, 2010). In particular, th feelings about technology is critical , because technology has a critical role in shaping how students learn in and out of school (Straub, 2009) and is a strong determining factor in the use of technology (Davis, Bagozzi, & Warshaw , 1989; Huang & Liaw, 2005; Myers & Halpin, 2002; Teo, 2006; Teo, Chai, & Lee, 2008). Indeed, Hebert and Benbasat (1994) reported that 77% of the variation in using technology is explained by attitudes toward technology. Whether positive or negative, attit udes have an effect on how students react to technology enhanced learning environment (Teo, 2008) Many in the educational community see the growing use of in schools as a panacea. Teachers hope that the integration of into schools helps students study more effectively , and f unding agencies are investing on use in order to see positive outcomes in schools, teachers, and students. Yet for such efforts to meet expectations, the tool must first be accepted by students yet e ducators and funders often overlook the acceptance of and other attitudes toward as a learning tool. Equally, there are gaps in the , including whether students perceive that they support learning and help students complete assignments . D ata on student acceptance of


24 would help educators make decisions about the purchasing of such tools and the implementation of related current and future initiatives. technology is a primary predictor of the success in using a particular technology (Davies and Brember, 2001; Karahanna, Straub, & Chervany, 1999; Teo, 2 006). Thus, it is reasonable to believe that the success of any effort in K 12 settings requires students to accept first. However, considering the literature and available research on , there is a gap in what we know a bout , student attitudes toward , and their actual use of , which forms the basis of this study. The existing empirical research base related to and cloud computing devices in education encompasses several a reas. Overall, current research trends on and cloud computing in education ha s focused on its technology, applications, use, costs, and benefits (Sabia, Uzokab, Langmiac, & Njehd, 2016). N umerous empirical studies have been conducted comparing the performance of students with and those without (Kimmons, Darragh, Haruch & Clark, 2017), classroom integration (Sahin, Top, & Delen, 2016; Urbina & Poly, 2017), the effect of on teacher and student outcomes (McCar they, s of and experience s with using (Leary, Severance, & Penuel, 2016). Similarly, research on cloud computing in education is multifaceted. In their comprehensive analysis of 13 2 studies, Shi, Yang, Yang, and Wu (2014) documented five main areas of research in cloud computing in education: conceptual and


25 pedagogical aspects, educational applications, processing of information and resources, pros and cons of cloud computing in edu cation, and database management system integrated with cloud based services. T here are studies that investigate system wide application of cloud based computing in higher education (Brandabur, 2013), analyze the economic impact of implementing cloud comput ing for educational services (Boja, Pocatilu, & Toma, 2013), and examine barriers for the adoption of cloud computing (Sahdev, Medudula, & Sagar, 2015). Even though there is a plethora of research on and cloud computing devices in education, the majority of the research focus e s on their impact on various outcomes and their evaluation in terms of project implementation. L ittle has been documented about students attitude toward and actual use of and other cloud computing devices at schools yet s is important for successful technology initiatives and efforts. As the use of in schools increases, it becomes critical for educators to be aware of how students react when are integrated into a portion of learning activities or used out of school for practice and homework. Student perceptions regarding an d their use for education purposes are critical to encourage the use of at every level of education. No technology is an effective learning resource unless actually used by students. While several benefits of are well documented, research on how students actually use is limited. R esearchers typically use generic , providing neither a definitive account of student interaction with and the ir app licati on s nor


26 a detailed picture capturing how students incorporate into their learning. An i n is needed to fully comprehend the nature of their experiences. The studies that do exist are usual ly conducted in higher education, industry, or out of school venues. Research examining in K 12 schools is scarce. Normally, t he concerns of multiple stakeholders, including administrators and teachers, are considered when any technology refor m efforts are undertaken by educational leaders s are deemed important, yet are often overlooked (Zheng , Arada, Niiya, & Warschauer , 2014). Ultimately, decision makers should include the valuable perspective of young students when impl ementing technology , as they are the ones who actually use and benefit from that technology. As more schools incorporate into classrooms , and student life in the school becomes more interconnected with the outside world, we need a more robust empirical base for gaining better understanding of related attitudes and use. Purpose Statement and Research Questions The purpose of this study wa , an d I embrace d technology acceptance as a framework. To guide this study, two research questions were applied : ? ? was was described in terms of how they perceive their own use of and


27 the usefulness of Chrom , and their affect toward using , which are together the most important determinants of their acceptance (Davis & Wiedenbeck, 2001; Legris, Ingham, & Collerette, 2003; Teo, Chai, Hung, & Lee, 2008; Vankatesh, 1999). This phase enable d us to obtain a n expansive toward , the differences in which were examined in terms of factors that have been shown to affect attitudes , including age, gender (Meelissen & Drent, 2008; Sáinz & López Sáez, 2010), and e xperience/time spent using in and out of school (Moore, 1994; Schumacher & Morahan Martin, 2001). In the qualitative was elicited through in depth interviews. acceptance of as a learning tool were examined. In the quantitative phase of the study, the primary tasks for which students use were identified through a sur vey. The purpose of the qualitative phase of the study was to establish a knowledge base for how students use . Students were asked for in what ways they find The intent in the qualitative phase is to explor e with in the framework of technology acceptance. Significance of the Study experience with provide d insight into the implications of provi ding the tools to , school districts are able to make more informed decisions about how to approach students who use them, and s chool administrators can look for bett er ways


28 to lead initiatives in the ir school s . This study provide s an example of and how students use them . toward and use of add s to our knowledge base around related behaviors and practices. Regardless of how powerful and cutting edge technology is, its use is ult imately dependent on attitude s toward and use of allow s educators, researchers, and policy makers to understand the underlying reasons why some students embrace , while other s do not. This study investigates the experiences of middle school students who have daily access to computers and the Internet. By inquiring into the attitudes students who have been provided substantial access to computers in school and out of school env ironment s , this study aims to illuminate potential themes regarding acceptance. The insights gathered on how students use can inform teachers on effective uses of technology in the classroom and on how their use of tra nslates into student experience. This research study is important because the examination of student use of students study and learn through technology generally . The resul ts also inform us about the gap, if any, between what we plan and what is enacted e ven the best systematic plan for student use might not work , i.e., t he way students use might be totally different than what we expect. Therefore, h ow students


29 actually use and how they feel about the devices are particularly important in how we plan initiatives. School leaders and teachers can apply the valuable information from this study to transform the ir efforts to use Ch for instructional purposes. Organization of the S tudy There are four additional chapters which are followed by appendices in this study. In Chapter 2, relevant literature related to laptop use, Chromebook use in K 12 settings, the foundations of technology acceptance and computer attitude were reviewed. Relevant studies to the current study were also analyzed in that chapter. Research design and methodology was provided in Chapter 3. In Chapter 4, the anal ysis of the instrument s, participant profiles, the results of surveys and interviews and findings were given. Chapter 5 contains discussion of the results, implications of the results of the study for both practitioners and researchers. Limitations of the study were also provided in Chapter 5. In Appendices which followed the last chapter, the surveys , the interview protocol and the opt out form were provided. At the end, references used in this study were listed.


30 CHAPTER 2 LITERATURE REVIEW Th and their use of . I embrace technology acceptance as . This includes an ved use of , their perception of the usefulness of , and their affect toward using , which are the most important determinants of both acceptance and actual use . This review of literature includes research related to laptop use and its effects on student outcomes in K 12 settings, use in K 12 settings, theoretical foundations for technology acceptance, and foundations of attitude s toward computers . In addition, I outline the findings from similar previous studies in order to situate this study within the current literature and identify gaps . Laptop Use in K 12 Settings that has not experienced a world witho ut technology (Niles, 2006). OECD (2016) reported that the skills required for and profiles of numerous jobs have changed along with technology. With the resulting evolving expectations and attendant requirements for being successful in the workforce , scho ols trying to prepare students for adulthood need to integrate technology into the classroom , and many have started doing so through systematic initiatives (Clarke, 2016). Because laptops are now more affordable, accessible, and durable than personal compu ting has ever been, and wireless networks are now common in many schools , , these technology initiatives often provide mobile devices to students (Harper & Milman, 2016; Kay & Lauricella, 2011; Teo et al., 2008a). Although a debate about


31 the benefits of us ing mobile devices in education continues , it is inarguable that technology has changed teaching and learning in the information age (Bebell, Clarkson & Burraston, 2014). In 1:1 technology initiatives, students and teachers are provided with their own mob ile devices such as tablet computers, laptops, or netbooks. Students can use their devices inside and outside of the school , with the latter helping to extend learning beyond the classroom (Simon, 2017). Penuel (2006) list ed three characteristics of 1:1 pr ograms: Students are given laptops which contain up to date productivity software like word processing and spreadsheet tools. Students are able to access the Internet through wireless networks in their schools. Students use their devices to complete acade mic tasks (e.g. homework, tests , and presentations). For 1:1 programs, how and for what purposes technology tools are used is more important than the technology itself (Morrison, 2014). Goals vary between programs; however, generally , they are designed for increasing student performance, improving the qualit y of instruction to engage more students, overcoming access inequity , and helping students prepare for the workplace (Abell Foundation, 2008; Penuel, 2006). Laptop use in classrooms can also be used to increase student motivation by enabling them to take m ore active roles in the learning process (Beelans, 2002). S uccessful and large scale laptop initiatives have been implemented across the country, including in Maine in 2002. This initiative , Initiative (MLTI) , . Its primary goal was to transform the utilization of technology in Maine , with a focus on 7 th and 8 th grade


32 teachers and students , who were all given M acBooks . T echnical assistance was provided for all users , along with professional development for the teachers. An evaluation of the program conducted after its first 5 years found that students mostly used their laptops for research and teachers mostly u sed their devices to communicate with their colleagues (Abell, Foundation, 2008). Another recent example of a successful laptop initiative is t he Digital Conversion Initiative in North Carolina , which started in 2008 and continues today . Under this progra m, all students in g rade s 4 to 12 a re given MacBook laptops during the school year. Evaluations of this program have found that t eachers who were given laptops changed their way of teaching , with many of them incorporating a flipped classroom approach , in which more student centered instruction is possible. With the individual laptops, many changes took place at the school, like easy access to digital sources, more effective communication, and enhanced collaboration between students (Hull & Duch, 2018). A large volume of published studies describ es the impacts of laptops in K 12 settings , including some showing the positive effects of laptops on student outcomes ( academic and behavioral ) . Other studies on laptop use found inconclusive or negative results. Academic Outcomes r egarding Laptop Use A number of studies have shown that laptop use increases student achievement (Ksopowa & Valdez, 2013). More specifically, students who use laptops show improved skills and test scores in several topics: math (Grimes & Warchauer, 2008; Gulek & Demirtas, 2005 ; Hansen et al, 2012) ; writing (Goldberg, Russell , & Cook, 2003; Owston & Wideman, 2001; Penuel, 2006; Rockman et al . , 2000; Silvernail & Gritter, 2007) ;


33 English/ l anguage a rts (Bebell & Kay, 2010; Ksopowa & Valdez, 2013; Zheng , Warschauer , & Farkas, 2013) ; reading (Bebell & Kay, 2010; Shapley, Sheehan, Maloney , & Caranikas Walker, 2010b ; Suhr, Hernandez, Grimes , & Warschauer, 2010) ; and science (Dunleavy & Heinecke, 2008; Crook, Sharma , & Wilson, 2015). In addition, the quality of student work was also enhanced (Grimes & Warchauer, 2008; Rockman et al., 1998; Silvernail & Lane, 2004). Students using laptops have also demonstrated imp roved learning in some non core curriculum areas such as 21 st century skills (Lowther, Inan, Ross , & Strahl, 2012; Zheng, Warschauer, Lin, & Chang, 20 16); technology skills (Lowther, Moss, & Morrison, 2003); information literacy (Dunleavy, Dexter , & Heinec ke, 2007; Grimes & Warchauer, 2008), and higher order thinking skills (Mitchell Institute, 2004; Rockman et al, 1998). Rockman et al. (2000) found that most of the students using laptops reported that laptops helped them do higher quality schoolwork , and G ulek and Demirtas (2005) showed that l aptops help e students to learn more effectively (Gulek & Demirtas, 2005). Moreover, laptop using students do better at transferring their learning to different settings (Rockman et al., 1997; 1998; 2000). L aptop use al so helps students with disabilities (Gulek & Demirtas, 2005) , whose writing also improves when using laptops (Goldberg, Russell, & Cook, 2003). Behavioral Outcomes r egarding Laptop Use With regard to positive behavioral outcomes, Rockman et al. (2000) repo rted that students had more positive attitudes toward computer s when they use laptops , and were more eager to use computers for their school related work. Several studies have shown that student engagement was enhanced by laptop use (Dawson, Cavanaugh, & R itzhaupt, 2008; Drayton, Faulk, Stroud, Hobbs, & Hammerman, 2010; Harris & Smith,


34 2004) specifically, students go t more engaged with real world learning environments (Danielsen, 2009), and use d different means for research (Storz & Hoffman, 2013). Other st udies have demonstrated that student motivation was positively affected by using laptops (Downes & Bishop, 2012; Robertson, 2015), and that confidence in their computer use also increased (Lowther et al., 2012). This confidence is not an illusion : technological competenc e also grew after they are given 1:1 laptops (Lei & Zhao, 2008; Oliver & Corn, 2008). As a result of laptop use, student attendance improved. W hen they were exposed to laptop use, special education students had better outcomes in terms of motivation and engagement ; t heir class participation, interaction with others , and ability to work independently were also enhanced (Harris & Smith, 2004). Similarly, Conway (2005) demonstrated better outcomes of laptops on writing and reading skills of students with dyslexia. Nega tive and Inconclusive Find ings r egarding Laptop Use More recently, literature that offers contradictory and compelling findings about the effects of laptop use in K 12 classrooms has emerged (Harris, 2010). According to Wenglinsky (2006), laptop use is negatively correlated with te st scores. Other studies have shown that the achievement gap between different groups of students (e.g. , high and low achievers or black and white students) was increased (Abell Foundation, 2008; Rousseau, 2007; Smith, 2012). In some studies, laptop use di produce any measurable effect for students , regardless of their achievement levels (The Hechinger Report, 2018). Even though low achieving students were expected to learn more, the se reports indicated that neither low achievers nor high achievers bene fitted from laptop use. Several studies have revealed that laptop use can cause behavioral problems (Harris, 2010) , e.g., s tudents can be distracted by the opportunities laptops afford to


35 pursue social media and other off task behaviors (DeLoatch, 2015; Do novan, Green, & Hartley, 2010; Haselhort, 2017; Robertson, 2015). Storz and Hoffman (2013) stated thatlaptops can be distracti ng, particularly for middle school students, because of the excitement generated by access to a personal computer and the Internet . Classroom management can be challenging in a learning environment that includes 1:1 laptops (Dunleavy, Dextert, & Heinecke, 2007). In addition to these negative findings on laptop use, some studies demonstrated inconclusive or nonsignificant findings. I n a study by Bryan (2011), laptops had no significant effect on the reading fluency of elementary students. Royer (2011) also found statistically nonsignificant differences in the test scores of middle school students using laptops . According to Penuel (20 06), laptop initiatives should be conducted more widely, and should be evaluated more systematically . In summary, studies of 1:1 laptop initiatives resulted in mixed findings on various outcomes. Laptops have been broadly used in 1:1 initiatives in K 12 se ttings , with some studies reporting positive academic outcomes , such as enhanced skills and scores in core curriculum areas such as math, science and English language arts. Moreover, some studies have found that laptop use has improved student learning and competency in non core curriculum areas such as technology literacy, information literacy , and higher order thinking. Positive behavioral outcomes linked to laptop use include incre ased student motivation, engagement, confidence , and attendance. Although there is a large body of literature showing positive results of 1:1 laptop initiatives, there are also studies demonstrating negative outcomes. Some studies


36 indicate that students c an be distracted by their laptops or can exhibit problematic behaviors making classroom management difficult. Finally, the literature also includes studies reporting no significant effects of laptop use. in K 12 Settings In this section, the features, the instructional use and benefits of in K 12 settings will be described. Features of Google have been used widely in classrooms since they were first in troduced to the market in 2013 (Herold, 2014; Shah, 2 017). There are more than 20 million students using all around the world. have dominated the education market in the U.S. for the last several years , and they are now the most common devices in K 12 schools (Google, n.d.). Chrome are laptops that use the Chrome operating system (OS), as well as many distinguishing features that make them very attractive for schools. First, they are fast: They can boot up in seconds with just one login (Bartolo, 2017) slowed down by add on virus software , since they have integrated security software that is always up to date (Mainelli & Marden, 2015). update automatically, with t he update occu r r ing in the background , ensuring that users are not interrupted and di stracted (Muniz, 2018) and that the system is never slowed down by out of date software . Second , they require a very small amount of technical setup. Deploy ing a takes less than 10 minutes , compared to 1.8 hours for an alternative device (Mainelli & Marden, 2015).


37 Third , have a long battery life ; with their battery able to last over 6 hours, students can use the devices for a whole school day without charging (Google Inc., 2013). Fourth , are cloud based devices , which means students can access their files and other data as long as they have their devices and an Internet deman d network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned Uzoka, Langmia, & Njeh, 2016, p. 183). Fifth, have a real keyboard, which can be more useful for document creation than the online keyboards tablets have (Cox, 2014). In addition to these advantageous characteristics, are a more afford able option than many tools . A that sold for $747 before 2012 now only costs $279. Besides the initial equipment outlay cost, s chools spend 70% less on than on a traditional computer , because there is no need to pay for servers, so ftware, security solutions , and other maintenance (Google Inc., 2013). Schools that choose can save $317 per unit o n average over three years of ownership (Mainelli & Marden, 2015). While price is an important consideration for schools while c hoosing technology, functionality and durability are also considered , giving an advantage (Molnar, 2014). are more frequently chosen by schools over iPads because of affordability, simplicity, security, and long battery life (Tab or, Capraro, & Yalvac, 2017).


38 A wide range of easily downloadable applications and extensions can be used with (Mainelli & Marden, 2015); these are also integrated with other web content and educational tools available in the Chrome Web Store . These apps are free for schools, and no advertisements are included in applications used for education. Applications in cluded in Google Classroom and their uses can be seen in Table 2 1, and the next section will explain how they can be used effectively in instruction. Table 2 1. Google Apps included in Google Classroom and their purpose Application Purpose Gmail Email Drive Online data storage Hangouts Real time chat Forms Information gathering Calendar Organization, time management, scheduling Docs Word processing Sheets Organization, analysis , and storage of data Slides Creating presentations Sites Website development and project management Instructional Use of A considerable number of studies have attempted to investigate how laptops are used by student s in and out of classroom. In summary, these studies show laptops are used for writ ing, note taking, assignment completion, organization, communication , and research (Penuel, 2006). Similarly, are used in instruction in many different ways . For example, the Bloomington Public School District implemented a 1:1 initiative that provid ed every student with a and adopted Google Apps. In language arts class es , teacher s used Google Sites to create a blog about books, with students contributing blog posts about the books they read. Teachers also assigned


39 pairs of stud ents to be who could share content through Google S ites (Google Inc., 2014). As Denton (2012) mention ed, K 12 instructors can use and Google Apps for many different activities, including assigning group projects or peer asse ssment s through Google Docs , using Google Slides for group presentations or in class discussions, and creating rubrics with students in Google Spreadsheets . With Google Docs and Spreadsheets , students can collaborate more easily . In the former, discus sions can be facilitated (Cox, 2014) , and students can edit or comment on With Google Forms , teachers can create pop up quizzes very easily (Google Inc., 2015). In addition to these and other common apps and extensions, ar e compatible with Google Classroom . With Google Classroom , teachers can student work without printing (Google Inc., 2016). Another benefit of Google Clasroom is that f ee dback provided by teachers in Google Classroom is not one way s tudents can reply to comments left by their teachers. Additionally , b y using , teachers can also flip their classrooms , the way two elementary school teachers did in Bloomington, by uploading videos to the Internet for use before or after classes. This type of innovation allows students to master new skills and knowledge at their own pace and via their own path (Google Inc., 2014). Google Classroom can also be used b y teachers to customize visual, audio , or text resources for their students. Assignments can also be personalized by Google Classroom , for example, by enabling different groups of students in the same class to


40 do different tasks simultaneously: While one group works on a reading assignment, another group may get immediate feedback from their teachers (Google Inc., 2015). Benefits of Using The very short boot up time of helps to minimize distractions and to increase available time for teachers and students in classrooms. With their cloud based computing feature, are a good choice for schools that do not want to spend too much money on specific software or technicians who will install the software and maintain the devic es (Muniz, 2018). Furthermore, the cloud base computing of provides more possible interactive and collaborative learning environments for learners (Bartolo, 2017). Thanks to cloud computing, students can extend their knowledge beyond school by creating a network among them selves process , because every student can complete assignment s at their own pace (Butoi, Tomai , & Mocean, 2013). Students can easily access, revise , or edit documents, and multiple students can use their devices to work on the same document at the same time (Vickers, Field, & Melaloski, 2015). Moreover, the low cost of makes them accessible and affordable for many schools (Google, 2014) , making it possible for them to provide devices to more students and potentially reach a 1:1 user device ratio (Mainelli & Marden, 2015). Individual profiles make differentiation and accessibility easier : Students can access their personalized settings by logging in with their personal information. Although the market that long , they have been used in many educational initiatives , with demonstrable instructional benefits . Lancaster and Topper (2011), for example, showed how the devices help to enhance writing and 21 st century skills.


41 It can be concluded that are the devices most preferred by schools for their low cost, durability , and ease of use and management. They can help schools to achieve goals like creating a collaborative and creative learning environment, personalizing the learning process for students , and extending lea rning beyond school through the use of technology. Theoretical Foundations for Technology Acceptance and their use of . I embrace a theoretical framework that provides theoretic ally sound definitions of concepts used in this study. While attitude s toward computers/technology and their use have been defined in various ways, I adopt technology acceptance as a framework that defines both attitude s toward computers and use of compute rs and which also explains their relationship. Having technology acceptance as a framework provides a structure that holds conceptually accepted and operationally defined concepts together. This section examines how attitude and use are defined across diff erent technology acceptance models. Having this framework lets us intellectually transit from a mere description of attitude and use to a more detailed account and articulation of these characteristics . A t echnology acceptance framework also helps identify the scope and the limits of these two concepts by highlighting how they might vary in different contexts. In this section, the definitions of technology acceptance suggested by different researchers and the distinction between adoption and acceptance wil l be discussed first. Defining technology acceptance is important because it establishes a basis for the theoretical foundation of this study. Second, the technology acceptance models and


42 theories that include attitude and use will be examined in terms of how these concepts are defined and interact with each other . Defining these two concepts has significance in a deeper way. Defining Technology Acceptanc e Although there are numerous models examining technology acceptance, there is no clear definition in the literature of the concept as a construct (Kauer, 2012; Menghrajani, 2011). However, several studies provide an operational definition. The most common ly accepted operational definitions of technology acceptance have been provided by Davis (1989) and Venkatesh and Davis (2000). While Davis (1989) defined , updated the parameters as . employ information technology for the tasks it is designed to Diez and McIntosh (2009) operationalized technology acceptance by measuring the responses of users to questions about approving of a system and how often they use the system. Venkatesh and Bala (2008) define d technology acceptance as an attitude with three different components: cognitive, affective , and behavioral. Whereas cognitive would comprise evaluation of the system in terms of its usefulness, affective refers to the degree to which users like or dislike the system. Behavioral indicates how users utilize the system and implement it successfully. Similarly to other studies o n technology acceptance, Sedera, Lokuge, Salleh, Moghavvemi, and Palekar (2016) asserted that technology acceptance is the incorporation and internalization tasks , where i ncorporation refers to the


43 and routines , and internalization to the incorporation of beliefs about the system into broader belief systems. Although they have often been used interchangeably in the literature, important to make a distinction between acceptance and adoption. There is a process i n adoption that starts with awareness of a new technology and ends with the full incorporation of that techno logy by the user. This complex process is developmental , and it has social aspects (Straub, 2009) and thus is an attitude users have toward a technology (Renaud & van Biljon, 2008). Straub (2009) argued that adoption connotes not only acceptance of a techn ology, but also its full integration into different contexts. The other difference between adoption and acceptance is that acceptance is about : whether they will use a technology or not . On the other hand, adoption also includes components and stages focused on the ways people actually do implement the technology in to their work. This study also explores stages in adoption theories , i.e., the slow progress in knowledge and understanding of a technology. Acceptance can be either a stage or an aspect of one , because it is an integral part of the adoption process (Gelderblom, van Dyk & van Biljon, 2010). O ther studies defin e adoption and accep tance in slightly different ways . For example, Kaldi, Aghaie , and Khoshalhan (2008) define d adoption as making (by a firm, division, or department) to introduce a new system into the organizati definition of acceptance was perceptions, and actions lead them to try new practices, activities, or innovations that . In this study, adoption is a


44 stage of a diffusion process at the organizational level, whereas acceptance is a stage of that process at the individual level. The models focusing on how users adopt technology or innovation have stages. For example, a Dif fusion of Innovations (DoI) model comprises five stages of adoption: knowledge, persuasion, decision, implementation , and confirmation. Similarly, a Concerns Based Adoption Model (CBAM) (Hord, Rutherford, Huling Austin, & Hall, 1987) includes stages for th innovation , and has three components: stages of concern (SoC), levels of use (LoU) , attitudes, LoU provides an und erstanding of behaviors during innovation process (Straub, 2009). Technology Acceptance Models A number of models are used to predict or describe technology acceptance : Theory of Reasoned Action (TRA) (Fishbein & Ajzen, 1975) ; Theory of Planned Behavior ( TPB) (Ajzen, 1985) ; Technology Acceptance Model (TAM) (Davis, 1989) ; Technology Acceptance Model 2 (TAM2) (Venkatesh & Davis, 2000) ; Technology Acceptance Model 3 (TAM 3) (Venkatesh & Bala, 2008) ; , Diffusion of Innovations Theory (DOI) (Rogers, 1995) ; and t he Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh, Morris, Davis , & Davis, 2003). The scope and key variables differ between the se models. T he models that incorporate attitude and use , the main concepts of interest to this study, are reviewed in this section. These three models are TRA, TPB, and TAM. TRA and TPB form the foundation of TAM. In fact, t hese three models are built on one other , and all have a notable focus on attitude. TAM has been a particularly


45 widely used model bec ause it specifically focuses on information technologies (Sharp, 2007 ), and because of its simplicity and understandability (King & He, 2006). Data collected through instruments designed based on TAM have been shown to be valid and reliable (Teo, 2008). I use the operational definitions of attitude and use provided by these three models to choose and develop data gathering instruments. Theory of r easoned a ction TRA was originally developed by Fishbein and Ajzen (1975) for sociological and psychological stud ies ; h owever, since then it has been used to predict behaviors related to technology usage (Taherdoost, 2018). According to this model, behaviors can be predicted by three components: Attitude: Beliefs about outcomes when target behavior is performed. Subj ective norm: Perceptions of social pressure to perform or not to perform the target behavior . In this model, the focus is only behaviors , not the outcomes of those behavior s. In addition, it is assumed that an Hartwick, & Warshaw, 1988). According to TRA, behavioral intention is the most important determinant of behavior , and a ttitude and subjective norms are the determinants o f behavioral intention (Fishbein & Ajzen, 1975). The relationships between the constructs of TRA can be seen in Figure 2 1. Figure 2 1. Theory of reasoned action model (Fishbein & Ajzen, 1975) .


46 There are many studies investigating the links between the constructs of this model , but the behavioral intention (BI) behavior (B) link is the one studied the most (Hagger, Chatzisarantis , analysis is an example of the studies focusing this link. Theor y of p lanned b ehavior TRA is only applicable to volitional behaviors ; however, not all behaviors are behaviors, Ajzen (1985) developed TPB. Unlike TRA, TPB includes perceived behavioral control , defined as perceptions and beliefs about ability, resources , and opportunities to perform the target behavior (Madden, Allen, & Ajzen, 1992). Perceived behavioral control both reflects external (e.g. time, m oney) and internal (e.g. ability, skill) factors (Nisson & Earl, 2015). While money and time are accepted as facilitating conditions making individuals engage with performing the target behavior. The s kill and ability of the individual to perform the targe t behavior determine self efficacy , which is the second component of perceived behavioral control. The study conducted by Madden et al. (1992) show ed that adding perceived behavioral control increased the precision of behavioral intention. This means that TPB explains more variation in behavior and behavioral intention than TRA. Figure 2 2 illustrates the links between the constructs of TPB . Figure 2 2. Theory of planned behavior (Ajzen, 1985).


47 According to Taylor and Todd (1995), the three constructs providing the determinants of behavioral intention are determined by different belief structures. For example, attitudes are determined by attitudinal beliefs. Similarly, subjective norm is determined by normative beliefs , and perceived behavioral control is determined by control beliefs. There are two limitations of TPB. First, belief sets, especially related to attitude, are specific to each different empirical setting so it is hard to apply TPB in different settings. Second, the relationship between beli certain (Taylor & Todd, 1995). Technology a cceptance m odel Mathieson (1991) found that TPB , which is predictive of behavioral intention , is actually not the best model to explain it. Thus TAM (Davis, 1989) became a powerful model to predict technology usage behavior. Over the years, TAM has become one of the most widely used theories to predict the acceptance of a new technology by users both because focuses specifically on information technologies and because of its simplic ity and understandability (King & He, 2006). TAM , which has been proved as a valid and reliable model can be applied extensively , so there is now a large body of research conducted with TAM (Sharp, 2007). Like TPB, TAM is adapted from TRA. Attitudes and behavioral intention are common in TRA and TAM. However, Davis did not include subjective norms in TAM , because he concluded that it does not have an important impact on behavioral intention. Additionally, Davis proposed in TAM that attitude can be predicted by two distinct beliefs : perceived usefulness (PU) and perceived ease of use (PEU) (Maranguni & Grani , 2015). Davis hypothesized that , in TAM, attitude is the most important determinant of behavioral intent ion. Perceived usefulness and perceived ease of use


48 influence attitudes. In the model proposed by Davis , perceived usefulness is predicted by perceived ease of use (See Figure 2 3). Figure 2 3. Original technology acceptance model (Adapted from Marangun i & Grani , 2015) . After developing a model for technology acceptance with three variables perceived ease of use, perceived usefulness , and attitude Davis continued to test this model. Davis, Bagozzi , and Warshaw (1989) , who relied on it in their study with 107 MBA students who used a word processing tool. However, Davis et al. found that perceived ease of use and perceived usefulness were not fully mediated by attitude , so they suggested removing it from the model. This new model without attitude was dubbed parsimonious TAM by Sharp (2007). Venkatesh and Davis (1996) showed that both perceived usefulness and perceived ease of use have a direct effect on behavioral intention. They also suggested removing attitude from TAM and proposed a new model ( s ee Figure 2 4). Figure 2 4. Parsimonious technology acceptance model (Sharp, 2007; Venkatesh & Davis, 1996).


49 Both original and parsimonious TAM h ave been used extensively in quite a few studies to predict user acceptance of different technologies (Sharp, 2007). finding that perceived usefulness is a stronger determinant of intention to use than perceived ease of use is supported by ma ny other studies conducted with different users and technologies (Amaoka Gyampah & Salam, 2004; Chau & Hu, 2002; Huang, 2005 ; Jen Hwa Hu, Lin, & Chen, 2005; Mathieson, Peacock, & Chin, 2004 ). Other studies have found that perceived ease of use is stronger than perceived usefulness (Brown, Massey, Montoya Weiss, & Burkman, 2002; Gong, Xu, & Yu, 2004; Moon & Kim, 2001; Shih, 2004). As with original TAM, parsimonious TAM , in which attitude is eliminated , has also been continually used in the literature. There are studies confirming the findings of this new model by Davis et al . (1989). These studies also assert ed that perceived ease of use and perceived usefulness are direct determinants of behavioral intention (Chau, 2001; Hong, Thong, Wong, & Tam, 2002; Liaw & Huang, 2003; Lin & Wu, 2004; Yi & Hwang, 2003). In addition to showing the direct effect of PU and PEU on behavioral intention, these studies indicated that perceived usefulness is a stronger determinant of behavioral intention (Sharp, 2007). O nly one st udy , by Van der Heijden (2004) , has object ed to this finding. Foundation of Computer Attitude Comprehending the foundation of computer attitudes requires an elaboration of attitude in general. The definition of any concept can be developed according to its relationships with other constructs, according to Ajzen and Fishbein (1975). This is also val id for defining attitude, which is related to various constructs in different theoretical frameworks. Conceptually defining attitude is more preferable than theoretically defining it because conceptual definitions provide procedural suggestions (Fishbein & Ajzen,


50 predisposition to respond in a consistently favorable or unfavorable manner with respect ey are evaluative; people are positioned somewhere from negative to positive on an evaluative scale. People may have favorable or unfavorable attitudes toward behaviors according to their consequences (Ajzen, 1991). Second, for many of modern definitions, attitude is the same as disposition (Fishbein & Ajzen, 2010). Attitudes need to be distinguished from other similar concepts used widely across research studies. One of these concepts is belief. While attitude is the favorable or unfavorable evaluation of an object , conducted by a person, belief is the information a person has about an object. The other concept that can be confused with attitude is Ajze n, 1975, p. 12). Although they are different concepts, in some ways, attitude is related to belief and behavioral intention. P eople may have positive and negative beliefs about an object , and that attitude is determined by the affect related to these beli efs. Correspondingly, attitude toward an object is also associated with the intention to perform different behaviors regarding that object. According to Ajzen (1991), when attitudes become more positive, intention s to perform a behavior become stronger. D efining Computer Attitude attitude (Cai, Fan, & Du, 2017, p. 3) because across research studies, attitudes toward technology are considered as a single, separate construct, ra ther than as a multi faceted construct (Whitley, 1996). Several researchers have aimed to define computer attitude in their theoretical models. Almost three decades ago, as Kay (1993) reported,


51 at least 14 different definitions of computer attitude exist i n the literature. A recent meta analysis study by Cai et al. (2017) confirmed that there are still different conceptualizations of attitude toward technology and technology use with various focuses. According to the definition of attitude in Ajzen and Fish bein (1977; 1980), s general evaluation or feeling of favorableness or unfavorableness toward computer technologies (i.e. , attitude toward objects) and specific computer related activities (i.e. , attitude towar d Caputi, & Rawstorne, 2000, p. 61). Zimbardo and Ebbesen (1970) and Triandis (1971) state that general computer attitude includes three components: affective, cognitive , and behavioral. While the affective component is related to peop the cognitive component is more about the knowledge about the object. Additionally, the behavioral component con notes visible behaviors of people toward an object (Thompson, Simonson , & Hargrave, 1996). Likewise, Meelissen and Dren (2008) pr oposed that computer attitude has three elements: affective (enjoyment while using computers), cognitive (perceptions about the relevance of computer) , and conative (anxiety and self confidence about using computers). Kay (1993) listed four component s of c omputer attitudes: Affect , which refers to feelings toward computers Cognition , which refers to perception and information toward computers Conation , which refers to intentions and actions with respect to computers Perceived behavioral control , which refers to perceived ease or difficulty in using computer s D efinitions of computer attitude across the previously described studies and theories vary fro m narrow and simplistic to broad and complex. This study emphasizes


52 computer attitudes within the framework of technology acceptance, which is explained in the next section. Computer Attitude in Technology Acceptance Framework Understanding a ttitude s towar d computers is integral to understanding how they are accepted (Ayres, 2002; Teo, 2006) and for predicting future computer use behavior (Selwyn, 1997). The importance of understanding attitude toward computers was highlighted in some of technology acceptan ce models and theories described earlier (Afshari, Ghavifekr, Siraj , & Jing, 2013; Davis, 1993) . According to the model of TAM described by Davis (1989), there are two elements to attitude: perceived ease of use and perceived usefulness. While perceived us system would enhance his or her job performance , of also specifie d these two components as determinants of attitude. TPB , proposed by Ajzen (1985, 1991) , added one more component determining attitude: perceived behavio ral control. Taylor and Todd (1995) asserted in their Decomposed Theory of Planned Behavior (DTPB) framework that , in addition to perceived ease of use and perceived usefulness, attitude also includes compatibility , which refers to matching of a ds, existing values , and experiences with the object itself. Similar to TAM and TRA, Brock and Sulsky (1994) argued that computer attitude is composed of two factors : beliefs about the benefits of computers and autonomy from them. These two factors were f irst identified by study (1970), in which 3 , 000 individuals were interviewed about their attitudes toward computers. More recently,


53 Rogers (2003) also discussed attitudes in his Diffusion of Innovations (DoI) model. According to the DoI framework, attitudes are integral , especially in the persuasion stage of adoption of an innovation , such as a computer. U sers about the usefulness compar ed to previous technologies, its complexity, and its compatibility can all affect t he attitudes of the users toward a technology (Laher & Bosholf, 2017). Given the complicated nature of attitude within the technology ac ceptance framework and varying definitions, this study takes a granular approach to define attitude toward computers/ that is dependent on a technology acceptance framework, mainly TPB and TAM. In addition, the definition provides a comprehensive account of attitudes toward computers. In the context of this study, attitude toward computers/ Chromeboo degree of favorableness toward , pleasure in , and liking of computers (Ajzen, 1988; Ajzen & Fishbein, 1977; 1980; Davis, 1985; 1993; Kay, 1993; Smith, Caputi & Rawstorne, 2000). The attitude toward computers has three dimensions: 1) perceived ease of use (PEU), 2) perceived usefulness (PU), and 3) affect toward computer (ATC) (Teo & Noyes, 2008). PEU is defined as the degree to which an individual believes that using a particular system would enhance his or her job performance (Davis, 1985). This includes using a computer to learn or complete tasks. PU is defined as the degree to which an individual believes that using a particular system would be free of physical and mental effort (Davis, 1985). Usefulness in this definition also refers to degree to which a computer helps a user


54 reaction s to and feelings about using a system (Teo, 2008). It also encompasses the joy and other positive feelings associated with using a computer (Teo & Noyes, 2008). Analysis of Relevant Studies In the previous sections, brief information from empirical studies about laptop use in the K 12 setting, their outcomes, and the benefits of Ch ha ve been presented in order to provide a general picture of the research context to which this study belongs. Within the scope of this study, three existing research areas are critical: computer attitude, in K 12 settings, and lapt op use in the technology acceptance framework . But because no one area of research contains all main four areas of interest computer attitude, computer use, , and technology acceptance studies in all three research areas were re viewed and summarized in this section to provide the most comprehensive picture as much as possible. Studies on Attitudes t oward Computers Teo (2008) investigated , through a survey of 183 students in Singapore, college The researcher defined computer attitude in terms of computer importance, collective attitude toward computers was also examined as a latent variable in the study. L imited information about the contex t of the study was offered, for example how students were using computers for instructional purposes , or what kind of computers were used . The results of this study showed that the target group had a strong and positive attitude toward computers. Compute r ownership at home produced statistically


55 significant differences between students who own ed computers at home and those who did not ; no statistically significant result was reported in terms of gender. Meelissen and Drent (2008) examined , through a lar ge scale correlational survey study of nearly 4 , 000 students in the Netherlands , the extent to which school related factors affect ed the difference in computer attitude in primary schools, given the effect of non school related factors. The study took int o consideration the cultural, contextual, and structural characteristics of schools (class and school size, student computer ratio) ; teacher s (pedagogical approach, use of infor mation and computer technology ( ICT ) , support systems, ICT skills and knowledge, gender, experience) ; and students (gender, computer use by parents, self efficacy in computer use). The researchers used three (pleasure in using computers), a cogni tive component (perceived relevance of computers), and a conative component (anxiety and self confidence). The results of this study showed that non school related factors (gender, family interaction, student views of computers) explained more variance in computer attitude than school related factors (school characteristics, school culture, teacher characteristics ) attitude. A teacher centred pedagogical approach and the computer experience of female teachers showed positive but small effect s Chau (2001) examined the impact of computer attitude and self efficacy on 360 framework. Perceived usefulness and perceived ease of use were also included in the


56 empirical model tested with structural equation modeling (SEM). Computer attitude and self efficacy were used as predictors of these two variables in the model. The researcher mainly adopted A study. The results indicated that with the addition of two variables, the augmented model showed a more precise model and produced a better ratio of explained variance. Computer attitude had a stron g and positive effect on both perceived usefulness and perceived ease of use. T he effect of self efficacy on perceived usefulness was weak and negative ; h owever, the effect of self efficacy on perceived ease of use was not statistically significant. In a descriptive survey study, Bayhan, Sipal, and Karaaslan (2009) investigated d according to various demographic variables , using data gathered from 226 6 th to 8 th grade students. The researchers a definition of computer attitude , but it can be inferred that self confidence, general attitude (liking) , and sex bias formed the basis of computer attitude in this study. The demographics variables used in the study were access to, ownership of , and freq uency of use of home computers ; computers at school ; frequency of use of computers for different applications ; gender ; preferences for use of computers ; and computer use experience and skills. The results of this study showed that boys were more experienced users of computers and spent more time on computers than girls. Girls were reported as having lower computer use ability and as being more likely to f ind computer technology difficult and complicated. In their survey study, Comber, Colley, Hargreaves, and Dorn (1997) collected data from 278 11 , 12 , 15 , and 16 year old students to investigate the effects of age,


57 gender, and prior computing experience on attitudes toward computers. The researchers used four subscales to conceptualize computer attitude: self confidence in the use of computers , general attitude (liking) , sex bia s, and perceive d computer utility toward, but only analyzed the first three . M ales from both age groups had more experience with computers and had more positive attitudes toward computers than females. Parallel results were reported for younger students. After controlling for ownership and use of a home computer, the researchers ind icated that both groups had comparable levels of enjoyment of computers. Similar analyses incorporating length of experience did not produce statistically significant results . In summary, studies of computer attitude have been pursued in the primary schoo l , middle school, and higher education environments . While each study used a different definition of computer attitude , this study relies on a comprehensive definition of attitude, which includes perceived usefulness of , perceived ease of use of , and affec t toward computers. The studies reviewed provide a knowledge base about general attitudes in these three dimensions and allow us to compare attitudes toward computers with attitudes toward . The computer attitude studies summarized here all focus ed on either laptop s or personal computers little to none research has been conducted about . Studies on in K 12 Settings use in K 12 settings has increas ed exponentially in recent years . Existing initiatives generally has two focuses: students and teachers. The research methods used are comparative quasi experimental, case studies, and survey studies. Typically , participating educators teach mathematics, writing, or science.


58 Urbina and Polly (2017) examined how four elementary mathematics teachers integrated into their classroom using an inductive qualitative research method in a public school. Using technological pedagogical content knowledge (TPACK) as its theoretical framework, the researchers also explored how these teachers handled the hardship of integrating technology in to their classroom s and how they adapted content and pedagogy knowledge. The study mostly technology (laptops and smartboards) integration , with use of . In the context of the study, teachers had their own laptops during class hours and used them to manage content delivery . Stude s had access to their own during the time they were in school. The researchers collected data through both classroom observations and interviews. The interview data showed that teachers thought promoted student learning in mathematics ; one teacher found use problematic , reporting Observations indicated several different findings. For one, w hen students completed classwork early , they used their to access websites for low level individual and practice assig nments. In addition, t eachers directed students to use mostly for extension and supplemental activities. On the other hand, observations in two classrooms demonstrated that students rarely used for instructional purposes , as those teachers directed their pupils to be engaged in hands on practices.


59 In an effort to compare the essay composition scores of students who used (n = 139) to those using handwriting (n = 319), Kimmons et al. (2017) conducted an experimental stud y with 8 th grade students in three different middle schools. The researchers arranged long term loans of to teachers , as well as professional development programs for teachers to learn more about and how to use them . Students were randomly assigned to experimental and the control group s, which were given the same instructions . with a standardized reading test and essay s . According to the results, essays written o n were longer and more advanced/sophisticated , with more unique words and fewer grammatical errors , and the essays received statistically significant high er grade s compared to hand writt en essays. A study by Brown (2018) was conducted to determine whether interventions increased student achievement on a high stakes mathematics assessment. T he researcher also explored the relationship between the student learning objectives of at risk students and the use of . N o intervention was provided ; h owever, using the data from the state, the researcher investigated the performance s of students who received mathematics instruction through and those who received it through traditional methods. A quasi experimental design using a pre test and a post test design was implemented with 236 9 th grade students. The mathematics instruction that the experimental group received through included drill s and practic e, project based and collaboration based activities, and manipulatives. Students in the control group received differentiated


60 instruction promoted by student collaboration. The results of the study showed integrated instruction did not increase student scores , but f urther analysis into gains in student learning objectives demonstrated that the use of scores. Leary et al. (2016) examined the effects of the us e of cloud based tools and on teacher learning and student activity after teachers attended a professional development program focusing on the development of a digital high school biology unit plan. With a design based implementation research method, sixteen teachers, researchers, and curriculum developers co designed student centered unit plans , including technology based instructional materials. Teachers were provided a high level of facilitation and support to design prototypes of plan s . Goo gle Drive was the main hub for participant collaboration . The project provided teachers with for their classrooms; h owever, two of the teachers did not receive classroom specific and instead had to secure access to a limited numb er of school owned for their students. Two teachers at other schools who received from the researchers already had access to their own tablet computers and used them in their class routinely. A mix of qualitative ethnographic rese arch methodologies (transcripts and field notes of meetings, mid process survey responses, interviews with teachers, field notes of observations of classrooms, and shared artifacts) and quantitative data tools (all classroom observations underwent a rating rubric, measure ment learning management system) were used. Ultimately, d ata from only seven teachers


61 were analyzed due to teacher attrition. The findings related to were reported in the use of digital tools and cha nges in teacher learning. The researchers instructional tools, which were housed in Google Drive . A teacher reported that she had her students make use of Google Docs to bot h collaborate and submit their individual homework in the digital environment. From the observations, the student favored over their own tablet computers. In their mixed method research study, Sahin et al. (2016) investigated use i n teachers teaching 6 th 12 th level in teaching with and their attitudes toward the process . The at all , after they incorporated into their classroom within the prior year . T eachers were also asked if they have any concerns regarding their implementa tion. The researchers selected schools that were already implementing initiatives and in which teachers already had . No training regarding was provided. 553 mathematics and science teachers from 30 schools were surveye d retrospectively to report their experience s in using and how they felt about the devices in using was significantly correlated with the number of technological tools they h ad access to, but was not statistically related to their level of teaching experience. According to the retrospective survey of pre and post implementation of were negative. Answers to open ended questi ons demonstrated that teachers need ed technical support using


62 and that the lack of such support was a block in their implementation , with the majority of teachers report ing that they need trainings to integrate into their classroo m. In an international study on and Google Apps , Blamire and other researchers from European Schoolnet (2016) explored the impact of administrative tasks at school. T hey also examined the role a professional development program played in supporting teachers to innovate, affecting their practices, and solving challenges in implementing innovation. The program was aimed at providing essential skills and knowled ge teachers need to use technology in an effective and pedagogically sound way. It included workshops and sessions about Google tools, how to use them, and the creation of learning scenarios and activities. In this qualitative study, twelve teachers from six schools in three different countries attended the program. The data was collected from the participating teachers through questionnaires, blogs post, interviews, mini case studies, statements during webinars and the program, video clips, and instructi onal materials developed by the teachers. The findings of the study demonstrated that most teachers benefited from the program , and schools aimed for more use of both in and out of the school. Teachers reported that after the project , they ga ined understanding in digital competence and online collaboration. They also described adopting new approaches and shift ing their perspective toward giving students more choice in the classroom. In addition, schools started implementing changes at the inst itutional level on using


63 for instructional and administrative purposes. Teachers identified several challenges to the use of in the classroom , such as low technology skills and their l ack of time to use . Some also fel t that the did not aid with promoting creativity among students or engaging students more . the economic value and benefits of using in K 12 schools. The researchers examined learning environment s of twelve school systems (including public, private, and charter schools) that used for educational purposes and provided a comparative cost analysis of and alternative devices. As a result of interviews with educators, IT staf f, and administrators, the researchers concluded that relatively less technical support was needed , compared to other technology, to implement in classrooms, which in turn meant schools would need to employ fewer IT staff. Another discovery was that teachers spent more time teaching , and administrators spent more time managing, when they used , making them more efficient and effective in their jobs . The d eployment of also made it easier to implement 1:1 lear ning methods. Generally, all of these studies examined how teachers integrate d integration Chromeb practices, teachers attitude toward using , and the benefits of in terms of economic value. In general, t eachers and instruction were the main focus of the research studies , demonstrating that there is a


64 gap in the literature analyzing how students use both in and out of school and how they feel about the experience t oward . review of existing studies helped illustrate what is missing in research on and determine how to address that gap making it one of the first empirical studies in this field examining this topic . Studies on Laptop Use in Technology Acceptance Framework E xtensive research on laptop use has relied on TAM. Correlational studies explaining the interrelationships among the elements of different technology acceptance models, particularly those using a structural equation model , are abundant. The participants in these studies were mostly teachers ; s tudies examining There are a plethora of research studies that incorporate TAM to explain researc h designs and structural equation modeling to test the interrelationships among TAM components. In their meta analysis of studies published between 1986 and 2013, used actual use of technology as an outcome variable, while others considered behavioral intentions and actual use as outcomes, and excluded attitude components. In a more recent meta analysis, Scherer, Siddiq , and Tondeur (2019) examined 114 empirical articles and i dentified four models used across TAM studies. The first model focuses on behavioral intentions as the final outcome , while t he second model uses intentions and actual use as outcomes. The third model adds external variables to the first model , and t he fou rth model is the most comprehensive one , adding external variables to the second model as predictors to usefulness and ease of use. Across all


65 four models, the hypothesized paths were found to be statistically significant and could be established empirical ly. Apart from the models the meta analys es identifed, there are other studies that a particular definition. Moses, Wong, Baker, and Mahmud (2013) examined attitude toward laptop use with only two predictors, usefulness and ease of use , in their correlational survey study with an international sample. They used SEM with data from 292 science and 278 mathematics teachers in secondary schools. Their main hypothesis was that perceived ease of use and perceived usefulness were the best predictor s of attitude toward laptop use. According to the results, perceived usefulness was a statistically significant predictor of attitude toward laptop use. However, perceived s toward laptop use. The f indings were found to be similar for both groups of teachers. In a different model, Teeroovengadum et al. (2017) assessed the determinants of ICT adoption by secondary school teachers in their instruction , statistically controlling for gender, age group, a , instead preferring hierarchical regression models to identify which group of variables explained more variance in ICT adoption. They included usefulness and ease of use as predictors, with the addition of s everal external variables, such as computer self efficacy and ICT policy. 368 teachers from 15 different schools participated in this study. The results indicated that neither of the demographic variables demonstrated a statistically significant effect fro m any TAM components. Perceived usefulness and perceived ease of use were both shown to have a statistically significant positive direct effect on ICT


66 adoption. Top management and peer support and competencies in us ing specialized ICT tools were additional variables found to A few research studies on laptop use in the TAM framework focus on students. In a five year long international study, Berger Tikochinski et al. (2016) examined the impact of a 1:1 laptop program norms, self efficacy, and behavioral intention s toward learning with laptops , according to TPB and attitudes and perceptions t oward learning with a 1:1 laptop. In this study, a 1:1 laptop program was implemented in two elementary schools , in the 5 th and 6 th grade s, and in one junior high school, in the 7 th through 9 th grade s (770). Teachers received professional development trai ning and follow up support for using laptops in the classroom , but determine d themselves how to use laptops in the ir lesson s . The researchers tracked the students for five years ; the last measurement was taken via a questionnaire given to 770 junior high s chool students. The researchers efficacy were shown as predictors for their intention to learn with laptops. The attitudes of students who started the program at a later stage were more positive than those who began earlier. In summary, the majority of the research on laptop use in the TAM framework is focused on teachers. Behavioral intentions are the most used outcome , and several external variables have been added to TAM models to examine interconnections between the elements of TAM. Yet W ttitude s toward computers within the


67 yet unanswered, though the studies reviewed here have helped fill some of the gaps in research in technology acceptance.


68 CHAPTER 3 METHOD The purpose of this study is to and their use of , with technology acceptance as a . Two research questions guided itudes toward ? This section includes an overview of the study design, participants and context in which the data was collected, instruments, and data collection and analysis. Study Design To answer the two research questions of this study, a mixed method research design was used , and data collection occur ed in two phases , (2013) sequential design. This type of design helps illustrate, enrich, and explain the results from one strand using the results from the other strand (Caracelli & Green, 1993; Creswell, 2014). Specifically, t his study adopt ed an explanatory sequential mixed method design, which includes data collection and analysis of quantitative and then qualitative data in two connected phases in one study (Creswell, Plano Clark, Gutmann, & Hanson, 2003) , with the q ualitative phase (text dat a) build ing on the quantitative phase (numeric data) (Ivankova, Creswell, & Stick, 2006). The rationale of the quantitative data in the explanatory sequential mixed method design is to provide a general view about the problem under investigation. With the support of qualitative data, thoughts in a more detailed way (Creswell, 2003; Tashakkori & Teddlie, 1998). The


69 s and opportunities for the exploration of the quantitative results i n The overview of the research design used for the current study is summarized in Table 3 1. Table 3 1. Overview of the research design used in this study Quantitative Phase Qualitative Phase attitude toward Chrom e books Measured by CAMYS Investigated by six structured questions in an interview Purpose: To obtain a complete toward feelings and deeper responses about Stud e Measured by Current Technology Use Survey Examined by ten open ended and structured questions in an interview Purpose: To identify purposes students use for Purpose: To establish a knowledge base for how students use as a learning tool and to ask for stories to reveal details. Quan t itative data from a survey help ed form ing attitudes toward and their use of . Surveys are frequently used in the educational technology field to study technology attitudes and use (Afshari et al., 20 13; Ayres, 2002; Cai et al., 2017; Meelissen & Drent, 2008; Smith et al., 2000; Teo, 2008; Teo & Noyes, 2008) because they provide economic and viable ways to collect data. The quantitative phase of this study includes two parts. In the first part, a gener was examined. Using Computer Attitude Measure for Young Students (CAMYS), quantitative data was i n terms perceived ease of use (PEU), perceived usefulness (PU), and


70 affect toward computer (ATC).The result s of the survey was used to purposefully select students for the qualitative phase, which was explained in details in the following section. In the s econd part, a particular set of tasks completed by using was identified to provide a general understanding of what purpose students use for. Qualitative sources of data through individual interviews with students focus ed more on their experiences in terms of using and their attitudes on particular aspects of . Personal qualitative stories regarding provide d depth and sophistication of the actual use of as well as how they feel about itself. The in tent in the qualitative phase was in the framework of technology acceptance and on how they feel about using and its usefulness and effectiveness. Col lectively, in depth interviews elicit ed a richer interpretation of use in terms of its acceptance and provide d deep use. Context This study was conducted in a laboratory sch ool of a research university. It is a public school which has a unique characteristic in that it provides opportunities for collaboration with researchers. This school which is established in 1934 is affiliated with the University of Florida. There are app roximately 1150 students in all K 12 grade levels totally. Florida Department of Education provides funding for this institution which is designed as a special school district. P.K. Yonge is expected to develop solutions to some educational problems in the state of Florida and as a result the other school districts can be provided with successful instructional programs.


71 The population of the school is a good representative of the state of Florida because the school administration purposefully admits/selects students from different cultural and socioeconomic backgrounds. The school adjusts the percentages for different categories of the population in the school according to Florida Department of termined according to following characteristics: gender, race/ethnic origin, family income, exceptional student status and academic achievement level. There are different needs of students in P.K. eeting the needs of each student. The number of students varies between grade levels. For example, 54 students are in Kindergarten through 3 rd grade , w hereas there are 66 students in 4 th and 5 th grades. The 6 th , 7 th , and 8 th grades include 110 students. Teacher s teach all the classes in one g rade level in 6 th through 12 th grades . Teachers in this school are mainly open to any research activity in the school. Since this is a laboratory school, extensive investment for new technology have been made and n professional learning communities to support each other and they are also encouraged to participate research studies or conduct their own studies. To meet the needs of all students with different backgrounds and make them ready for a future in which tec hnology is ubiquitous, a 1:1 initiative started in 2015. By allocating a device to each student 4th grade through 12th gr ade, it is aimed to enhance learning digitally. In addition, student engagement in classrooms has been broaden to out of s chool by their . By using in the school, the use of online resources and digital tools can also be increased. This


72 reduces the barriers related to access comprehension of the content to meet the needs of all students. Further, the use of supports tiered academic and behavioral interventions for goal setting, improved self regulation and self efficacy. The students in 4 th and 5 th grades are assigned to for using them in the school. The other students in 6 th and 9 th grades were provided devices for the use at school and home in the 2015 2016 school year. This has been extended to all students in 6 th to10 th grades since the end of that school year. This means that 6 th grade students are the group of students w ho start s and outside of school. While distributing the devices, parents/guardians and students have to sign and return some documents for agreement and consent: device agreement, web apps consent and acceptable use agreement. Students in 4 th 12 th grades are required to use their . They are responsible for bringing their to all their classes unless the teachers tell them the opposite. The devices are for instructional use in a school day. Students and calendars, and schedules by using their . the school is mandatory which means way their teachers require. Students are expected to use their to complete their school work and if there is a malfunction of the device, the school provides technical support . Students could als purposes at home in which the use is voluntary. In all , Google Suite exists and can be used for instructional purposes. Google Calendar , Google Classroom , Google Docs and Google


73 Sites are available to the use of all students in P.K. Yonge. By using Google Calendar which is an individual calendar, students can organize their schedules, daily activities and assignments. Google Classroom makes the use of Google tools for instructional purposes easier . Students can use Google Docs as word processing, spreadsheets, and presentation tool similar to Microsoft Office . Finally, G oogle Sites can be used to create websites by students and teachers. In addition to Google Suite , a Learning Management Syste m (LMS) is also available for upper grades. By LMS, teachers can plan, apply and assess learning processes. They can also create and deliver content through LMS. LMS allows teachers to monitor student participation and assess their performance. Through Go ogle Suite and LMS used in the school, students can collaborate and communicate with other students in the school and their teachers. They can also create, edit, and share files for their school related works such as assignments and projects. All the serv ices are totally online and students can access them 24/7 from their or any computer which has Internet access. Participants This study focused on 6th and 7th grade students in the developmental research school in Florida. 6 th and 7 th graders were selected beginning in 6 th grade, students were given Chromebooks for both home and school use. For this research study, two differen t selection techniques were used. For the quantitative phase, convenient sampling was used, and the survey, including CAMYS and Current Technology Use, was sent to all 6 th and 7 th graders. The participants were informed about the purposes of the study. The y were also told that their participation to the study was voluntary and that


74 they could re ject to take the survey or to be interviewed. I wanted all participants to use their first names to access them for the interviews if needed but I reassure d that the ir responses were kept confidential. They were also reassured that their identities were not a scertained in any research report or publication. These were done to decrease social desirability bias on reponses to surveys and interview questions. In these g rade levels, there are 220 students. Ten students were absent on the days of survey administration. T wenty f our students disagreed/declined the participation in the study. Four students submitted the survey fully empty after agreeing/accepting the participation in the study. There were 182 students in total participating in the study. Student demographics were provided in Table 3 2. Table 3 2. Student demographics participatin g in the study Category n Percentage Grade level 6 th grade 89 48.9 7 th grade 93 51.1 Age 11 18 9.9 12 85 46.7 13+ 78 42.8 Gender Female 89 48.9 Male 93 51.1 use in a week in school Less than an hour 0 0 About 1 2 hours 7 3.85 About 2 3 hours 50 24.5 More than 3 hours 125 68.7 use in a week outside of school Less than an hour 69 37.9 About 1 2 hours 68 37.7 About 2 3 hours 31 17 More than 3 hours 14 7.7 There was only one student older than 13 years old. Table 3 2 shows that the number of students in each gender and in each grade level was close. The majority of the students (89%) was older than 11 years old. The hours students spent using in a week were differentiated by where they used it. In school, 68.7% of the students used more than 3 hours.


75 There was nobody using less than one hour in school. On the other hand, the majority of the students (75%) spent less than 2 hours using outside of school. Relatively lower percentage of the students (7.7%) used more than 3 hours outside of school. For the qualitative phase, a mix of sample of 6 th and 7 th grade students who take the survey was purposef ully selected. The number of students to be interviewed was determined based on two criteria: gender, which has been shown as a critical variable in explaining computer use (Meelissen & Drent, 2008; Sáinz & López Sáez, 2010) and their attitudes toward Chro , which were calculated based on the scores from CAMYS. As for gender, equal number of students from each gender was randomly selected. For the second criteria of selection, the average scores from CAMYS was used to select students. Overall, stude nts can get scores 12 to 60 from CAMYS. There was not a specific cutoff to differentiate students in terms of attitude levels (i.e., low, medium, or high) stated by Teo and Noyes (2008). However, based on the previous studies that used CAMYS (Efendioglu & Yelken, 2010; Milic & Skoric, 2012) and similar Chau, 2001; Teo, 2008), an approach to divide students up into two groups was embraced. According to this approach, using a frequency distribution table and central tendency statistics, the above average scores from CAMYS were in the


76 As a final filtering, I sorted the total scores in an ascending order. For the lower group, four students with the lowest scores were selected for interviews. Four more students were identified as substitutes. For the higher group, the male interviewee was randomly selected out of ten male students who had the score of 60. For selecting three female participants, scores were sorted in an ascending order. Three female students with highest scores were selected. Four more students were ran domly selected for being substitutes. At the end of filtering process, eight students w ere selected for individual interviews. Table 3 3 presents the number of students selected in terms of the two criteria. Table 3 3. Number of students interviewed Male Female Lower group 3 1 Higher group 1 3 Four male and four female students who belong to different attitude groups was selected for individual interviews. This approach helps to identify the ways are used in terms of student attitudes and allows to compare their experience with . Instruments There were three instruments used in this study. For the quantitative phase of the study, CAMYS and Current Technology Use Survey; for the qualitative phase of the study, a researcher developed interview protocol for semi structured individual interviews was used. I tems regarding demographics of students, such as age, gender, and experience/time spent using in and outside of school w ere also included in the survey.


77 Computer Attitude Measure for Young Students Computer Attitude Measure for Young Students (CAMYS) developed by Teo and Noyes (2008) was used in this study (See Appendix A). The theoretical framework of the measure is based on assessing computer attitudes proposed by Kay (1993) who drew on the tripartite model of attitude (Breckler, 1984), the theory of planned behavior comprehensive account of measuring attitudes toward computers. There a re 12 items that spread over three factors (four items in each factor) in the instrument. The factors in the instrument are 1) perceived ease of use, 2) perceived usefulness, and 3) affect toward computer, which are aligned with many technology acceptance models. These three components explained 59.18% of the total variance. The items are measured on five point Likert scale: strongly agree (5), agree (4), neutral (3), disagree (2), and strongly disagree (1). The factors can be either used separately or summ ed across factors to obtain an overall score for the general attitude toward computers. The minimum and the maximum score a student can obtain for each factor is 4 and 20, respectively. On the overall attitude toward computers, students can get scores from 12 to 60. refer to students at the ages of 10 and 14. In the development process, the researchers took a strong approach to fine tune the semantics and syntax of each item so that students at these ages can simply answer the items. There is no reverse/negatively items of this instrument was


78 ha coefficients of the instrument calculated by Teo and Noyes (2008) is .85. Those for the perceived ease of use, perceived usefulness, and affect toward computers are .64, .74, and .81, respectively. All alpha coefficients indicate strong to acceptable va lue for re use of the instrument (DeVellis, 2003). Alpha coefficient for this study was reported after collecting the data. CAMYS has been cited in research studies extensively for investigating relationships of various emerging technologies (Borhani, Vata nparast, Abbaszadeh, & Seyfadini, 2012; Bujak et al., 2013; Yuksel, 2012; Zschocke, Beniest, Yayé, & (Efendioglu, 2012; Efendioglu & Yelken, 2010; Milic & Skoric, 2012). CAMYS appeared to be used in various multidisciplinary fields and produced meaningful research evidence. This instrument was also validated again by Asil, Teo, and Noyes (2014). According to this validation study, it was confirmed that this instrument still can be used invariance study indicated that the instrument shows invariance across gender, which means CAMYS can be used for gender groups of young students. Current Technology Use Survey A survey developed by Lei and Zhao (2008) was general use of . The main purpose of using this survey is to reveal and identify percentages of use to complete commonly used tasks for learning pu rposes. The survey includes 10 independent items regarding specific tasks students perform on their and the purposes for which are used: 1) Doing homework, 2) taking notes in the classes, 3) sending and receiving emails, 4) search ing information for school work, 5) surfing online for fun, 6) chatting


79 online, 7) working with specific software, 8) playing computer games, 9) creating websites, and 10) participating online discussions. The question stem asks students to mark the tasks for which they use , which makes the questions binary (yes or no). Interview Protocol experience in using and their attitude toward based on recommended strategies for preparing an interview protocol from Patton (2002) and Seidman (2013). Face t o behavior and thereby provides a way for researchers to understand the meaning of that information about actu al experiences of . The style of interviews was semi the purpose of taking each respondent through the same sequence and asking each respondent the same questions This format was aligned with the purpose of this study because the semi structured interview allow ed 2002, p. 56) about their Ch use. Because technology use might have various meanings, the use in this interview protocol as a learning tool. The interview protocol includes open ended and structured quest ions use and additional guiding and probing questions to open s.


80 elicit ed deeper responses during the conversation and gave the researcher the ability and the flexibility to probe further when needed (Patton, 2002). The content of the inte rview questions was based mainly on technology acceptance framework and models used in this study (Ajzen, 1985; Davis, 1989; Fishbein & Ajzen, 1975) and previous studies in the literature. All interview questions mainly fall into technology use and attitud e, which are two of the constructs in TAM, TRA, and TPB frameworks used in this study ( See Appendix B). For the questions regarding use, these three frameworks guide d the scope and the nature of the questions. As described in TAM (Davis, 1989), technology usage and its description are important. Therefore, questions asking how student use and prompts for them to give details about their typical use of were included in the protocol. In addition, results from previous stu dies and reports on were also used while interview questions are constructed (Butoi et al., 2013; Cox, 2014; Denton, 2012; Google Inc., 2014; 2015; 2016; Kimmons et al., 2017; Leary et al. 2016; Muniz, 2018; Vickers et al., 2015). In general, the questions asked in these studies address ed how students are currently using in school and outside of school and their experiences related to their use to support their learning. In partic ular, the interview protocol had questions and promp ts that encourage students to talk about how they complete an assignment or a project using , the apps they are using on , and the way they use when they study with a classmate or in a group. An important aspect of Chro use is teacher directed use of . Thus, a question and guiding questions about


81 how their teachers use and examples of in struction led by were also included in the interview protocol. Using technology acceptance models mentioned above, three questions related to students were also added to the interview protocol that address perceived ease of use, perceived usefulness, and affect. Students were asked what they think how Chr are effective, useful, and user friendly. In specifically laptops (Cai et al., 2017; Chau, 2001; Smith et al,, 2000; Teo, 2008), there were questions and prompts to dig more into what general feelings (likes/dislikes) they have when using were used. were adjusted to the context of questions were prepared to establish a knowledge base for how students use and to ask for st ories to elicit details. In addition, according to Patton (2002), the questions were planned to reveal feeling about both and . The interview protocol was also piloted with two students from different middle school s. Through piloting, content and face validity were improved. While writing questions and asking those questions during an interview, several important considerations must be taken into account. Interviewing young students is different than interviewing a dults. To have interviews with better quality, the researcher


82 needs to build rapport with participants, which can be primarily achieved by doing the interview in a convenient, well designed setting (Irwin & Johnson, 2005). Second, asking complex, open ende d questions at the very beginning of an interview can be challenging for young children. Therefore, more close ended, direct questions should be asked at the beginning to help children more engaged in the topic and help them become less tired with the comp lexity of the questions (Wilson & Powell, 2001). As the interview proceeds, more open ended questions can be asked. Third, selecting words used while interviewing is also critical. The words should be appropriate to the developmental stage of the children who are interviewed (Kortesluoma, Hertinen, & Nikkonen, 2003). The wording of the questi ons in the interview protocol was de termined according to the needs of 6 th and 7 th grade students so that children in this study could easily understand them. Data Col lection There were mixed method explanatory design. The first phase included the administration of CAMYS and the demographic items to students. The second phase was consisted of conducting ind ividual student interviews. Parent consent for the survey and interviews were obtained through an opt out form with an IRB protocol ( See Appendix C and Appendix D ) . Since this is a laboratory school, parents were aware and open to studies that might be conducted in the school. When they do not want their children to participate a research study, they sign the opt out form. Survey Administration The survey, includin g CAMYS and Current Technology Use Survey, was administered online through Qualtrics. The coordinator of educa tional technology and


83 the social studies teachers of 6 th and 7 th grade at school allocate d a time for students to take the online survey. Students was obtained electronically. When the students press , this means that they accepted to take the survey. They could also exit from Students taking the survey were ion in a classroom. It t ook 10 15 minutes to administer the survey. There were (CAMYS) and use. The items were organized such that no two items from the same factor in CAMYS was next to each other. Students were told that the survey was not a graded test or ungraded activity and that there were no correct answers. Their honest responses were encouraged as much as possible. Individual Interviews I conduct ed face to face , one on one interviews with eight students who ha d experience with . The social studies teachers helped me to schedule interviews. On the day of interviews, teachers assisted me with selecting proper settings. I chatted briefly wi th students before the interview to help them be relaxed. First, I introduce d myself and the purpose and the nature of the interview. After that, I asked for their consents to participate the interview. If they accepted, I follo wed the order of the questio ns on the interview protocol document during the meeting. The focus was on collecting in depth data about the whole experience of students with . I asked each question when the timing was appropriate not to interrupt the student as s/he is talk ing and collecting his/her thoughts. All interviews were tape recorded. I also took handwritten notes and recorded information from interviews. These anecdotal notes provide d information about d these notes as additional


84 information into their views and feelings about and also as contextual information to introduce students in this study. Data Analysis Quantitative Data Analysis After implementation of the instrument, the response rate was reported. Firstly, descriptive statistics (means, frequencies, and standard deviations) of the three factors of CAMYS, Current Technology Use Survey, and demographic variables were reported. Secondly, the differences in attitudes toward were investigated in terms of age, gender, and time spent using in and outside of school through t test and ANOVA using SPSS 23 . The results address ed the first research que stion. Qualitative Data Analysis Thematic analysis was used to determine, analyze and report patterns in interview data (Braun & Clarke, 2006) . across different theories and epistemologies. There are two types of thematic analysis: inductive and deductive. Researchers code the data without an effort to fit the data in a pre existent coding frame in inductive thematic analysis so it is driven by th e data. In contrast, in deductive perspective and interest strongly impact the data analysis. Therefore, deductive 006, p.12). Researchers choose inductive or deductive analysis depending on the purposes and ways of data analysis. An inductive approach involves open coding while a deductive approach involves a priori coding (Boyatzis, 1998). Depending on i nterests, some parts of the data could be analyzed and presented in a more detailed way (Nowel,


85 Noris, White & Moules, 2017). Since explanatory sequential mixed method design in which qualitative phase could be used to explain the results from quantitative phase was used in this study, the deductive approach was preferred. It allowed survey results to be explained and understood more deeply by interview responses. All transcripts was read and the passages that represent any instances of the key concepts of TAM were highlighted. During the ana l ysis, I followed the steps of thematic anlaysis. First, I became familiar with the data through repeated reading and then initial codes were generated with some specific questions and ideas in my mind that I want to benefit for my coding process . For example, I used entertainment and communication as initial codes. I tried to create as many codes as possible. After generation of the codes, I searched for themes. For example, for the codes entertainment and co The data w ere hand coded for themes. I sorted the codes into potential themes and sub themes. At the end of this stage I had a list of candidate themes. Themes are for expression of the latent meaning tha t is found in categories. Then, I reviewed the themes I created. During revision of the candidate themes, some themes were collapsed into each other and some of them were discarded/changed. C hromebooks The n ext step was defining and naming the themes. While naming the themes, I tried to be concise and clear to help readers to have a sense of what the themes tells about. Finally, I wrote the report for qualitative findings. confidentiality . Analysis of qualitative data in this study was a recursive process in which


86 the res earcher moves back and forth if necessarry rather than a linear process in which the researcher proceeds to next step after the one step is completed. During the qualitative data analysis, I read the data many times. After creating codes, I reread the data and made an evaluation of the relevance of the codes with the data and theoretical framework. After code creation, I applied the same recursive approach to the creation of themes. The results addressed the second research question. While doing thematic analysis, I made some decisions as a researcher. First, I decided what counts a theme in the data set. Second, for thematic analysis, researchers should decide that they provide rich description of the entire data set or more detailed depiction of one particular theme. In this study, I preferred providing a rich description of my entire data set. Although there is a possibility of losing some depth of the data, a rich overall description was ensured. For the confidentiality in qualitati ve data analysis, I removed identifiers and used codes for each interviewee . Research Design and Rigor The research design of the study was developed on technology acceptance framework in which attitudes toward and use of computers are the main components. The design did no t incorporate one of the technology acceptance models, instead, focusing on the general outline of the components in the framework. Both attitudes and use were defined in the framework of technology acceptance and were based on previous s tudies and theories, which contribute to rigor in design, instruments, data collection, and analysis. Quantitative Phase For the validity of the data collected through CAMYS, I review ed the validity evidence using the data I collect ed , such as factor loa dings, error variances, explained


87 total, and individual variances. I also compare d what I find with the recent validation study of CAMYS by Asil et al. (2014) to ensure that the validity evidence is similar. For the reliability of the data via CAMYS, I rep ort ed coefficient when the data was collected for this study. A cutoff .60 suggested by (DeVellis, 2003) was used to evaluate the coefficient. Qualitative Phase In the qualitative phase of this study, to determine if or not the findings are accurate and consistent, I employ ed multiple strategies (Creswell, 2014). This help ed me address trustworthiness, credibility, and authenticity of the study (Creswell & Miller, 2000). Before collecting data, the interview questions were reviewed by two research experts who are knowledgeable about technolog y and its use in K 12 settings , an d two middle school students similar to the students targeted in this study. This helped to make effective changes and revisions on some vague questions . Additionally, the interview questions became better to elicit deeper responses from participants. Peer debriefing help ed me enhance the accuracy of the findings. I locate d a person for him/her to review and pose questions regarding the study. According to the feedback that my peer provided, I fi xed some errors in my analysis and made changes in the final r eport of results. External auditor helped me to review the entire qualitative phase of the study. This person was someone who is not familiar with the topic of the study and who can provide objective comments on accuracy of transcription, relation between the research question, the interview questions, the qualitative data, and the data analysis. An audit trail which was first introduced by Lincoln and Guba (1985) was done in this study to increase the confirmability and trustworthiness of the results of t he study. I sent the raw data, my notes during analysis and list of themes to an expert auditor to review. This process helped for self questioning of my decisions during data analysis. It also helped me to have a transparent research. I also tried to generate thick, ri ch descriptio n of the results. I provided interconnected and abundant details when I was writing about a theme, an activity or a participant. I frequently revisited the raw data and added new description if I could find. Th is helped me to delve into my data and find every important detail which could be important for my study.


88 As suggested by Gibbs (2007) and Creswell (2014), I use d several procedures to provide reliability. I read the interview transcripts multiple times and check ed them to ensure that there was not any mistake during the transcription. I continuously compare d the data in terms of codes and themes across the interviews by writing definitions and descriptions. Subjectivity Statement Merriam (1998) states that to get richly descriptive results, the researcher is a primary instrument. If the researcher does not aware of his/her own values and objectives, this may affect the validity of the collected data (Creswell, 2013). According to G lesne (2006), clarification of researcher bias help with trustworthiness. If the researcher can clarify the bias that are brought to the study, this results in an open and honest narrative (Creswell, 2014). A subjectivity statement is a good way to help t he researcher to recognize and reflect on in what ways cultural background, experiences, feelings, beliefs and previous knowledge may affect the decisions made in the study conducted. The topic which is selected for the study, how hypotheses and objectives are formulated, in what way the methodologies are selected and data is interpreted are statement, readers can make critical evaluations of truthfulness, credibility and the validity of the study. During my bachelor degree, I took classes in which I was using Moodle to submit Those were the years in which technology use was becoming po pular in education. Using an online system in my classes made me aware of the importance and different ways of technology use. After my graduation, I became a science teacher in a middle


89 school aiming to integrate technology effectively. I was using diffe rent technological tools in my classes to make my students more engaged and learn better. While teaching, the school decided to conduct a 1:1 iPad initiative. As a pilot, only 6 th graders and teachers were given iPads in the school. I did not teach 6 th g rade so could not experience how it went. However, as a former teacher who was a part of a technology initiative, I have been motivated to question how students accept and use the school issued devices. After teaching a few years, I decided to pursue a do ctorate degree in Educational Technology. How teachers and students use technology and how technology is integrated more effectively resonate me during my Ph.D. journey. As a Ph.D. student and a member of a research team, I participated in a professional l earning community (PLC) in which the goal was helping lead teachers to implement technology to meet the needs of their students at P.K. Yonge K 12 School. These lead teachers who are responsible for one grade level are expected to provide instructional sup port for struggling and gifted students and helping other teachers considering needs of their students and planning instruction. With this role in the school, these lead teachers may impact every teacher and student in the grade levels they are responsible for. These teachers are provided knowledge for the use of one of the Google extensions: Google Read and Write . In this PLC which met once or twice a month, teachers learned how to use this extensions for different purposes. After learning, they implemen ted the tools available in Google Read and Write . Then, they shared how they implemented and what they struggled with. As a PLC, we learned together and discussed how teachers used technology for different purposes in different grade levels. I had the cha nce to


90 observe the teacher side of a technology initiative. However, we did not investigate how students accept and use their devices. I believe that student acceptance and use of technology are also very critical to integrate it successfully. During the individual interviews, as a researcher, I was involved in an intensive experience with students. As Locke, Spirduso, and Silverman (2013), this kind of involvement might pose some critical, ethical, and special threads into the research process. As suggest ed by Creswell (2014), I identify some biases, values and my own personal background about the topic of the study that might change the interpretation of the results. In addition to my personal background in technology, I have several beliefs about very critical for teaching practices and designing instruction. I believe that techn ology and innovation will fuel the future of education. Our students will have some careers which do not exist yet. Although we cannot imagine a life without the Internet today, it was scarcely available only for some big corporations in the past. As educa tors, we should be aware of technological advancements and make a substantial effort to prepare our students for the needs of future careers. Technology has been evolving with time. For example, paper and pencil was a new technology in a particular time period. Thus, laptops and iPads are the technology of this recent time period. If students do not share their pencils with their classmates today, sharing their technological devices will be nonsense in the future. Since technology use in teaching and lea rning processes will be inevitable, students should accept and use them effectively as their pencils and notebooks.


91 I tried to set aside my own experience and thoughts about and the ongoing efforts in the schools to clearly understand those o f students in the study.


92 CHAPTER 4 RESULTS and their use of , with technology acceptance as a . T wo research toward ? This section includes the results of the responses to the survey and the findin gs of the interviews. Responses to Computer Attitude Measure for Young Students Descriptive Analysis 182 students out of 220 responded to all twelve items in CAMYS as detailed in Table 4 1. Table 4 1. Descriptive statistics regarding the responses to CAMY S Minimum Maximum Mean Standard Deviation General attitude toward 17 6 0 52.07 7.31 Perceived ease of use (PEU) 5 20 17.41 2.54 Perceived usefulness (PU) 7 20 17.15 2.94 Affect toward 5 20 17.51 2.71 *General attitude toward total scores were calculated by totaling the three dimensions (4 + 4 + 4 = 12 items), as suggested by the developers, and ranged from 12 60 . Table 4 1 shows that the mean of the overall score was 52.07 out of 60, whic h is was high. T he mean of each of the three factors of general attitude toward was around 17. Each dimension has four items, and the sum of all four produces a total score for that dimension, ranging from 4 to 20. No one


93 lowest score across the three dimensions 5 out of 20in both PEU and affect toward Chromeb . Across all dimensions, the maximum total score, 20, was achieved. Mean Comparisons For mean comparisons, four factors were analyzed, using two different statistical tests. Gender An independent samples t test was conducted to compare attitude s toward , sortedby sex , as shown in Table 4 2 . Table 4 2. T test results comparing genders on general attitude toward n Mean Standard Deviation t D f p Female 89 51.2 9 . 8 5 1.411 180 .159 Male 93 52.82 .67 * For testing the assumption of equal variance across the groups, indicated equal variances across genders (F = 1.952, p = .164) , allowing for a t test analysis to be conducted. Table 4 2 shows that there was not a statistically significant difference i n the scores for females (M = 51.29, SD = . 8 5) and males (M = 52.82, SD = .67 ) in general attitude toward ; t (180) = 1.411 , p = .159. T he effect size for this analysis ( d = .21 ) was found to be s mall as indicated by for a small effect ( d = .2 0). This means that the two groups' means differ by a .21 standard deviation . Age Multiple group comparisons in terms of age and use in one week both in school and outside of school were reported as follows.


94 Descriptive statistics by age on general attitude toward are reported in Table 4 3. Table 4 3. Descriptive statistics by age on general attitude toward n Minimum Maximum Mean Standard Deviation 11 years old 18 37 60 51.39 6.40 12 years old 85 23 60 53.31 6.45 13 years old 78 17 60 50.97 8.20 As indicated in Table 4 3, the means of three age groups can be ordered from lower to higher as follows: 13 year old students (M = 50.97, SD = 8.20), 11 year old students (M = 51.39, SD = 6.40), and 12 year old students (M = 50.97, SD = 8.20). A one way between subjects ANOVA w as conducted to compare the effect of general attitude toward . Results are shown in Table 4 4. Table 4 4. ANOVA of general attitude toward by age SS D f MS F p Between groups 2 33.91 2 116 . 957 2.222 .111 Within groups 9368 . 650 178 5 2 . 633 Total 9602 . 564 180 * For testing the assumption of equal variance across the groups, showed equal variances across age groups (F = 1.015, p = .365). This indicated that ANOVA could be conducted. Table 4 4 shows that age did not have a statistically significant effect on general attitude toward at the p < .05 level for the three age groups [F(2, 178) = 2.222 , p = .111]. T he effect size for this analysis ( 2 = .024 ) was foun d to be small to medium as indicated by Cohen, Miles, and Shevlin (2001) convention for small effect ( 2 = .01 ) and medium effect ( 2 = .06) sizes . This means that 2.4% of variance of general attitudes toward is associated with each of the main effec ts, the interaction, and error.


95 Use in School Descriptive statistics on the effects of use in school over a week on general attitude toward are reported in Table 4 5. Table 4 5. Descriptive statistics on the effects of use in school over a week on general attitude toward n Minimum Maximum Mean Standard Deviation About 1 2 hours 7 48 60 55.29 4.19 About 2 3 hours 50 35 60 51.10 6.47 More than 3 hours 125 17 60 52.28 7.72 * No student reported using a in school for less than 1 hour . From Table 4 5, the means of three groups can be ordered from lower to higher as follows: about 2 3 hours (M = 51.10, SD = 6.47), more than 3 hours (M = 52.28, SD = 7.72), and about 1 2 hours (M = 55.29, SD = 4.19). S tudents spending about 1 2 hours on a in school had a higher general attitude toward compared to other students. A one way between subjects ANOVA was conducted to compare the effect of use in school over general attitude toward . Results are shown in Table 4 6. Table 4 6. ANOVA of general attitude toward affected by use in school over a week SS D f MS F p Between groups 124.943 2 62.471 1.1 72 .315 Within groups 9543.129 179 53.314 Total 9668.071 181 * For testing the assumption of equal variance across the groups, revealed equal variances across the groups (F = .455, p = .635) . This indicated that ANOVA could be conducted. Table 4 6 shows that there was no statistically significant effect of use in school over a week on general attitude toward at the p < .05 leve l for the three groups [F(2, 172 ) = 1.163, p = .315]. T he effect size for this analysis


96 ( 2 = .013 ) was found to be small as indicated by Cohen (2001) convention for a small effect size ( 2 = .01 ) . This means that 1.3% of variance of general attitudes toward is associated with each of the main effec ts, the interaction, and error. Use o utside of School Descriptive statistics on the effects of use outside of school over a week on genera l attitude toward a re reported in Table 4 7. Table 4 7. Descriptive statistics on the effects of use outside of school over a week on general attitude toward N Minimum Maximum Mean Standard Deviation Less than an hour 69 17 60 51.39 8.14 About 1 2 hours 68 22 60 51.72 7.64 About 2 3 hours 31 45 60 52.00 4.05 More than 3 hours 14 39 60 55.07 6.58 From Table 4 7, the means of three groups can be ordered from lower to higher as follows: less than an hour (M = 51.39, SD = 8.14), about 1 2 hours (M = 51.72, SD = 7.64), about 2 3 hours (M = 52.00, SD = 4.05), and more than 3 hours (M = 55.07, SD = 6.58). S tudents spending about 1 2 hours with a in school had a higher general attitude toward compared to other students. S tudents spending more than 3 hours with a outside of school had higher general attitude toward compared to other students , but only 14 studen t s out of 182 report ed that they used this way . A one way between subjects ANOVA was conducted to compare the effect s of use outside of school over general attitude s toward . The r esu lts are shown in Table 4 8.


97 Table 4 8. ANOVA of effects of use outside of school over a week on general attitude toward SS D f MS F p Between groups 193.017 3 64.339 1.20 9 .304 Within groups 9475.055 178 53.231 Total 9668.071 181 * For testing the assumption of equal variance across the groups, showed equal variances across the groups (F = 1.721, p = .164) . This indicated that ANOVA can be conducted. Table 4 8 shows that there was no statistically significant effect of use outside of school in a week on general attitude toward at the p < .05 level for t he four groups [F(3, 178) = 1.20 9, p = .304]. T he effect size for this analysis ( 2 = .020 ) was found to be s (2001) convention for a small effect size ( 2 = .01 ) and a medium effect size ( 2 = .06). This means that 2% of variance of general attitudes toward is associated with each of the main effec ts, the interaction, and error. Responses to Current Technology Use Survey The Current Technology Use Survey was used to answer the second research question of this study. The main purpose of deploying this survey was to reveal the extent to which were used for common learning tasks . The number and the frequency of students who used to complete each of the ten tasks are provided in Table 4 9. As shown in Table 4 9, there were two tasks that most student s used their to complete: Doing homework (98.3%) and searching for information for schoolwork (98.9%). Taking notes in class (79.2%) was the third most completed task using . The tasks with the lowest positive responses were c hatting online


98 (3.4%) and c reating websites (16.9%). The percentages of students who used their to complete other tasks ranged from 36.9% to 63.7%. Table 4 9. Descriptive statistics regarding the tasks completed using Yes No Total % N % N Doing homework 98.3% 178 1.7% 3 181 Taking notes in class 79.2% 137 20.8% 36 173 Sending and receiving emails 63.7% 109 36.2% 62 171 Searching for information for schoolwork 98.9% 179 1.1% 2 181 Surfing online for fun 55.4% 92 44.6% 74 166 Chatting online 3.4% 6 96.6% 171 177 Working with specific software 62.4% 83 37.6% 50 133 Playing computer games 61.1% 105 38.9% 67 172 Creating websites 16.9% 29 83.1% 142 171 Participating in online discussions 36.9% 59 63.1% 101 160 questions regarding some tasks . Interview Participant Profiles Two groups of participants were interviewed for this study according to their attitudes toward : Four participants were selected for the low att itude group, and 4 participants were selected for the high attitude group . The average score in the survey was 52.07. The students who had lower scores than the average were identified as the low attitude group, and all the students in the high attitude group had scores higher than 52.07. There are a considerable number of studies showing that female students have less favorable attitudes toward technology than male students (Chou, Wu, & Chen, 2011; Colle y & Comber, 2003, Collis & Williams, 2001), and a recent meta analysis by Cai, Fan, and Du (2016) also identified this trend.


99 To further understand these findings, my study included three males and one female in the low attitude group, whereas the high attitude group was made up of three females and one male. Low Attitude G roup These interviewees were selected from the student s who had the lowest scores for attitude toward . In this group, there were three male students and one female student. Interviewee 1: J. J. was a 13 year old female in the 7 th grade . She received a score of 17 out of 6 0 for general attitude toward in the survey . and paying taxes for her grandparents. She uses her at school for more than 3 hours , and at home for less than 1 hour , for a mixture of school related and non school related pursuits like doing homework, taking notes in class, searching for information for schoolwork, watching videos on YouTube, surfing online for fun, working with specific s oftware , reading digital textbooks, and participating in online discussions. She reported that she did not use the to learn things. She reported that it was not easy to learn how to use the , but she tried hard to figure out how it worked. She found using the at using time, she indicated that she felt scared of using the . She found the to be more updated than other techn ological devices like her computers

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100 she uses. Interestingly, although she chose the as her favorite device, she reported feeling neutral about using her . Interviewee 2 : S. S. was a 13 year old male in the 7 th grade . He received a score of 22 out of 6 0 for general attitude toward in the survey. He defined technology as He reported using his at school for more than 3 hours and at home for less than 1 hour , for doing homework, taking notes in the class, searching for information for schoolwork, surfing online for fun, and playing computer games. His technological devices include a , a phone, a home computer, and an Xbox . He used his eported, he regularly played games with his Xbox for 30 minutes and watched something on his phone. He used almost all the Google apps , such as Google Slides , Google Docs , and Google Sheets , for different purposes in his classes. He also reported usin g Canvas assignments. Interestingly, he found Canvas very complicated at the beginning. He also reported that it was neither easy to use the nor easy to learn how to use it.. But he did not make too much effort to learn how to use the that h e does not enjoy using the , he chose it as his favorite device in the interview because he likes

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101 Interviewee 3 : Al. Al. was a 13 year old male in the 7 th grade . He received a score of 36 out of 6 0 for general attitude toward in the survey. According to him, technology is them and that makes it faster than going all the way and talking to them He reported using his at school for 2 3 hours and at home for less than 1 hour , for doing homework, searching for information for schoolwork, and creating websites. His favorite technological device was his phone, because he could d o things on it without a Wi Fi connection. He indicated that he preferred using his phone and his for different purposes. while he is using his phone to do other things that are not related to school. There is no feature of he likes less than other features. When he was a 5 th grader, he came from a different school where students used paper and pencil for classwork. When he started to use , typing fast was the biggest challenge fo r him, but he got comfortable with fast typing through using the indicated that he put in a lot of effort to learn how to use the at both school and home. He was satisfied with the use of for creating slides for group projects. He reported in the survey that although he looks forward to using his , he did not feel that he was in control while using it. Interviewee 4 : H. H. was 12 year old male in the 6 th grade . He received a score of 40 out of 6 0 for general attitude toward in the survey. He reported his at school for 2 3 hours and at home for 1 2 hours , for doing homework, searching for information for schoolwork, surfing online for fun, and creating websites. He defined

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102 technological device was his Apple Watch , but he preferred using his , which he used mainly a t home, and sometimes found it difficult to use the because all the was not easy to use in the survey, in the interview he asserted that he did not make a lot of eff ort while learning how to use because he took a class that taught him how to use computers. Although he indicated that he does not enjoy using in general, he loved using it to create slides for projects, to search on the Internet, a nd to type fast. High A ttitude G roup These interviewees were selected from the students who had the highest scores for attitude toward . In this group, there were three female students and one male student. Interviewee 5: D. D. was a 13 year old male in the 6 th grade . He received the score of 60 out of 6 0 for the score of general attitude toward He reported using his for 2 3 hours at school and for 1 2 hours at home , for doing homework, taking notes in class, s e nding and receiving emails, searching for information for schoolwork, and w orking with specific software. rite technological device was his phone because it was . He found using

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103 for studying and creating presentations effective. He mentioned that where you can change the presentation to look Interviewee 6 : L. L. is a 12 year old student in the 6 th grade . She received a score of 60 out of 6 0 for general attitude toward in the survey . She reported using her at school for more than 3 hours and at home for 2 3 hours , for doing homework, taking notes in class, sending and receiving emails, searching for information for sc hoolwork, and working with specific software. She indicated that she , phone, and Alexa house. In her daily life, she used technology for communication and productivity, finding it very he just for classwork, because she had her handy and because the that she made a lot of effort to learn how to use a . Before P.K. Yonge, she went a public school at which the only time she used computers is in the library, effort to figur e out how to use [the for projects.

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104 Interviewee 7 : An. An. is a n 11 year old female in the 6 th grade . She received a score of 58 out of 6 0 for general attitude toward . She reported using her at school for 2 3 hours and at home for less than 1 hour , for doing homework, taking notes in class, sending and receiving emails, searching for information for school work, surfing online for fun, working with specific softw are, and playing computer games. She stated that she used technology every day, for entertainment, like watching videos on YouTube and Netflix , . She used almost all of the Google apps , but Google Slides was her spelling and voice to text features of the , she has had it for a longer time, and it is her first year with the . She indicated that she put in a lot of effort to learn how to use the Interviewee 8 : M. M. is 13 year old female in the 7 th grade . She received a score of 52 out of 6 0 for general attitude toward . She use d her at school for more than 3 hours a t home for 1 2 hours , for doing homework, taking notes in the class, sending and receiving emails, searching for information for school work, surfing online for fun, chatting online, working with specific software, playing computer games, creating websites , and participating in online discussions. phones, smart boards, and computers. The was her favorite device, and

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105 she said she used homework, she preferred her because it had a bigger screen. She used some Google apps like Google Docs and Google Slides , as well as YouTube and Canvas on the . Goog le Docs was her favorite application, while she that when she got her , she was new to the school and felt shy of working with the . She worked hard to learn how to use the , especially at the beginning, loved the spelling feature of Findings from Interviews Two main themes emerged from the interviews. The first theme is that were used for only academic purposes at school , while they were used for both academic and non academic purposes at home . The second theme is that s ed between the high and low attitude groups in terms of their affect toward and the perceived eas e of use and perceived usefulness of . There are three sub themes under the first and second main theme. Theme 1: we re Used f or o nly A cademic P urp oses a t S chool , W hile T hey we re U sed f or b oth Academic a nd Non Academic Purposes a t H ome Results showed that the use of differ ed from student to student. It was revealed that were used for different purposes at home and at school , or academic and non academic purposes. Doing homework, looking up infor mation, and using Google apps to complete schoolwork are examples of using

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106 for academic purposes , while texting, calling people, playing games, and watching non educational videos on YouTube are examples of using for non academic purposes. The findings for this theme were reported under two categories: use at home and use at school. There was little to no difference between how students with low attitude a nd those with high attitude t oward C Students were asked how and for what purposes they used their at school. I fell into two areas in terms of attitude and class/course. use at sc hool was similar between different attitude levels , with both groups using them for academic purposes at school. The only reason surfaced for why a might not be used for non academic purposes at school was that attitude). Due to the could only use for surfing educational websites and reviewing course related content. How students in both attitude groups use d in school included completing tasks and assignments using Google apps (Google D ocs , Google Sheet s , and Google Drive ), connecting to friends and teacher s with Canvas and Google C lassroom , and reading digital textbooks on their : We normally use Google slides, Google docs, Google Drive for projects or write stuff down in classes like civics. (D., m ale, high attitude) It helps me sometimes with homework. (J., female, low attitude) I use technology every day. Especially with my for schoolwork. [ For example ] if I need to do math homework and I do not know the exact page or what the question was, I can use my to find an e book. (An., female, high attitude)

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107 Stu dents also take tests, create presentations, take notes, and do research with their : You can do various stuff on a device like homework or you can look up stuff when you need help. (S., male, low attitude) If I am stuck on questions, I will u se my and it will help me to get better understanding of it in a certain way. (J., female, low attitude) We can also use just use Google the search engine to find answers to questions or to research things. (D., male, low attitude) In summar y, students in both attitude groups used their in school only for academic purposes such as taking notes, taking tests, doing research, and looking up information for better learning. No student indicated no use at school. use differ ed according to type of classes How were used in school and for how long varied between different classes/courses. The interviewees shared that they mostly use d their in their civics, performing arts, and sc ience classes. In civics class, students used their for discussions (J., female, low attitude), to share documents with teachers (S., m ale, high attitude), to do projects (A., f emale, high attitude), and to take notes (D., m ale, high attitude) . S. (male, low attitude) elaborated on the use of in civics class , explaining that students often used their in civics class to take notes and write down vocabulary words; for example, for one activity in this class, the teacher posed some questions, which each student answered in a Google Doc that they then shared with the teacher.

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108 Students also reported using in their science classes to take quizzes and tests, to do group projects (A l ., Male, low attitude) and research, and to find help with difficult content (J . , f emale, low attitude). Finally, students talked about using their in their performing arts classes to do individual and group projects (L., female, high attitude) and to wr ite monologues, plays (A n ., f emale, high attitude), and scripts (J., f emale, low attitude), . were typically not used in mathematics classes , according to five of the interviewees. are clearly used differently for different types of classes when they are used at all. In summary, all the students interviewed indicated that they are using their frequently at school , and only for academic purposes . T he use of by the students with high attitude and the stude nts with low attitude did no t differ drastically at school. Finally, although both low and high attitude students used their for the same purposes, those purposes changed from class to class. There w as little to no difference between how stu dents with low attitude and high attitude t oward t home Students were asked about their use of at home to understand how they use the tools outside of school. The use of at home is equated with the extended use of by students. Based on the excerpts, produced mixed findings across attitude groups .

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109 D. (high attitude) and J. (low attitude) were the participants mos t used their for both non academic and academic purposes at home : I use it to study. If I have homework that needs to be done, I will just get it on there. Sometimes when I am bored I play games on it. (D., male, high attitude) If I am given an overload of homework or projects that I have to finish on the weekends on , it will help me. [ ] Some websites are restricted [ at school ] . When I am at my house, I go on an older website that was restricted [ at school ] . [ ] It is not just f or homework; it is to watch videos on YouTube. (J., female, low attitude) L. (female, high attitude) mentioned using her for personal use a small amount at home; mostly, she uses it for homework . While D. and L. ha d the highest score s in their response to CAMYS (60 out of 60) , J. ha d the lowest score out of all 220 students who took the survey (17 out of 60) . O f all survey respondents, o nly H. (male , low attitude ) said that he never use d his at home. No student from the high attitude group never uses a at home. Two students from the low attitude group and two students from the high attitude group stated that they are using their devices just for studying or doing homework at home. In short, both students with high attitude and low attitude toward are using their devices outside of school . The number of students who never use at home is only one. The group of students reporting use at home for b oth academic and non academic purposes includes two students with

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110 the highest attitude and one student with the lowest attitude. This can be interpreted as the use of by students with different attitudes does not differ drastically. T heme 2. Attitudes Differed across High and Low Attitude Groups in terms o f t heir A ffect toward Ease of Use and Usefulness Students described why they felt good with their , how much effort they inve sted in learning how to use a , the challenges they experienced, and the advantages of using . High and low attitude group students differ ed in terms of th eir affect toward In the interviews students were asked about t heir favorite devices first. If they chose a technological device different than the , they were further asked to compare their feelings about and their favorite device. The summary can be found in Table 4.10 . O nly M. (female) in the high attitude group indicated that the was her favorite device . But she also mentioned that she could do same things with her phone, too ; s he prefer red her only because of its big screen. The other three students (D., L, and An.) with high attitude indicated that their phone s were their favorite device because of their portability and ease of use. They also found their phones easier to communicate with and l iked that their phones had everything on them , like photos . When the three students who chose their phones as favorite device were asked to compare their phone s to their with regard to how they feel about them, they all responded that they pre fer their phones . D. (male)

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111 and L. (female) indicated that their phone s were more personalized than . comfort on there [ phone ] . With the , everyone can see to be alone, my phone is personalized . have blocks and stuff. I can do whatever on my phone. Not that I do anything bad. I can just An. (female) felt better with her phone because she ha d owned her phone for longer than she had owned the . Table 4 10 . Summary of In tervi ewee Favorite Device Why? Feel Better With Why? D. Phone Easier to use More portable Phone While using a , everyone is looking at the screen (no privacy) Phone is more personalized L. Phone Better communication with it More portable Phone has blocks. She can use the phone more personally. An. Phone Everything is in the phone such as pictures, videos, etc. Phone She has it for a longer period of time but it is her first year with her M. has bigger screen. J. is more updated H. Apple watch He can track heartbeat and time with it. He can do more w a like searching on Internet. Al. Phone It works without Wi Fi. Both is good for schoolwork and getting good grades. Phone is good for other personal stuff. S. It is very helpful. He can type faster with it. Auto correct feature is good. I n the low attitude group, two interviewees selected their as their favorite devices. J. (female) liked that it was always updated, while S. (male) found the

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112 helpful because he could type fast on it. He also like d its auto correction feature. Although the other two students in the low attitude group selected different devices (their phone and Apple W atch ), they stated that they felt better with their H. (male) because he could do more things, like searching on the Internet , and Al. (male) because it helped him to do homework and get good grades. Interestingly, the low attitude group reported feeling better with their more than the high attitude group. The students in the low attitude group chose their as their favorite devices or , even if their favorite device was something else, they felt better with their Chromeboo . High and low attitude group students differ ed in how eas y they perceive are to use To better , the survey asked about their effort s to learn how to use their . They w ere also asked about the challenges and advantages they experienced while using their . All students in the high attitude group noted that they invested a great deal of effort in learning how to use their , especially when they fi rst got the devices . L. (female) indicated that because she had not used computers in school before, she worked hard to learn how to use her : [Yonge] I went to a public school , and the only time we would use computers is in the library. If we had to do classwork, there would only be like three computers. So I would not go on the computers a lot . high attitude) She shared that using her got easier with help from her friends, and said that s he now found the easy to use because she had figured it

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113 out. A. (female) also indicated that she had put in a lot of effort while learning how to use her because she had to find out where everything was on the device; h owever, she was motivated because she felt that it would be a great help for her schoolwork. She also thought that she could enjoy playing games on her when she had free time. When the students in the low attitude group were asked about their effort s , only two indicated that they invested a lot of effort , especially at the beginning , but that using the got easier through time (J., female) and frequent use (Al., male). The other two student s expressed that they did not make too much effort to learn how to use their . Using his every day helped S. (male) to learn how to use it more quickly he had taken a class about co mputers. Students indicated some challenges when they used their , both related to the device itself and its applications. While the device related challenges were generally more technical in nature, like how to use the keyboard and the quick restart or how to charge the device, the application related challenges were more about figuring . Some students were disappointed that when a shut down, it refreshe d everything , causing students to lose track of their work. They then would have to find and open all the files they were working on again (L., female, high attitude). J. (female, low attitude) said that search feature of the did not work properly , so it wa s sometimes difficult for her to find what she was looking for. The same interviewee indicated that learning the functions of each button on a was

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114 challenging. A. (male, low attitude) was not happy with how long it took to charge the Chromebook , and said it was often necessary to charge the device at home so that it would have enough battery to last out the school day . He added that the became slower when the battery was low or the Wi Fi connection was bad. According to A. (female, high attitude), taking pictures and recording videos with a are not easy or satisfying because of the low quality. Another challenge of use for her was having to be careful not to drop and break it . In addition to challenges related to the itself , some of the low attitude students also enumerated some challenges related to its applications. For example, for S. (male, low attitude), creating folders in Google D rive was difficult and using Canvas was co mplicated . M. (female, low attitude) also found Canvas a challenge to use , their teachers through Canva s . Finally, S. (male, low attitude) indicated that he found Google Sheets which he does not need very oft en, pretty complicated. In summary, although the high attitude group expressed expending a lot of effort to learn how to use , the low attitude attitude group did not try as hard . Some students from both groups experience d some technical challenges in learning how to use the device, and some of the low attitude students also found some of the applications they were required to use for schoolwork challenging. Overall, t hree students from each group indicated that the more common challenges they experienced were technical and related to using the device itself rather than its applications .

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115 Both the high and low attitude group s found useful , es pecially for academic purposes Perceived usefulness is related to a user perceptions about whether a device enhances their performance. In this study the interviewees were asked about the ways they use d their the most effectively and the things that help ed them to do more easily or in less time. When the high attitude group was asked for the most effective ways they used their , all responses were related to schoolwork. They found their the most effective for making presentations (D., male), using e books (An., female), and kee ping up with homework (M., female). L. (female) responded to the same question with . was easy and fast typing. All of these students found their effective in some way related to their schoolwork. Secondly, students in the high attitude group indicated that their increased their performance with its correction of spelling and voice to text feature (An., female). M. (female) was also satisfied with the spe lling correction feature because it made her stories sound better. The Google or YouTube helped L. ( female) to do her classwork more efficiently. D. (male) also mentioned that typing very fast with Chrome helped him to do schoolwork in less time or more easily. H e was also very pleased that he could create good looking presentations for his projects. The students in the low attitude group also found their useful , especially for fast typing (J., female & S., male). Three of the four students in this group found typing with a more effective than writing on paper.

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116 Another academic advantage students mentioned was digital te xtbooks. According to A. (female, high attitude), digital textbooks were one of the most effective ways of using . J. (female, low attitude) was also very happy with digital textbooks : Digital textbooks help a lot because if you are not at sc textbook there. If you are at somewhere else which does not have a textbook, you should go to your and you can see what lessons you are doing. (J., female, low attitude) In addition, students asserted that they like d t he shortcuts on their . H. (male, low attitude) love d the shortcuts for opening a new tab, copying, and pasting the most. D. (male, low attitude) also expressed his satisfaction with the shortcut menu , which help ed him to get better at . J. (female, low attitude) was very happy with the ease of changing the background color of the screen. were useful for searching o effective for the use of Google , which required only one click to open a tab. Similarly, Al. (male) was satisfied with his ability to watch videos on YouTube for school and in his free time on his Chro One of the features of cloud based system. Interview data also showed that students used Chromeboks computing through different Google applications for different academic purposes. S tudents with low attitudes were satisfied with their for the creation of slides in Google S lides (H., male & S., male) , asserting that Google Slides was the best tool for creating presentations for their school projects. Students from both g roups found

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117 Google Slides very creative (A., female, high attitude) and satisfying (S., male, low attitude) for presentations. It also made presentations look better (D., male, high attitude). A. (male, low attitude) indicated that Google S lides was very satisfying for group projects. Similar ly , students were mostly satisfied with Google D ocs , finding it especially effective for spelling and other text auto corrections. I like to write things on my because it will help me if I spell a word wrong. (J., female, low attitude) We have a lot of readings and we write summaries, different fiction stories or nonfiction daily biographies. I feel like Google helped me with my spelling . (A., female, high att itude) Google Sheets was also used by students for projects in some classes. While A. (female, high attitude) used Google Sheets in one of her elective courses, S. (male, low attitude) used it in science class to create charts. Regarding Google Drive , L. (female, high attitude) mentioned the tool made it easy to reopen the files she had used a while back . S. (male) also indicated that submitting assignments on his was very easy. Moreover, the highlighting (J., female, low attitude) and voi ce to text (A., female, high attitude) functions that are provided by Google Read & Write on were found satisfying by students. Students in the low attitude group found their useful for studying. For example, J. (female) said that highlighting and the use of digital textbooks were the most effective and satisfying ways of using a . She also gave some specific examples for the effective use of in differen t subjects : for writing or taking notes in civics and for problem solving or researching in math and science

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118 classes. She found it easier to complete her homework on time because of reminders Canvas sent her . S. (male, low attitude) was happy with Canvas because of how easy it was to check grades and classes. Students also like d Google Classroom . Through it, they could see class assignments easily submit completed assignment s effor tlessly (S., male, low attitude). With Canvas or Google Classroom , studen ts keep up with their homework easily In summary, although the ways of and the purposes for using differ ed across the attitude groups, the students all found their useful , especially for schoolwork. Most interviewees appreciated typing fast on and many were satisfied with creating slides for school projects on their . Stud ents found many advantages in the technical features , like keyboard, screen size, and shortcuts , and several mentioned the advantages of using applications and the learning management system. S tudents in the low attitude group were more likel y than those in the high attitude group to mention advantages related to both the technical features of and the applications used on it. Summary Two themes were extr acted from the qualitative data, including semi structured interviews: Chrome were used for only academic purposes at school , and for both academic and non academic purposes at home. ed across high and low attitude groups in terms of their affect toward and the perceived ease of us eand perceived usefulness of .

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119 The categories used to create themes and some sample quotes can be seen in Table 4 11. Table 4 11 . Themes and categories from the qualitative data Themes Categories Sample Quotes are used for only academic purposes at school, while they are used for both academic and non academic purposes at home. Chromeboo use at home projects that I have to finish at weekends, my will help me. Some websites are restricted at school, but sometimes when I am at home, I go on an older website that was restricted. It (J., female, low attitude) I use it ( ) to study. If I have homework that needs to be done, I will just get it on there. Sometimes, when I am bored playing games on it. (D., male, high attitude) Chromeboo use at school exam. Usually, our tests are on our . notes. We also use it for thinking questions. He writes question down and you write your answer down. It is really easy because our teacher can see it because attitude) like music instruments all around the world. I could connect with my friends that I hav e to do the project with and we could all work on the same one female, high attitude). Use of Chromeboo across classes down notes. We also use it for thinking questions. He writes the questions down and you write it down. It is really easy because teacher can see it because we attitude) For ELA, we have a lot of reading books that we have to write summ aries on or we do different fiction stories or nonfiction daily biographies. I feel Google attitude).

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120 Table 4 11. Continued Themes Categories Sample Quotes Attitudes of the students in high and low attitude group are different in terms of their affect toward perceived ease of use and perceived usefulness of Affect male, low a ttitude). phone because I can talk to my friends, I have my calendar on my phone. It is also really Perceived ease of use was) probably a lot because before I went to P.K. I went to a public school. The only time we would attitude) challenging thing was Google Drive like I didn't kn ow a lot about it I didn't I barely knew anything about it and creating folders. That was really hard and then canvas, too. male, low attitude) Perceived usefulness taking longer attitude) you have a missing assignment, you just go and look instead of having to ask every teacher. So I can get it done quicker and faster on my

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121 CHAPTER 5 DISCUSSION toward and their use of using the Technology Acceptance Model (TAM) as a framework. Two research questions guided this study: 1) ? and 2) What are ? An explanat ory sequential mixed method study design was used to answer the research questions through a quantitative survey and follow up qualitative interviews. The purpose of the quantitative phase which came first, was to obtain a general picture of 182 6 th and 7 th , using the Computer Attitude Measure for Young Students (CAMYS) by Teo and Noyes (2008). In the qualitative phase, 8 students who were selected according to their scores on CAMYS were interviewed to elicit their feelings about and deeper descriptions of their use of . Research Question #1: What a re M iddle S chool S A ttitudes t oward ? This study used the Technology Acceptance Model (TAM) as a framework and, accordingly, attitudes toward reaction and degree of favorableness, pleasure, and like toward their ( Ajzen, 1988; Ajze n & Fishbein, 1977; 1980; Davis, 1985; 1993; Kay, 1993 ). More specifically, TAM considers three dimensions of attitude, which were also measured in this study: perceived ease of use (PEU), perceived usefulness (PU), and affect toward computers. Both the mean score of the CAMYS survey results (52.07 out of 60) and follow up interviews suggested students had positive attitudes about their in

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122 these three dimensions. In fact, even the interviewed students with relatively lower CAMYS scores report ed having positive attitudes toward their . One potential explanation of the overall positive attitudes in the sample may be related to . Many researchers (Harvey & Wilson, 1985; Houle, 1996; Levin & Gordon, 1 989; Ogletree & Williams,1990; Shashaani, 1997; Teo, 2008) have asserted that computer ownership has a positive relationship with computer attitudes. For example, in an empirical study on secondary students conducted by nd high attitude toward computers were positively correlated. Specifically, in the school in this study, students receive when they enter middle school in 6 th grade and keep them until they graduate in 12 th grade. They are allowed to use their both in and outside of school. It is possible to infer that as they use , students develop feelings of ownership, which then translate into high attitude toward . In addition to ownership, early access to may also be one of the explanations for positive attitudes for some of the students in the sample. Previous studies regarding computer attitude also support this interpretation. For example, Moore (1994) reported that if students are engaged in using comp uters early, they are likely to possess more positive attitudes toward them. The school from which the data were collected encourages students to use technology from Pre K to 12 th grade . If a student attends the school starting in kindergarten, it is highly possible that s/he will be exposed to a variety of technologies during his/her school time. Many students in the sample all attended the school for at least some of the elementary gra des ; however some attended different schools during those

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123 early exposure to technology might not be a completely valid explanation for their positive attitudes toward . It has been documen ted in the literature that computer attitudes are correlated with age, gender, and computer experiences (Loy & Gressard, 1984; Moon, 1994, Shashaani, 1994; Volman & Eck, 2001). Meelissen and Drent (2008) argued that the variance in computer attitude is bet ter explained by non school related factors like gender, age, and time spent with computers. Therefore, the results for computer attitudes found by this study were also analyzed in terms of the non school related factors of age, gender, and computer experi ence. There were No Statistically Significant Differences between Different Aged The results of the current study may seem to suggest there were no differences among students of different ages in terms of their atti tudes toward . Yet this result might be attributable to the fact that the age range of the included students was narrow, from 11 to 13 years old. Therefore, attitudes toward among 6 th a n d 7 th graders could be interpreted as fairly uniform , as represented by this sample . age range of 3 years (Adebowale, Adediwura, & Bada, 2009) and 4 years (Colley & Comber, 2010) has been found to uncover the most signifi cant differences. In the study conducted by Adebowale et al. (2009), two student groups were compared: pre adolescents (10 12 years old) and early adolescents (13 15 years old); in another study, Colley and Comber (2010) compared 11 to 12 yearold students and 15 to 16 year old

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124 attitudes toward computers by age have used more age variability such as a 6 year age range (from 11 to 17 years old) (Kay, 2012) or a 12 year ag e range (10 22 years old) (Kay & Knaack, 2008), as well as grade level ranges, 7 th graders and 11 th graders (King, Bond, & Blandford, 2002). toward computers in terms of age is inconclusive, even when there is more variability in diffe rence between 11 and 12 year old students who reported less positive attitudes toward computers compared to the attitudes of 15 and 16 year old students. Kay and Knaack (2008) reported similar results, with older students having higher attitudes toward c omputers in K 12 settings. Differences in ages in terms of attitude were observed in previous stud ies . Mostly, older students reported more positive attitudes toward computers (including liking computers and PEU of computers) than younger students in other studies of K 12 levels ( Durndell, Glissov, & Siann, 2006; Jennings & Onwuegbuzie, 2001). On the other hand, some studies have contradicted the results of the studies reported above, with no difference in computer attitudes between age groups found. For ex ample, the difference in computer attitudes between students in the 7 th and 11 th (2009) six group comparisons among pre adolescents (10 12 years old), early adole scents (13 15 years old), mid adolescents (16 18 years old), and late adolescents (19 years old and above), there was only one statistically significant difference reported,

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125 which was between pre adolescents (10 12 years old) and late adolescents (19 year s old and above): The late adolescents had higher computer attitude. A number of studies have investigated the differences in computer attitude among various age groups over the last three decades. While meaningful results in computer attitudes have been reported, regardless of the variation among age groups, it seems that there is no agreement as to whether age directly correlates to computer attitudes. There were No Statistically Significant Differences between Female and Male Students in terms of their The result of the current study indicated no difference between female and male students in terms of their attitudes toward the . Despite extensive literature looking at computer related attitudes in K 12 students,, after almost four decades, there is still no consensus on whether attitudes toward computers differ by gender. Mostly, statistically significant differences in computer attitudes favor males in K 12 settings , however considerable variability exists. Some studies suggest males have more positive or less negative attitudes toward computers than females (Colley & Comber, 2003; Comber et al . , 2006 ; Sáinz & López Sáez, 2010) . For example, Colley and Comber ( 2003 ) reported that 11 and 12 year old boys liked computers more than girls. On the other hand, Kubiatko, Haláková, Nagyová , and Nagy (2011) found that girls have more positive attitudes toward computers than boy s. In terms of the computer attitudes of middle school students, there are mixed results . Some studies have indicated that males of this age like computers more than females (Bayhan, Sipal, & Karaaslan, 2009). Volman, van Eck, Heemskerk , and Kuiper

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126 (2005) argued that while gender differences at the elementary level are negligible , at the seco ndary level they are considerable, with boys hav ing more positive attitudes than girls. However, many studies have shown that there is no difference in computer attitudes between genders (Bovee, Voogt, & Meelissen, 2007; North & Noyes, 2002). I n a recent l iterature review study, Cussó Calabuig, Fa rran, and Bosch Capblanch (2018) reported no differences across genders in computer enjoyment (computer interest not only within the academic context of schools , but also during leisure time ) at the secondary level . There are also numerous empirical studies from the last four decades showing that gender has no effect on computer attitudes (Busch, 1995; & Prokop , 2008 ; Kaino, 2008; Jones & Wall, 1990; Loyd & Gressard, 1984). Overall, the role of gender on computer attitudes is unclear. It is difficult to offer explanations as to why there is no patterned effect of gender on computer att itudes, but one reason might be that new generations of students have easy and early access to ubiquitous computing almost anywhere and anytime, essentially growing up digital ( Montgomery, 2009; Palfrey & Gasser, 2008; Tapscott, 2008). nder related attitudes because of the omnipresence of computers (Kay, 2010). In this study, it is possible that some contextual features play ed a role in , for example, systematic use of Chromeboo in the school. The students, who were responsible for bringing their to school every day, used the devices to access class documents, calendars, messages, and announcements in addition to completing schoolwork with them. Through Google app s , Google Classroom , and Canvas (the learning management system used in

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127 the study context), students communicated with other students and teachers and created, edited, and shared documents for assignments and projects. Experience/Time S pent U sing in and outside of S chool did not Have a Statistically Significant E As students spend time with their computers, they gain more experience using them, in turn, presumably, developing positive attitudes toward them (Schumacher & Morahan Martin, 2001). In this study, almost 7 0% of the students used their more than 3 hours a week in school, and almost 75% of the students use d their less than 2 hours a week outside of school. Overall, the time students spent on their varie d from moderate to high use. However, neither time spent with in school (which was relatively high) nor time spent with at home (which was relatively low) had a statistically significant effect on their attitudes toward Chromebooks . In fact, there is very limited evidence in the literature related to the relationship between computer experience and computer attitudes that corroborates the result of this research study. In one empirical study, for example, Pope Davis and Twing (1991) found no meaningful relationship between computer experience and attitudes toward computers. However, the sample in their study comprised college students, who might have used computers for different purposes both inside and outside of school than t he middle school students of the current study. On the other hand, numerous studies in the past three decades have reported a direct ratio between amount of computer experience and computer attitudes ( Bové e, Voogt, & Meelissen , 2005; Garland & Noyes, 200 4; Meelissen & Drent, 2008; Levine & Donita Schmidt, 1998; Loyd, Loyd, & Gressard, 1987; Schumacher & Morahan Martin,

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128 2001). For example, Levine and Donita Schmidt (1998) used general computer use as a proxy for computer experience. The researchers found t hat for 7 th to 12 th grade students, computer experience in school and at home was positively associated with computer attitudes. In a study by Bové e et al. (2005) comparing students from upper and middle class schools who were exposed to computers regularly with students from lower income, rural schools who were exposed to computers once a month, the former group reported more positive attitudes toward computers . Loyd et al. (1987) examined the relationship betw attitudes, with the premise that that this is an important population to study, because at that age students are developing an abstract reasoning ability for computers. By using the Computer Atti tude Scale, the researchers found that middle school students with more computer experience had more positive computer attitudes. One reason that might explain the discrepancy between the result of this study and prior studies mentioned above is the anxie ty students feel in using computers. Students might develop anxiety as they are exposed to computers more and with repeated frequency (Noyes & Garland, 2004; Rosen & Weil, 1995). From this perpective, as students in this study spend more time with Chromebo in the future, they might get anxious as they associate the devices with schoolwork and stress, instead of liking or positively connecting to them. That may be why a statistically significant difference in computer attitude in terms of time spent/expe rience of students storne, 1999).

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129 Students have negative subjective computer experiences if they are anxious about using computers even though there is an increase in their experience measured by objective tools. Having positive attitudes and meaningful computer experience m ight not account for students who might be anxious and not self sufficient about using computers (Noyes & Garland, 2004). in terms of use at school and outside of school might be related to how use was measured . Across the literature, experience/time spent with computers i s usually measured with weeks, months, or frequenc y (once a week). For example, to report their computer experience in terms of frequency, such as occasionally or often ( Bové e et al., 2005), and on scales of weeks or months (i.e., Loyd et al.,1987; Meelissen & Drent, 2008 ). For example, study participants may have had the option to report that they use d computers occasionally every week. However, this study asked students to report computer use , both inside and outside of the school , in terms of hours per week . There is a chance that these middle school students had a difficult time accurately estimating the number of hours they used their . Research Question #2: What U sing ? The findings of this study re vealed that the use of by students with low and high attitude s did not significantly differ betwee n school and home . Regardless of attitude levels, there were t hree notable findings. For one, s tudents use d at school for academic purposes only , but use d them at home for both academic and non academic purposes. Additionally, all students reported that they

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130 use d their differently in different classes. Finally, the results of the survey and intervi ews did not align, with the students who scored lower on the CAMYS still exhibiting positive attitudes toward during the interviews . These findings will be discussed with in the TAM framework in the subsequent sections. Students with Differing Attitudes toward Report Using them in Similar Ways in School All students, regardless of their attitudes toward , stated that they used them at school in similar ways. The data from the Current Technology Use survey also demonstra ted that students used their for learning purposes. According to the survey, the tasks most completed were searching for information for schoolwork, doing homework, and taking notes in class, respectively, which are consistent with the themes that emerged from the interviews, in which students asserted that they used their mainly for academic purposes such as taking notes, taking tests, and searching for information. The primary reason the students in this study used in school was that their school required it: The students were given and expected to use them in school. Teachers had students complete their assignments on their in class, created class activities in which all students had to use their . This type of technology use can be regarded as mandated. In the literature, the distinction between mandatory and voluntary use has been documented: In mandatory settings, users use technology because they have to; however, in voluntary settings, users make choices to use or adopt a technology (Agarwal & Prasad, 1997; Venkatesh & Davis, 2000). Previous research has not found a correlation between attitudes toward technology and intention to use in mandatory settings (Brown

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131 et al., 2002). At least one study has shown that even when a user has negative attitudes toward a technology, s/he may use it because it is a requirement (Hwang, Chung, Shin , & Lee, 2017). The discrepancy between attitude and use in mandatory environments is important, especially for the context of this study. In learning activities in which teachers make their students use their in school, students must follow standard sets of steps or instru ctions to complete class assignments. Therefore, the mandatory use of in class activities might be a reason why no differences in use were reported across attitude levels. Another reason why uses of in school in this study did n ot vary between students with differing attitudes toward the devise may be illuminated using Theory of Reasoned Action (TRA). Fishbein and Ajzen (1975) averred that attitude and subjective norm are the determinants of technology use, with attitude encompas sing beliefs about outcomes of a system use and subjective norm comprising perceptions of social pressure to use or not to use a system. Hartwick and Barki (1994) found that in mandatory settings, subjective norm is a more important predictor of system use than attitude. They reported that the frequent use of a technology by mandatory users is due to the belief that important others expect them to use it. In this study, the students may have used their frequently in school because their teacher s, who are important others for the students, expected them to do so. Therefore, their uses of in school did not differ drastically, although they reported different attitudes toward them.

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132 S b etween Classes The results of this study showed that the use of by students differed by class. For example, in science class, students reported that they used their for a variety of purposes like taking tests, doing research, p utting together group projects, and looking up information on the Internet. For example, during the interviews, one student indicated that she often visited a website that helped her understand some science concepts better. These findings are consistent wi th the findings of previous studies. Shapley, Sheehan, Maloney, and Caranikas Walker (2010) found that laptops are used in classes for conducting Internet research, creation of presentations, and completion of tests and quizzes. By using their individual c omputers, students can visit websites that their teachers suggest to learn new concepts, work on projects, and complete school related activities (Lei & Zhao, 2008). On the other hand, in courses like civics, students used their to take notes , answer questions provided by their teachers, and share documents with their teachers. In their English language arts (ELA) classes, students use their for writing fiction stories, essays, and non fiction stories. In interviews, students ment ioned the ease of typing on their . This evidence is corroborated by previous research examining laptops. For example, 1:1 laptops have been used to assist students in writing (Suhr, Hernandez, Warschauer, & Grimes, 2010); these researchers sug gested that, in fact, the primary use of 1:1 laptops was for writing and editing. There are also studies showing that students write more in class when they have their own computers (Bebell & Kay, 2009; Russel, Bebell, & Higgins, 2004). This could be due s easier to write with a keyboard than by hand (Grimes & Warschauer, 2008).

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133 Moreover, the literature shows that in 1:1 classrooms, students are given more feedback on their writing, and that the y both edit their papers more and use more resources to write (Bebell & Kay, 2009; Grimes & Warschauer, 2008; Lei & Zhao, 2008). In addition, Grimes and Warschauer (2008) reported that by using laptops student could write in various formats and genres like brochures, newspaper text, and formal letters. Similarly, students in this study reported that they frequently used their in ELA classes to write fiction stories, non fiction daily biographies, and essays, as well as in performing arts classe s to write monologues, scripts, and plays. The use of in social studies classes was also described by the students in the interviews. Students reported taking notes , creating projects , participating in discussions , and shar ing documents with their teacher on their . This finding aligns with previous studies showing that laptop use is common in social studies classes, e.g., a mixed method study by Lowther, Inan, Ross, and Strahl (2012) that found that 52.5% of 5,770 6 th grade students used their laptops in their social studies classes. While students reported that using their in a variety of ways, depending on the class , they also indicated that they d id not use in math classes that much , instead relying on pen and paper . This finding is echoed in , which found only 34.1% of students used laptops in their math classes. One explanation for why use differs between classes might be erences and requirements vary. A possible factor worth mentioning is

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134 and perceptions of (Rogers, 2000). As evidenced in the literature, (Christensen, 2002; Rogers, 2000; Sahin et al., 2016; Teo et al., 2008). To get benefits from teaching with technology, sufficie nt desire to use technology is needed (Teo et al., 2008). Going beyond that, teachers also need essential skills and knowledge to incorporate into their classroom s attitudes and beliefs (Hew & Brush, 2007). Lac king fundamentals in technology integration might be one reason why some their students to use . Another explanation for varying levels of use between classes might be related to subject culture. The effect of subject culture on the adoption or use of technology by teachers has been highlighted in the literature (Hew & Brush, 2007; Inan & Lowther, 2010). Each subject area has its own norms for and expectations about learning , and this has an effect on teacher us e of technology (Howard, Chan, Mozejko, & Caputi, 2015). When a technology is not compatible with their subjects, teachers are not willing to use it in their classes (Hennessy, Ruthven, & Brindley, 2005). For example, graphing software can be an effective technology tool in math classes , and animations and simulations can be useful for science classes (Howard, Chan, & Caputi, 2015) , but these tools might not be appropriate for other subject areas. S tudents Reported Using for Different Purposes at Home The findings from the interviews and the results from the Current Technology Use Survey showed that students in both high and low attitude groups use d in similar ways in school. However, they use d for different purposes at home , regardless of attitude level.

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135 T he students interviewed reported engaging with a set of similar academic tasks or activities on their at home. Some st udents used only for academic purposes at home, like doing homework (using word processing software or application) or studying for tests, which can be regarded as continued practice and enrichment to the schoolwork. Other students used their C at home for both academic and non academic purposes. These findings are consistent with those of other studies. For example, Kafai (1999) described three categories of home use of computers: 1) the use of software for academic purposes independ ent from school activities, 2) the use as a continued practice or enrichment to work in school, and 3) the use that facilitates the communication between teachers and students. As far as non academic use of is concerned, in the interviews, some students reported using their for playing games or watching videos, activities independent from school activities. The use of for non academic purposes was also visible in the data collected by the Current Technology Use Survey: 61.1% of the students uses for playing games. Previous studies have found similar trends regarding non academic uses of computers at home. For example, Downes (1996; 1999) reported that playing games was the most common activity for computer use at home by children, and Mumtaz (2001) found that playing games was not only the most popular activity that all the children enjoyed , it was also seen to be the primary function of a home computer by most of the participants. Lea cock (2004) reported that students who play ed games with their computers at home were more confident using their computer.

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136 T he Results of the Survey and the Findings of the Interviews did not Align for the Three TAM Indicators Attitude in the T echnology A cceptance F ramework has three indicators/dimensions: affect, perceived ease of use (PEU), and perceived usefulness (PU) . Davis (1989) define d (p.320). In the same study, he also define d computer or technology in general (Kay, 19 93). T he survey used in the first phase of this study included s . In the interviews, students also talked about their affect and the perceived ease of use and perceived usefulness of their . The results regarding these variables will be discussed in this section. Considering affect toward , i n the interviews, when students were asked about their favorite devices, most of the students with high attitude chose their phones. When the y we re asked to compare their phones and in terms of positive feelings, they also indicated that they fe lt better with their phones. Interestingly, l ow attitude students mostly chose their as their favorite device s, including J., who received the lowest score for the general attitude toward in the survey . When the students who did not choose were asked to make a comparison between their feelings about their favorite device and their , they state d that they felt better with their . It was also revealed in the interviews that low attitude students found useful.,.

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137 In the low attitude group, one student did not choose as his favorite, but even he stated that he felt better with his . In a similar way, when students were asked about their perceived ease of use of , two of the low attitude group students indicated that they did not struggle too muc h t o learn how to use a . The other students in that group asserted that they worked hard to learn how to use their but that using it frequently helped them pick it up quickly. All the students with high attitude stated that they p ut a lot of effort into learning how to use their even the two students with the highest scores on the survey. The qualitative results showed that low and high attitude students did not differ in terms of the perceived usefulness of their Chro students in both groups found useful for academic purposes such as creation of slides, spelling, and fast typing. In short, the students who had low scores in the attitude survey did not indicate that they had negative feelings towa rd , and in fact, their views of the perceived ease of use and perceived usefulness of were positive. This means that the results of surveys and interviews did not align in the current study. S urvey and Interview Results did not al ways Align Mixed method studies integrat e qualitative and quantitative data to strengthen results, because w he n results from both sets of data are interpreted together the research problem is bet ter understood (Creswell, 2015) and the inferences are of h igher quality (Tashakkori & Teddlie, 2003). In the current study, an explanatory sequential design was used , in which the interview data collected in the qualitative phase provided for a more in depth exploration of the numeric data collected in the quanti tative phase

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138 ( Ivankova, et al. , 2006). As Creswell et al. (2003) indicated , quantitative data provide a general picture of the research problem , while qualitative data are used to explain the s and thought s in a more elaborative way. In this study, the results of the survey provided a general representation of , determined as high. Also, no differences in general attitudes of students were found in terms of age, gender, or time using . in and outside of school was similar for students with low and hi gh attitudes. More interestingly, in the interviews, students with low attitudes reported high affect, perceived usefulness, and perceived ease of use. In this case, a mixed method design rd , and the results were unexpected because the different forms of data did not align. There are several possible explanations for this. The first explanation may relate to challenges when interviewing children. Interviews with young childre n aim to elicit their perspectives so that adults do not have to make interpretations of their perspectives on their behalf (Eder & Fingerson, 2001). Interviewing provides important data that cannot be obtained by any other method (Korteluoma, Hentinen, & Nikkonen, 2003). Yet interviewing adolescents requires special care. First, a natural context should be created for interviews. Eder and Fingerson (2001) argued that, rather than collecting only interview data from young participants, observations may help to provide natural contexts for the interviews. In this may have helped triangulate

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139 data from the survey and interviews. Second, especially when interviewing children, the power imbalance that is perc eived by the interviewee may be an obstacle to obtaining accurate results the current study, after being selected by the researcher, students were told by their teachers to participate in interviews about their use. This may have caused a power imbalance problem in the study. To reduce this type of imbalance, interviewing students as a group may h elp (Brooker, 2001; Carr, 2000). In this study, all with conveying their use. Finally, especially for the interviews in schools, answers and that they need to provide those answers in the interviews rather than their own perspectives (Hatch, 1999). There is one more consideration regarding the interviews. In this study, th e interview protocol was developed before the administration of the survey , which is not always ideal. In explanatory sequential design, there are two points for connecting the quantitative and qualitative phase s : selecting participants for the qualitative phase based on the survey results , and developing qualitative data collection protocols based on the survey results (Ivankova, Creswell & Stick, 2006). In this study, the first connecting point was achieved by selecting participants for interviews from su rvey results. For the second point of connecting two phases, there are some considerations. For this study, an interview protocol was developed before the survey was administered

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140 because of time constraints. After implementation of the survey , the interv iew protocol was revised. Since the interviews were semi structured, there was only one interview protocol, including some predetermined questions. All the participants selected were interviewed according to that interview protocol. However, using intervie w protocols that included more specific questions for each participant may have been helpful for better survey answers and tailoring individualized questions to elicit their attitudes and use. A second possibility for the disconnect between the survey and the interview results may relate to the stages of technology diffusion. In the early stages of introduction of a technology, an acceptance decision is made by users. Decisions made for long term usage and those for initial acceptance are different (Morris & Venkatesh, 2000). Technology acceptance does not occur immediately and as a result of one beliefs and attitudes that have an effect on acceptance decisions are formed as users spend time with the technology (Straub, decision whether to integrate an innovation in to his or her life; diffusion describes a collective adoption process over time. terms. Adoption of a technology or innovation by the individuals of a population can be Diffusion of Innovation (DOI) theory, there are five stages: knowledge, persuasion, decision, implementation, and conclusion. In the knowledge stage, users learn about technology itself and how to use it. In the persuasion stage, the attitudes toward techn ology are formed. In the decision stage,

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141 users decide whether to adopt technology. In the implementation stage, users put technology into practice. Finally, in the confirmation stage, users seek support for the decision they made about technology. In this study, participants may have been in different stages of diffusion while taking the survey and being interviewed. Their decisions about their may have differed even from day to day. For example, when taking the survey, a participant may have be en in the persuasion stage , in which attitudes are formed or in decision stage in which decision for adoption is made , but by the time of the interview, in the implementation stage. This progress may have caused or contributed to the disconnect between the qualitative and quantitative data . Another possible reason for the disconnect between the survey and interview results may relate to the use of CAMYS in a mandatory setting. Asil et al. (2014) study showed that the survey used in this study was a valid and relevant scale for measuring computer attitudes of young students. On the other hand, studies using CAMYS invariably either involve the voluntary use of technology (Dundar & Ackcayir, 2014) or do n ot specify whether the technology use was voluntary or mandatory (Milic & Skoric, 2012) t here are no studies using CAMYS to measure computer attitudes in mandatory settings. However, in this study, students were given and expected to use , whic h could be regarded as mandatory technology use. This shows that a data collection tool might not differentiate what it is intended to measure in an appropriate way in different settings. Specific to this study, participants might have had higher scores in CAMYS that did not reflect their actual attitude toward in a mandatory setting. In other words , students may have use d ,

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142 irrespective of whether they had negative or positive attitudes toward them, because they had to . This means that students with low scores in CAMYS may have still report ed that they use d their frequently. In this study, the items in CAMYS were s toward , but Chrome or specific applications installed on them . The operationalization of the in CAMYS was limited to the use of the device itself. Other aspects of using , like applications (Google Suite ) or content related software (Geogebra) , were not included. This made it somewhat unclear what a student intended when he or she answer ed general questions about a . Students benefited from the c loud for di fferent instructional purposes The other point to discuss is middle school students based system Google Slides for creating presentations and find it very creative and satisfying. They also stated that Google Docs help for spelling and auto correcti ons. Google Sheet is another application that is based on cloud computing and students use it to create charts . Similarly, they indicated that Google Drive makes the submission of their assignments very easy on their Chromebooks . In addition to Google applications, students also use some Google extensions for their assignments. For example, students use Google Read&Write extension for its highlighting and voice to text feature and find them very satisfying. One of the most salient affordances of Chromebook is that it has a cloud based system. Cloud computing could be defined as a model for enabling ubiquitous, convenient, on demand network access to a s hared pool of configurable computing

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143 resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider p. 183). Chromebooks are fully compatible with Google Classroom and the Google applications which are based on cloud computing such as Google Docs , Google Sheets , an d Google Slides . Cloud computing has many affordances and benefits for students similar to other educational stakeholders such as teachers, IT personnel and educational institutions. Through cloud computing in their Chromebooks , students could extend their learning out of the school. Cloud computing services also promote management practices that can be exemplified as creation, storage, transfer, and application of knowledge. Improved management of knowledge has an important role on high academic performance. Students can acces s and store written information easily through cloud storage on Chromebooks . They could also share resources and communicate with their classmates and teachers over the Internet (Arpaci, 2017). The sharing feature of Google applications make students able to assess their peers (D enton, 2012). As Arpaci (2017) stated that cloud computing helps students to retrieve and search information more quickly and easily. In addition, students could study on the same document for making some changes to improve a shar ed document in collaborative way ( Thomas, 2011). An open communication could be achieved by using cloud based tools because students could see what their peers type . For example, students create a collaborative reflection on what they have learned in class through Google Docs . While doing this, students c ould collaborate while planning and revising their writing as a group (Denton, 2012).

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144 Additionally, students coul d provide fe by using Google Docs . Since the back and forth communication is easy on Google Docs , st udents could communicate their friends quickly to interpret their feedback better and apply them in a more effective way (Ne umann & Kopcha, 2019). With cloud computing, students need less coordination especially for group projects because they can work on the same document simultaneously (A rpaci, 2017). In addi tion to benefits and affordances of cloud based system of Chromebooks for academic purposes , there are benefits also for some behavioral aspects of the student learning. Cloud computing could enhance student engagement ( Bagley, 2018 ; Goyal & Krishnamuthy, 2018). Goyal and Krishnamuthy (2018) also found that stud satisfaction and perceived learning could be improved by cloud based educational environments. Google applications socialability. Students could publish what they create on Google Apps as a web page. This helps them to become global citizens (Nevin, 2009). Finally, cloud computing in education have some technical and environmental benefits. Since the documents created on cloud based system is automatically saved, there is no risk of lost of any work (Nevi n, 2009). Another benefit of cloud computing on Chromebook is that students can use the same application at their home without buying a license ( González Martínez et al., 2015). Additionally, Google apps do not need to be installed to the device so there is no need to heep some hard drive space for them (Nevin, 2009). One of the benefits of cloud computing on Chromebook is that students can use the same application at their home without buying a license (González Martínez et al., 2015). Students use the sa me tools at home and school so

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145 they just need to learn one learning environment which requires less effort If they use cloud based tools, students do not need to print any docume nts. This helps them to keep environment green (Nevin, 2009). Implications The picture that emerges from this study is one in which attitude toward or time/experience with . Attitude toward was also found to be an ineffective either in school or outside of school. Across subjects, there was evidence of different use s of . These results have implications for both a practical context and future research studies. Implications f or Practitioners In an educational technology based initiative, examination of acceptance of that technology provides insights for the success or failure of the initiative. The facto rs behind this success or failure could also be determined by attempts to investigate technology acceptance. The results of this study have some practical implications regarding essential diagnostics and actions to be taken . There are very few studies on 1:1 use of by students in the literature. However, the most valuable information about the acceptance of technology regardless of the method by which the data are collected. Hearing what students say about their t echnology use through interviews and measuring their attitudes and perceptions through surveys are critical, because students provide the most helpful and detailed information about their own use in classrooms. This study reported findings specifically related to the acceptance of by middle school students. Through this study, school leaders and

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146 school districts may decide that technology initiatives should be investigated based o n what students feel, do, and/or say , potentially improving their understanding of what à vis initiatives in a middle school environment. The results of this study can also inform its context by providing information about the current status of use and the attitudes of middle school students in a laboratory school toward the devices, to wit, the extent to which students perceive as useful and easy to use. Additionally, the study pro vides evidence on how students feel about using their . Most importantly, the ways these students actually use both in and outside of the school have been described in detail. In short, a s the first empirical study conducted on Chr in this school since 2012, this study enables teacher s and school leaders beyond just the subject school to understand the effectiveness of a initiative from the With this information , potential changes in imple mentation and policy adaptations needed to enhance the effectiveness of initiatives could hopefully be performed more systematically in this and other schools . B ased on the results of the quantitative parts of this study, it appears that educa tors need not be overly concerned about gender biases or gaps in using , particularly with respect to student attitude toward and use of the devices . Moreover, seem uniquely suited to students in middle school , regardless of their grade level or experi e nce using in and outs ide of the school.

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147 Students use for different purposes at varying frequencies in different classes. This finding has a practica l implication for teachers. Tea c her directed use of is dependent on teacher related factors. For example, to integrate into instruction, teachers should familiarize themselves with the and its applications appropriate to their subject and should be provided sufficient time and other support to do so . The different uses across classes imply that the expertise, skillset, and confidence of teachers are different, too. One of the mechanisms to alleviate discrepancies in how are used to provide meaningful and effective professional development for teachers. Through professional learning opportunities, teachers become familiar with what resources to use and how to use them when they are teaching in their own conte xt. Implications for Research ers Investigating produced information for researchers on how students perceive the in terms of its usefulness and ease of use. As become more widespread and as students become more sophisticated users, new research will be needed. meaningful difference in attitude between gender s , grade level s , and time/experience with has significant implications for future rese arch method s and measures . First, in this study, the variables were analyzed by themselves , with a one b enefit from the ability to control the effect of other variables on attitude toward . In future studies, a different analysis method might be incorporated to show relative effects of each variable. For example, three variables could be added to

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148 the analysis model together. Also, nonsignificant effects reported in this study refer to the fact that there are other factors that need to be taken into account when examining attitude s . For this reason, other relevant variables, such as pre vious computer/ experience (Meelissen & Drent, 2008) , support/encouragement to use computers/ (Vekiri, 2010) , and actual experience in academic use of computers/ (Smith et al., 1999) could be added to the model to identify the relative effect of each variable on attitude. More quantitative studies are needed to support the assumption that student related factors could influence their attitudes toward . Second, across the literature, a large number of di fferent computer attitude surveys are used , and the theoretical framework s of available surveys are often not clear. Another issue regarding measures is that there is no survey or questionnaire specifically designed for exam in ing use and attitu de; the survey used in this study had several limitations in this regard . CAMYS only focuses on three dimensions of computer attitude based on the T echnology A cceptance F ramework: perceived ease of use, perceived usefulness , and affect. However, there are other surveys that measur e computer attitudes such as the Computer Attitude Survey (CAS) (Nickell & Pinto, 1986), Computer Attitudes and Confidence Questionnaire (CACQ) (Levine & Donitsa Schmidt, 1998), and Attitudes Toward Computer Usage Scale (ATCUS) ( Po povich, Hyde, Zakrajsek , & Blummer, 1986) that include external factors or other important variables in technology acceptance like subjective norm, perceived enjoyment, self efficacy, and computer anxiety , which were classified as the most

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149 widely used exte rnal factors by Abdullah and Ward (2016). Future studies should examine attitudes toward using these measures . Additionally, the current study found that students used differently in terms of purpose and frequency depending on the class for which they used the devices , as teachers play an important role in how are used in school the y control w hen and how students access and use technology (Bebell & Kay, 2010). Teacher use of technology could be classified as either teacher centered or student centered. In a study by Liu, Wang , and Koehler (2019), teacher centered use was operationali zed as use of technology for knowledge transmission, while student centered use was defined as technology use to help students build knowledge. To and the extent to which student centered use is , data could be collected through surveys with , interviews with, and/or observations of teachers . As Grani and Maranguni (2019) reported in a meta analysis, most empirical studies (83%) collected data from university students about their acceptance of technology , with the restrelying on high school students, teachers , and other employees as their participants. By collecting data from middle school students, this study helped fill in the gap in the literature around This study produced evidence showing that there were both positiv e and high attitude s toward in a laboratory school. H ow this has been achieved among young students is particularly important . However, the acceptance of other devices and higher attitude toward these devices in laboratory schools have not bee n

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150 studied in the literature. Future studies should investigate whether other technology devices (tablets or mobile phones) in these kinds of schools produce similar results. Regarding the lack of alignment among the quantitative and qualitative analysis i n this study, there is an important implication for research. Well tested and comprehensive measures , as well as reliable and valid data from these measures , should be used to conduct future assess ments attitudes toward and use of . These measu res should be administered in a wide range of systematically selected schools with a large, diverse sample of middle and secondary school students. For future studies, different measures like observations of how students use can be used to col lect data about their technology acceptance. Observation of students can provide in depth perspectives about how students react to use in the classroom. At the same time, observations have limitations : They are often limited to a small number o f students due to cost effectiveness and time considerations. To compensate, other objective measures of actual use, like computer recorded usage or system logs , could also be used in future studies (Turner, Kitchenham, Brereton, Charters , & Budgen, 2010). Researchers should carefully evaluate the benefits and drawbacks of using self reports, observations, or log data when examining attitude toward and use of . We need more studies using a combination of survey implementation (w ith more complicated statistical models and with a different population) and case studies (selection of particular cases based on qualitative data) , which might better serve the purpose of having an appropriate research design to examine use an d attitude s .

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151 Limitations and Future Research Attitude s toward may also be influenced by the subject for which they are used. Attitudes toward may be related to attitude s toward math or science. For example, the use of C during science lessons may reinforce gender differences in attitudes toward both science and . This phenomenon was not examined in this study. This study uses self reported data. When participants self report their use of technology in their daily lives, actual usage may not be accurately measured. A social desirability bias could also be a concern in this study: Students may have underreported the challenges they experienced while using . For these reasons, self reported data may not be enough to completely explain technology acceptance of users. Limited measurement of actual behavior may lead to poor predictions or unclear relations hips between acceptance and other dimensions. Another limitation of this study is the limited extent to which its findings can be extrapolated to other schools and students. The 6 th and 7 th graders who were the subjects of this study may not be representative of students enrolled in other grades at other schools. Most likely, the results o f a study conducted in a different middle school would not align with the findings of the current study. Therefore, generalizations drawn from the results of this study should be carefully considered before they are applied to other populations or contexts . Future studies may choose populations in different levels of educational settings, using random sampling to choose secondary schools across the U.S., to measure technology acceptance. Another potential limitation of this study could be its exclusion of experiences with other technology outside of school. According to the interview findings, the students

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152 in this study had access to a variety of technological devices in their daily lives. Their erceptions of the ease of use and usefulness of in meaningful ways. This study did not analyze this potential factor. Additionally, in this cross sectional study, the variables of technology acceptance at a single point were examined. Howeve r, perceptions and attitudes related to technology may evolve dynamically over time (Karahanna et al., 1999). In the context of this study, students were required to use their from 6 th grade until graduation . Therefore, understanding their con tinued usage of is also important. Davis et al. (1989) claimed that cross sectional data about technology acceptance are not enough studies should also include an examination of technology acceptance over time. As experience with technology in creases, sustained usage decisions are made. In this study, the participants interviewed were 6 th and 7 th graders who had been recently given for at home and in school use. To date, may not be enoug h to determine their ultimate decision about whether to adopt . A longitudinal study could be the most effective way Another limitation related to the sample was its reliance on gender and age as the only in dividual differences between users. Cultural differences and environmental factors like habit, personality , and technology change (Maranguni & Grani , 2015) could also be included in the future studies.

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153 experience with technology and teaching in a school in which there was a technology initiative could result in unavoidable bias. Finally, the inherently complex nature of attit udes and acceptance is a limitation of this study. As the literature shows, attitudes toward computers and technology acceptance are not concepts that can be easily explained. Therefore, the understanding of acceptance of and attitudes toward C that this study has elucidated is limited. In summary, as school districts and states are extensively working on equipping students feel about and use them has been particulary important. This study was aimed at invest the computers using cloud based system terms of age, gender, and experience was taken. In addition, a knowledge base for how students ease of use, and usefulness have been established. The results of this study open a door for new research opportunities to nology acceptance. Most importa ntly, this stu dy highlight technological tool into schools.

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154 APPENDIX A SURVEY My name is Nihan Agacli Dogan. I am a doctorate student at the University of Florida.I am conducting a research study aiming to understand your attitudes toward and behaviors regarding your use. You are invited to participate in this research p roject because you are a 6th or 7th grade student. Your participation in this research study is voluntary. You may choose not to participate. If you decide to participate in this research survey, you may withdraw at any time. If you decide not to participate in this study or if you withdraw from participating at any time, you will not be penalized. The procedure involves filling an online survey that will take approximately 15 minutes. Your responses will be confidential. I may need your name to access you for an interview after this survey. But your name will not be used anywhere and any time in my research study. The survey questions will be about attitudes and perceptions about your . If you have any questions about th e research study, please contact me at 352 631 9937. Please select your choice below. Clicking on the "agree" button below indicates that: you have read the above information you voluntarily agree to participate If you do not wish to participate in the research study, please decline participation by clicking on the "disagree" button. Age: Gender : Female / Male Hours spent using outside of school in a week: Less than 1 hour About 1 2 hours About 2 3 hours More than 3 hours Hours spent using in school in a week: Less than 1 hour About 1 2 hours About 2 3 hours More than 3 hours Computer Attitude Measure for Young Students Please indicate the degree to which you agree or disagree with the following statement. 1: Strongly Disagree 2: Disagree 3: Neutral

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155 4: Agree 5: Strongly Agree 1 2 3 4 5 I use to learn things (PE1) I look forward to using (ATC1) I use to help me to do my work better (PU1) I feel that I am in control when I use my (PE2) I am not scared to use (ATC2) It does not take up much time for me to find things on (PU2) It is easy for me to learn how to use (PE3) I enjoy using (ATC3) I like to do assignments that allow me to use (PU3) is easy to use (PE4) It is fun to use (ATC4) allows me to do my work faster (PU4) Current Technology Use Survey to complete the following tasks. Tasks Yes No Doing homework Taking notes in the classes Sending and receiving emails Searching information for school work Surfing online for fun

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156 Chatting online Working with specific software Playing computer games Creating websites Participating online discussions

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157 APPENDIX B INTERVIEW PROTOCOL Today I am going to ask you several questions about your experience with that you are using at school and outside of school. I will be recording our conversation so that I can transcribe your answers later. Remember that it is important to be as honest as possible. No one will ever know who participated in the survey or what their answers were. Thank you for taking the time to meet with me. I have several questions to help guide our discussion. Please feel free to elaborate and expand your ans wer if you feel the questions do not cover all of your past experiences. The focus of this interview is to better understand your experience with . Close ended Questions to Build Rapport 1. Did you use last year? a. How long have you been using it? 2. How often do you use your ? a. Tell me how much (the frequency) you use it at school and outside of school. b. In some classes more than others? What classes used them most? 3. Would you describe a typical day you use it at school? a. Could you give me an example? 4. Tell me about how you use it outside of school. a. How did you complete an assignment at home you finished recently? Would you walk me through it? 5. What apps are you currently using on your ? a. Which apps are your most and least favorite? Why? 6. Tell me about an assignment or a project that you are most satisfying with/proud of you completed with your . a. How long did you work on it? b. Did you work on it alone or with a classmate or in group? c. What did you discover when you were done? 7. . How were they different from the assignments you had to use ? 8. Have you used your with your friend(s) to study? If yes, walk through me and tell me about your experience. 9. Can you share some examples of how your teacher uses in the classroom? a. What would it look like?

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158 b. How did the class begin and end? How long did you work on your ? c. Do you like how your teacher used it? What was the best moment? 10. Did you like [any of the 10 tasks from the survey] in ? Why or why not? 11. How do you feel while you are using your ? a. Why do you think you feel that way? What has your experience been that informed this? b. What do you like/dislike about your ? 12. are mandatory tools to use at P. K. Yonge. Do you feel there is a need for at school? Why? a. What particular concerns do you have? b. to use? c. What would you tell other students in Florida about Chrome ? 13. Can you please tell me how effective you think you spend your time with your ? 14. In what ways do you think your is useful? 15. Can you please tell me how user friendly you think is? Wrap up 16. Is there any additional i nformation you would like to share about your experiences with ? 17. Do you have any questions or comments that you would like to add? Thank y ou again for your participation.

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159 APPENDIX C OPT OUT FORM *Note: if you DO consent for your child to take part in the study, you do not need to take any actions. If you DO NOT want your child to participate in the study, please complete the form below. For students who are not participating, teachers have been asked t o give them a quiet, individual activity that will take up the same amount of time. Title of the research study: Description and exploration of middle school : A mixed method study Purpose of the research study: The purpose of this research study is to attitudes toward and their use of . What your child will be asked to do in the study: Your child will be asked to complete a survey first. In this survey there are questions aiming to obtain a and to identify purposes students use for two related activities. Then, some st udents will be selected for an interview in which I will ask questions for eliciting and establish ing a knowledge base for how students use as a learning tool and to ask for stories to reveal details. Time required: Approximately 15 minutes for the survey and 30 minutes for the interview . Risks and Benefits: There are no risks associated with this study. The responses of your child This study has the potential to influence teachers by providing information on how their use of translates into student experience. Teachers can use the re sults of this study to encourage their students to use for their own benefits. Compensation: None. Confidentiality: Before the data being delivered to the rese archers, all identifying information will be removed for research purposes. Voluntary participation and the right to withdraw from the study:

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160 s completely voluntary. There is no penalty for not participating. Your child has the right to withdraw from the study at any time without consequence. In the survey or interview, your child does not have to answer any question s/he does not want to answer . Whom to contact if you have questions about the study: Nihan Agacli Dogan, via email telephone at or 352 631 9937, or Dr. Kara Dawson, via email or telephone at or 352 317 6811 participant in this study: UF IRB office, via email or telephone at or (352) 392 0433 I do NOT want my child to take part in the study described above. __ ________________ __________ Print Name __________________________ Signature ____________ Date

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163 LIST OF REFERENCES Abell Foundation. (2008). One to one computing in public schools: Lessons from . Baltimore, MD. Adebowale, O. F., Adediwura, A. A., & Bada, T. A. (2009). Correlates of computer attitude among secondary school students in Lagos State, Nigeria. International Journal of Computing and ICT Research, 3 (2), 20 30. computer assisted language learning. Procedia Social and Behavioral Sciences, 103, 852 859. Agarwal, R., & Prasad, J. (1997). The role of innovation characteristics and p erceived voluntariness in the acceptance of information technologies. Decision Sciences, 28 (3), 557 582. Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Action control (pp. 11 39). Berlin: Springer. Ajzen, I. (1988). Attitude s, personality and behaviour. Milton Keynes, UK: Open University Press. Akkoyunlu, B., & Erkan, S. (2013). A study on student and teacher views on technology use. Procedia Social and Behavioral Sciences , 103 , 68 76. Amoako Gyampah, Kwasi, & A. F. Salam. ( 2004). An extension of the technology acceptance model in an ERP implementation environment. Inf ormation & Management, 41 (6) , 731 745. Argueta, R., Huff, D. J., Tingen, J., & Corn, J. O. (2011). Laptop initiatives: Summary of research across six states . Ra leigh, NC: Friday Institute for Educational Innovation, North Carolina State University . Asil, M., Teo, T., & Noyes, J. (2014). Validation and measurement invariance of the computer attitude measure for young students (CAMYS). Journal of Educational Computing Research, 51 (1), 49 69. Ayres, R. (2002). Learner attitudes towards the use of CALL. Computer assisted Language L earning , 15 (3), 241 249. Bartolo, P. (2017). Integrating Google Apps and Google Chromebooks into the core curriculum: A phenomenological study of the lived experience of public school teachers (Unpublished doctoral dissertation) . Liberty University, Virginia. Bayhan, P., Sipal, R. F., & Karaaslan, B. T. (2009). Computer use among Turkish middle school pupils: Identifying gender differences in attitudes towards computers. In EdMedia: World conference on educational media and techn ology

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185 BIOGRAPHICAL SKETCH Nihan A Kutahya , Turkey. In 2011 , s he earned a n integrated Bachelor of Science and m aster s degree in c hemistry e ducation at the Bogazici University. S he started another master s program in curriculum and i nstruct ion in the same institution but then decided to pursue her career as a teacher . Before coming to the U.S., s he worked at IELEV Schools for 2 years as a science teacher . In 2014, Nihan got married and moved to Gainesville, Fl orida. In 2015, she started to pursue her Ph.D. at the University of Florida. During her Ph.D., she had worked as a graduate assistant in several research projects for 3 years and as a teaching assistant for 1 year. Sh e received her Ph.D . degree in curricu lum and i nstruction with the specialization of educational t echnology in 2020 . Sh e presented at national and international conferences in the U.S. Nihan is married to Sel ç uk with whom s he has a cute son, Poyraz.