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INHIBITION AND WORKING MEMORY CONTRIBUTIONS TO CHILDREN' S
TOWER OF LONDON PERFORMANCE
CHRISTINE A. MACDONALD
A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE
UNIVERSITY OF FLORIDA
Christine A. MacDonald
I would like to thank my thesis committee Drs. Keith Berg, Scott Miller, and Peter
Delaney for their tireless commitment to this project.
TABLE OF CONTENTS
A C K N O W L E D G M E N T S ......... ......... .. ..................................................................... iii
LIST OF TA BLES ......................... ................................... .... .... ............ vi
LIST OF FIGURES ......... ....... .................... ............ .... ........... vii
A B STR A C T ...................... .................................. ........... ... ....... ....... viii
1 IN TR O D U C T IO N ............................................................. .. ......... ...... .....
In h ib ition ..................................................................................... . 4
W working M em ory ............... ..................... .............. ... 7
Contributions of Inhibition and Working Memory ...................................................9
2 M E T H O D .............................................................................13
P a rtic ip a n ts ............................................................................................................ 1 3
P ro c e d u re ........................................................................................1 3
T O L ..............................................................................1 4
D ay-N ight Stroop ............................................................16
Spatial N -back .................................... .........................17
B oxes T ask ............................................................................................... ....... 19
3 R E S U L T S .............................................................................2 0
T ow er of L ondon ............................................................... ........ 20
Perfect Solution Accuracy ..................................................... 21
F first M o v e T im e ............................................................................................. 2 2
E x tra M o v e s .................................................................................................... 2 3
Rule V violations ............................................................................... 23
D ay -N ig h t S tro o p ................................................................................................... 2 3
S p atial N -b ack ................................................................2 5
Inter-T ask R elation ship s ........................................................................................ 2 5
4 D IS C U S SIO N ............................................................................... 3 1
A N-BACK FORMAT AND VERBAL INSTRUCTIONS ..........................................36
B TOL FORMAT AND VERBAL INSTRUCTIONS ................................................38
C BOXES FORMAT AND VERBAL INSTRUCTIONS .........................................40
D STROOP FORMAT AND VERBAL INSTRUCTIONS................ ..................42
L IST O F R E F E R E N C E S ......... .. ............... ................. ................................................43
BIOGRAPH ICAL SKETCH ...................................................... 47
LIST OF TABLES
3-1 TOL average results by difficulty level........................................... .................. 21
3-2 Average results for all tasks by age group .................................... ............... 25
3-3 Correlation m atrix for all tasks and age ....................................... ............... 27
LIST OF FIGURES
2-1 Day-Night Stroop presentation on touch-screen computer..................................16
2-2 Spatial N-back presentation on touch-screen computer................ ..................17
3-1 Average percent correct by difficulty level for each age group.............................22
3-2 Average percent correct for each trial block by age group ....................................24
3-3 Working memory and TOL performance regression plot. Predicted values are
unstandardized predictions of working memory with age removed ........................29
3-4 Inhibition and TOL performance regression plot. Predicted values are
unstandardized predictions of inhibition with age removed .............. .....................30
Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science
INHIBITION AND WORKING MEMORY CONTRIBUTIONS
TO CHILDREN'S TOWER OF LONDON PERFORMANCE
Christine A. MacDonald
Chair: W. Keith Berg
Major Department: Psychology
The Tower of London (TOL), a goal directed problem solving task, is recognized
as a useful tool to measure Executive Functioning (EF). The purpose of the current study
was twofold. The first objective was to expand our understanding of how normally
developing children perform on the TOL task as an EF measure. The second, and major
focus of the study, was to examine what cognitive processes are devoted to performance
on the TOL as there remains debate as to what cognitive constructs make up EF. Children
3- to 6-years-old were given the TOL, the Day-Night Stroop, and the spatial N-back to
look at the extent to which inhibition and working memory (WM) contribute to TOL
performance in young children. In regard to the first goal, the results demonstrated that
there are age related increases in TOL performance as older children are more accurate
and make fewer extra moves when solving TOL problems. To the second goal, the
overall results demonstrated that the ability to successfully inhibit a prepotent response is
necessary for successful TOL performance in young children. A final model showed that
inhibition but not WM significantly predicted TOL performance with age controlled. This
demonstrated that at least for children, good inhibitory control may be the key to
successful TOL performance.
To carry out flexible problem solving a host of cognitive resources are required
including goal-directed behavior, selective attention, planning, response inhibition, and
working memory maintenance-- or together, executive functions (EF). Tower transfer
tasks (Tower of London and Tower of Hanoi) are commonly used to evaluate problem
solving skills and to a larger extent EF in young children (Bull, Espy, & Senn, 2004). As
the pool of EF literature swells many different higher order cognitive skills are cited as
being crucial to EF skill level (Bull et al., 2004; Dowsett & Livesey, 2000; Miyake et al.,
2000, for reviews). The Tower of London (TOL) measures EF through the evaluation of
goal directed behavior. The TOL is a spatial object transformation task in which the
participant is required to rearrange a set of three balls on pegs to match those on a goal
board within the fewest number of moves (Berg & Byrd, 2002, for review).
As a complex problem solving task, the TOL likely involves the use of a number of
EFs. To understand the ability to perform this task it is important to evaluate these
underlying components (Welsh, Satterlee-Cartmell, & Stine, 1999). Therefore, the
purpose of the present study is to identify of two distinct and important EFs, ability to
inhibit prepotent responses and ability to manipulate items in working memory, that are
likely to contribute to successful performance on the TOL task.
One important consideration in EF tasks is its neural underpinnings. It has been
recognized that the prefrontal cortex (PFC) is the main locus of control for many EF
abilities and this is most apparent when participants with damaged frontal areas are tested
on EF tasks like the TOL (Carlin et al., 2000; Shallice, 1982) and Wisconsin Card Sort
(Kimberg & Farah, 1993). These deficits are also demonstrated on component processes
such as inhibition (Luria, 1966) and working memory (Levin et al., 2002). The protracted
development of the PFC makes incorporating and integrating the processes that make up
executive functions for effective problem solving a major challenge for young children
(Fuster, 1989). Similarly, poor EF performance has been noted in normal young children
on EF tasks such as the TOL (Anderson, Anderson, & Lajoie, 1996), and Wisconsin Card
Sort (Welsh & Pennington, 1988). However, little consideration is made to the details of
children's poor EF abilities, especially concerning the component processes that may
contribute to their difficulty with EF tasks. In fact, Espy, Kaufmann, Glisky, and
McDiarmid (2001) advocate a need to distinguish specific cognitive profiles of young
children. As Espy et al. explains, it is important to determine any detriment that may be
apparent in EF ability in the critical preschool years so to provide intervention early.
Further, the ability to catch delays early before the entry into formal schooling is
A wide range of behaviors seem to be affected by EF in childhood including
ADHD (Sonuga-Barke, Dalen, Daley, & Remington, 2002), mathematical ability (Bull &
Scerif, 2001), and certain neurodevelopmental disorders (Ozonoff & Jensen, 1999)
therefore it seems necessary that its development is fully tracked and understood by
researchers. However, very few studies attempt to examine EF before the age of 7-years-
old; especially overlooked is the toddler to young childhood age range (Welsh &
Pennington, 1988); furthermore there are even fewer studies that examine normal
development in this age range. A primary reason for the lack of research is the dearth of
developmentally appropriate EF measures. It is also the case that those tasks that are used
to determine EF ability, like the TOL have not been formally evaluated extensively
enough to understand what cognitive components are being measured by them (Phillips,
Wynn, Gilhooly, Della Sala, & Logie, 1999; Welsh et al., 1999). As researchers both
continue and begin to explore the significance of the frontal cortex in EF, it is important
to identify developmentally appropriate tasks that are useful to examine the development
of EF and to fully understand the cognitive components of these tasks.
Fuster (1989) noted three aspects of EF that come together to interact and produce
goal-directed behavior. These are working memory, planning, and inhibition. Many EF
tasks are assumed to tap each of these cognitive processes, to one extent or another, to
generate an estimate of the participant's overall EF ability (Miyake et al., 2000). The
steps required to provide accurate and efficient solutions to TOL problems very likely
include inhibition and working memory processes as well as planning components. The
TOL spatial problem solving task, with its transformation from a starting position to a
goal position, very likely also involves both working memory and inhibition, though to
what extent they are important and there relative contributions has only begun to be
assessed. Working memory is important to keep intermediate moves goal focused, while
response inhibition is needed to generate correct intermediate moves, some of which may
be counterintuitive, or moves into a non goal position. It is reasonable to hypothesize that
the contribution of these components are needed to produce effective solutions by all
participant populations including young, old, clinical, and normal.
The TOL is particularly useful as a measure of EF in children because the
procedure presents researchers with the opportunity to incorporate a variety of difficulty
levels (Shallice, 1982). This keeps the game challenging for various ages, with even
younger children having success at initial problems (MacDonald, Garner, & Spurgeon,
2002). Most TOL problems given to children can be solved well within two minutes. The
ability to arrive at a solution quickly and receive feedback is compatible with young
children's attentional capacities.
In sum, although the TOL is a common tool in use throughout the EF literature on
clinical (Carlin et al., 2000; Levin et al., 2002; Levin et al., 1996) and non clinical
(Anderson et al., 1996; Krikorian, Bartok, & Gay, 1994; Welsh et al., 1999) studies, very
few studies have empirically evaluated the validity of the accompanying assumptions that
are made concerning what cognitive processes contribute to task performance. In
particular, it would be useful to know what role inhibition and working memory play on
the TOL performance as these components seem to be large threads of the EF braid.
To demonstrate accurate goal directed behavior one must be able to ignore what
may be irrelevant or extraneous information to focus on the relevant information needed
to obtain the goal. Young children have difficulty exerting control over what they do and
there is a fair amount of evidence that this control especially improves between the ages
of 3 and 6 (Diamond & Taylor, 1996; Gerstadt, Hong, & Diamond, 1994; Kochanska,
Murray, Jacques, Koenig, & Vandegeest, 1996).
As a component of EF, inhibition is required to suppress an inappropriate
immediate response or response tendency. Dowsett and Livesy (2000) suggested that
because inhibition plays a role in a number of EF tasks, EF training should result in
increased inhibitory control in children that initially displayed poor inhibitory control. In
their study Dowsett and Livesy divided a sample of 3- to 5- year old children into
"inhibitors" and "noninhibiting" as defined by performance on a go-no-go discrimination
learning task. This task consisted of an apparatus that the children were instructed to
press a bar when a light was lit red (go) and not when it was lit blue (no-go). After
splitting the children into groups the noninhibiting were subjected to either training on
two EF tasks (Wisconsin Card Sort and a change paradigm) or practice on the go-no-go
discrimination learning task. Results of their study revealed that exposure to tasks that
require EF abilities significantly improved the young children's inhibitory performance.
In fact, 12 out of the 15 noninhibiting children were showing performance equal to that of
the inhibitors upon retesting. It was concluded by the researchers that inhibitory skills are
central to EF processes.
A task commonly used to measure inhibition in adults and older children is the
classic color/ word Stroop task (Stroop, 1935). The color/word Stroop takes a relatively
automatic response, reading, and pits it against the perceptual cue of the words ink color.
Inhibition is required during the interference condition in which the participant is
required to name the ink color when the color word is conflicting. Therefore, the
inhibition can be measured as the number of incorrect responses given by the participant
and/or the slower responding during the interference condition.
The original Stroop task was designed to measure inhibition of a verbalized reading
response, as the participant reads the ink color of the word aloud. Variations of the
original color/ word Stroop have been developed that do not involve a reading response
and instead requires inhibition of a motor response (Carlson & Moses, 2001). The use of
a pictured stimulus rather than a word in this task improves the task for use with younger
children in that it removes the reading requirement. The Day/ Night Stroop is a simplified
version of the original Stroop in which during the interference condition the participant is
shown "day" cards instructed to respond by pointing to a picture of night, and shown
"night" cards and instructed to point to a picture of day. Therefore, a Stoop effect is
produced in that the participant must inhibit a natural tendency to select the visually
matching stimulus and instead select the opposite stimulus. The Day/ Night Stroop task
was originally used by Passler, Issac, and Hynd (1985) to demonstrate the development
of inhibitory ability of children 6- to 12-years-old. Passler et al. (1985) suggested that
inhibition develops in a stepwise multistage process that achieves control
contemporaneously with the maturity of the frontal lobes.
To allow for successful planning when solving the TOL motor inhibition is
required before most moves, but particularly to repress the desire to move the balls
directly in the goal position when this is not optimal response. That is, the response
inhibitory process is especially taxed when solving problems involving such
counterintuitive moves. The counterintuitive problems, although they may contain as
little as three moves, are ones that require the initial placement of a ball in a non-goal
position before being able to place that ball in its final goal position on a subsequent
move. This is counterintuitive because it may temporarily move the problem solver away
from the goal. The failure to inhibit the more obvious move due to poor inhibitory control
will result in excess moves or inaccurate solutions. These types of problems also create
situations in which rule violations are common because the child seems unable to try the
counterintuitive alternative and instead chooses to attempt a perhaps more intuitive albeit
illegal solution to the dilemma.
Working memory (WM) is involved on a number of executive or frontal lobe tasks,
particularly those that require planning. Most EF tasks require the participant to actively
monitor his or her progression throughout the task, holding a subset of events in memory,
and then making updates to those events to optimize their responses (Phillips et al., 1999;
Roberts, Hager, & Heron, 1994). In the TOL task, planning toward a goal requires the
WM on-line revision mechanism to constantly maintain the goal relative to the starting
Age differences in the role of WM in TOL performance among adults was
examined by Phillips, Gilhooly, Logie, Della Sala, and Wynn (2003) in a comparison of
older (60- to 76-yeas old) and younger adults (18- to 30-years old). Phillips et al. (2003)
used a dual task paradigm to analyze different three aspects of WM (Baddeley, 1986 for
review), executive, phonological articulatoryy suppression and verbal random
generation), and visospatial (spatial pattern and spatial random tapping) for effects on
TOL performance. They hypothesized that age differences in the role of WM would
suggest that the TOL makes different cognitive demands on different age groups. The
results showed that TOL performance was impaired more for younger adults when the
dual task was high on executive load whereas for older adults executive load did not
impair TOL performance. This pattern of results were opposite when looking at the
visospatial dual task disruption. Here older adults faired worse than younger under dual
tasks of TOL solving and spatial memory tasks. The results supported their hypothesis
and showed when cognitive limitations are pushed there are developmental differences in
the detriments on TOL performance for older and younger adults. These data demonstrate
that TOL performance may extract different cognitive abilities depending on the age of
The N-back is a WM task that requires the participant to process some information
or rule that dictates the response to a given set of task stimuli (i.e., letters, numbers, or
objects). The objective of the task is to test the ability to hold and monitor information,
like a rule, as while assessing each piece of subsequent information. The rule can be
manipulated to create different levels of difficultly; 0-back, 1-back, or 2-back. For
example, Levin et al. (2002) tested traumatic brain injured children ages 6- to 8-years-old
using a letter identity N-back. The rule in this case depended on the condition either
being that a target letter must be responded to (0-back condition), or a response must be
made when a match appears to a letter displayed 1-back, 2-back, or 3-back. Levin and
colleagues concluded by noting the applicability of the N-back task for use with children
to test prefrontal WM abilities. Instead of a letter identity N-back, Thomas et al. (1999)
used a spatial N-back to test WM in 8- to 10-year old children. For this task, participants
were presented with a screen displaying four squares and a button box with four
corresponding keys. The rule given was to match the location in which the dot appeared n
trials back in the middle of any given square upon presentation by pressing the correct
corresponding button. This method is similar to the one being used in the current study as
There is evidence that spatial WM in particular makes a considerable contribution
to TOL performance. A link with TOL performance and spatial working memory in
children was established by Lehto, Juujarvi, Kooistra, and Pulkkinen (2003). Here, Lehto
et al. tested 8- to 13-year-olds and found a significant correlation between proportion of
perfect solutions of the TOL and spatial working memory. Although not the main goal of
the study, age effects were found with the TOL but not spatial working memory.
However, a significant correlation between age and spatial working memory
demonstrated that there were improvements with age.
Contributions of Inhibition and Working Memory
Welsh et al. (1999) examined the proportional contribution of inhibition and
working memory to EF performance for adults as measured by the TOL. For this study,
participants received 4- to 6-move problems on the TOL, two tests of inhibition and two
tests of working memory. The inhibition tasks used color/word Stroop and the
Contingency Naming Test. The working memory tasks used were the Visual Memory
Span and the Spatial Working Memory Test. In general the study found that both
inhibition and working memory performance explained over half of the TOL
performance variance. Although both inhibition and working significantly contributed to
TOL performance the relationships among the tasks were uniquely different. First it
should be noted that spatial working memory (r = .61) held a higher correlation than
visual working memory (r = .49). Also it is interesting to point out that of the two
inhibition tasks used by Welsh et al., the color/ word Stroop task (r = .40) held a
significant relationship whereas the Contingency Naming Test was not related (r = .06)
with TOL performance. The authors suggested that this difference may be because the
inhibition tasks selected for were measuring different kinds of inhibition. I will return to
this issue in the Discussion.
This study by Welsh et al. (1999) demonstrates the cognitive contribution to TOL
performance in normal adults, whom are generally noted to have high EF abilities as
maturation has reached a relatively pinnacle state. It is important to understand the
development of EF as it begins early in life and continues throughout adulthood. This
expansive developmental period is due to the ongoing cognitive changes that occur as the
frontal lobes mature, leading to improved inhibition, planning, mental representation of
tasks and goals, and hence improved general EF performance. This maturational process
presents the opportunity to study EF and how the behaviors and responses under its
control are affected by development.
In a recent study Rebbeca Bull et al. (2004) sought to replicate the Welsh et al.
(1999) study with a sample of preschoolers. Here Bull et al. gave normal children
between the ages of 3- and 6-years-old TOL and TOH (Tower of Hanoi, a similar tower
transfer task) problems along with a short term memory task, and an inhibition and
shifting task. The main focus of this study was not developmental, but was, like the
Welsh et al. study, to explore the contributions short-term memory and inhibition make to
TOL and TOH performance. Because working with young children imposes greater
session length time constraints than working with young adults, instead of giving
participants two of each memory and Inhibition tasks like Welsh et al. did, this study
gave one of each. The WM task given was a short-term memory digit span task, and the
inhibition task was a task that combined an inhibition and shifting condition. The
inhibition condition resembles a go-no-go task in which the child must name (based on
the color of the character) a line of characters that show expressions of happiness in the
picture, but not the ones that express sadness as fast as they can. The shift condition
added another dimension to the response contingency, shape. Here the children had to
name the character based on the color if the character without a hat and based on shape if
the character had a hat. Results showed that inhibition and shifting successfully predicted
TOL performance, whereas short-term memory performance did not. In contrast, the
Welsh et al study with adults described earlier suggested that for adults it was WM that
was the greater contributor. Unfortunately, the two studies used quite different measures
of inhibition and WM. Therefore, although this study yielded interesting results, it would
be important to see what kinds of comparisons can be made when the tasks more closely
resemble those given by Welsh et al. (WM instead of short-term memory) so that
conclusions can be better compared across development.
Overall, from the data presented it is reasonable to suggest a contribution of both
spatial WM and inhibition to TOL performance in adults. However, there is still
insufficient evidence to confidently conclude that there is a significant contribution of
both inhibition and WM to TOL performance in young children. Furthermore, the
question remains as to what similarities in children's TOL performance could be drawn
that from that reported previously for adults. The reason for the paucity of evidence for
children is twofold. First, most studies that involve EF, inhibition, and WM are not based
on normal populations and consequently include small sample sizes. The second reason is
that most EF, inhibition, and WM studies do not include very young children in the
sample. The majority of these studies begin the youngest sampling at 7-years-old
although tasks such as the TOL, Day-Night Stroop, and spatial N-back are noted as
suitable for children much younger (Gerstadt et al., 1994; Levin et al., 2002; Welsh &
Therefore, the current study will explore the extent to which two main cognitive
processes, inhibitory control and spatial WM, contribute to EF performance as measured
by the TOL. Although the TOL is frequently used as a task to measure EF ability, many
questions remain regarding the cognitive components that contribute to task performance.
The study will also fill a gap in the current literature by providing normal developmental
data for children younger than 7-years-old. The current study will contribute by
attempting to answer a number of questions, including: (a) How does inhibition and
spatial WM contribute to TOL performance for young children? (b) Will young
children's TOL performance show higher correlations with WM than inhibition
performance as the adults' did according to Welsh et al. (1999) findings? And (c) how
does development affect TOL performance within the 3- to 6-year-old age range?
Participants between 3- to 6-years-old (N= 43, range from 41 months to 69
months) were recruited from preschools throughout the local Gainesville community. The
preschools sampled were chosen in an effort to represent of a wide range of socio
economic and education levels. There were slightly fewer girls (n = 16) than boys (n =
27) sampled. Children were excluded if they have ever been professionally diagnosed
with ADHD, a learning disorder, or tested as gifted based on prescreening questions on
the participant consent form filled out by the child's guardian. The participant was tested
for handedness at the beginning of the session and then encouraged to use the dominant
hand throughout the session. All participants were treated according to the published
APA recommendations for ethical treatment of participants (American Psychological
The total procedure took no longer than 45 minutes per participant. Participants
were rewarded with stickers at the end of each session. All participants were presented
the tasks in the order of Spatial N-back, Boxes task, TOL, and finally Day/Night Stroop.
Through pilot testing it became apparent that the Spatial N-back was the most
challenging task for the children. By placing it first the author thought it would be
minimally affected by fatigue. Also placing the TOL in the middle allowed a break from
the computer tasks to help keep the children interested. All tasks, with the exception of
the TOL, were presented on a touch screen computer. The screen was placed directly in
front of the child on the floor while the child sat with their legs crisscrossed. This was a
natural, comfortable position for the child.
All participants performing the TOL were videotaped for later scoring of details of
moves made. The camera was arranged behind the participant with an over-the-shoulder
view to record the action of both hands and to reduce distraction.
The TOL consisted of two identical game boards and one "done" button. The two
game boards, one participant board and one experimenter board, were each made up of
three descending pegs tall, medium, and short, which accommodated three, two, and one,
equally sized wooden balls colored, red, green, and blue, respectively (7.62 cm in
diameter). The pegs were mounted on a wooden game board (40 cm x 9 cm). To play, the
participant moved the balls on the pegs of the participant board to mach the goal state as
shown by the experimenter's board. After solving a problem the child was instructed to
press the "done" button. The "done" button is a dummy button that served two functions.
First, during the testing session, it indicated to the experimenter that the participant was
finished solving the problem, and it also became important for subsequent scoring from
video tape (Results section). The button was placed to the right or left of the game board
depending on the child's handedness as tested at the beginning the session.
There were 12 TOL test problems, ranging in difficulty from problems that take 2-
moves to 5-moves to solve. The 12 test problems were presented in 3 blocks. Each block
contained four problems increasing in difficulty level (2-move, 3-move, 4-move, and 5-
move). Each move level is indicative of the minimum number of moves it takes to solve
each problem. The participant had a maximum of 2-minutes to solve each problem. If the
child could not finish within the 2-minute period they skipped that problem and moved
on to the next.
The experimenter first explained all instructions and gave examples of the rule
violations as they were explained (Appendix for full task procedure). The experimenter
then walked through a demonstration of how to solve a 2-move problem with the child
while specifically explaining the goal of task, how to move toward the goal, and the rule
violations. There were three rules the participants were required to adhere to: (a) only one
ball can be moved at a time; (b) a ball can be placed only on a peg, and; (c) each peg is
limited to the number of balls that can be placed on it: three balls on the largest peg, two
balls on the middle peg, and one ball on the smallest peg. Then the participant is given
two practice problems to do on their own, one 2-move and one 3-move. The child was
required to pass both of the practice problems within two attempts before moving to the
test session. If the child failed after the second try, they were excluded from TOL testing.
However, no children in the current study that failed either practice problem.
During the testing session, each problem proceeded until either the child hit the
"done" button, the maximum time elapsed, or the child violated a rule. If a child did
begin to violate a rule, the child's movement was immediately stopped and redirected.
For example, if a child began to move two balls at one time (a rule violation), the
experimenter stopped the child after the balls were picked up, but before the action was
completed. The balls were then returned to the original position and the child was
verbally reminded of the violation and asked to continue solving without making another
violation. This method restricted the participant from using violations to solve the
problems, but allowed the researcher to track their occurrence. Movements during the
violation did not contribute to any time or move measures.
The participant performed this task entirely on a touch screen computer (Figure 2-1).
For the current study only the interference condition, being the condition which
required a non-matching versus a matching response when shown a "day" or night" card,
was presented (Appendix for full task procedure).
Figure 2-1 Day-Night Stroop presentation on computer
The following Day-Night Stroop testing methods were an adaptation of Carlson
and Moses (2001) and Gerstadt et al. (1999). Following an explanation of the task to the
child, there were two (one Day, one Night) practice trials that included the prompt "What
do you touch when you see this card?" and feedback. The next two trials (one Day, one
Night) were pre-test trials. Like the subsequent test trials, these did not include a prompt,
but the pre-test trials did include verbal feedback. The participant had to pass both of the
pre-test trials, thus demonstrating knowledge of task instructions, to be included in the
testing session. If a child failed any pre-test trials, they were excluded from the Day-
Night Stroop testing, but were included in other tasks. There were no children in the
current study that failed the pre-test. The pretest was followed by 16 test trials.
The computer program presented an equal number of each "day" and "night" cards
in a pseudorandom order identical to that given in Gerstadt et al. (1999). The position of
the day and night cards, right or left side, on the touch screen for the participant to choose
was also randomized to reduce response biases. A bulls-eye was positioned between and
below the cards on the screen. The children were instructed to rest the selection finger in
the middle of the bulls-eye in between trials. This served to avoid anticipatory responding
and to standardize the distance through which the response was made. Response timing
for the selection of a card on each trial began when a new card appeared and ended when
the child selected a day or night card.
The version of the spatial N-back was adapted from Thomas et al. (1999) and Levin
et al. (2002) with the modifications made for use with younger children (Appendix for
full task procedure). The stimuli for this task are three squares centered in the middle of
the touch screen (Figure 2 for an accurate depiction of the screen layout).
Figure 2-2 Spatial N-back presentation on touch-screen computer
The response buttons, one green smiley face and one red unhappy face, were
centered under the squares on the screen. Inside any one of the squares, a star can appear.
For the 0-back condition, a randomly defined "target" square was identified for the child
as being in the right, left, or middle location. The target remained the same throughout
the 0-back condition. After the child was shown which square was their target square,
they were asked to indicate if the current spatial location of the star matches the target
square identified at the beginning. This served as a check to determine if the child could
remember the target location. Under this 0-back condition, if the star showed up in the
target square the child was instructed to press the green smiley face. If the star was not in
the target square the red unhappy face must be selected. For the 1-back condition, no
predesignated star position was indicated. Instead, the child was instructed to press the
green smiley face when the star, "stayed still" and was in the same square as on the
previous trial. If the star "moved" and was in a different square than the previous trial the
child was instructed to press the red unhappy face. For all trials, the star appeared every
two seconds for 500 ms maximum or until the child made a response by selecting either
the smiley face or unhappy face. Thus, all conditions a response was required on every
trial. The conditions followed sequentially in order of increasing difficulty beginning
with 0-back and proceeding through 1-back. Please see the Appendix for details of task
The general N-back task instructions were followed by the 0-back condition
instructions and 10 practice problems. The practice problems differed from the test
problems in that they included verbal feedback from the experimenter and they did not
have the 500 ms response time restraint. Following the practice problems, 21 test trials
were given of the 0-back condition. Then, instructions andl0 practice problems were
given for the 1-back condition, followed by the corresponding 21 test trials. Of the 21
test trials in each condition, 9 were target (location matched) trials and 12 were distracter
(location not matched) trials.
Although the Boxes task was presented, due to technical limitations the task results
were not analyzed. See the Appendix for a full description of the task.
Generally, analyses consisted oft-tests and ANOVAs to examine age effects within
all tasks. The participants were placed by age at testing into three groups; 3-year-olds
(range: 41- 47 months, n = 7), 4-year-olds (49-59 months, n = 25), and 5-year-olds (60-69
months, n = 11). Regressions and correlations were run to determine the relationships
between and within tasks and specifically to assess the contribution of inhibition and
working memory to TOL performance. Not all children were included in each analysis.
One child did not want to play the TOL, and three children refused to play the N-back.
All children completed the Stroop. Specific ns are provided below for the various sets of
Tower of London
All test problems were video taped and subsequent to testing were coded by having
a trained laboratory assistant "play along" with the video to replicate the child's moves.
Watching the tape, the assistant did the "play along" using a computerized simulation of
the TOL task. This then provided a computer record of not only which moves were made,
but also the timing of each move. Rule violations including picking up two balls at one
time, putting a ball somewhere other than on a peg, or exceeding the maximum amount
of balls that the peg can hold were manually recorded during video replays. Violations
were coded as either present or absent on each problem. The interrater reliability was
determined from a sample subset of 17. Interrater agreement for timing accuracy to
within 1.0 s per move was calculated at 97% for this sample. Interrater reliability at 100
% agreement was achieved for the sample in determining the execution of rule violations
and 99% for the number of moves that were made.
For analysis of variance, the independent variables were age and problem difficulty
level consisting of four levels. The difficulty level was determined by minimum number
of moves (2- move, 3- move, 4- move, and 5- move) required to solve the problem. The
primary dependent variables are percent perfectly solved (that is, solved within the
minimum amount of moves), and on those problems solved perfectly or not, extra moves,
latency to the first move, total time, and frequency of rule violations. The sample size for
this analysis was 42. See Table 3-1 for TOL results overview.
Table 3-1 TOL average results by difficulty level
TOL Difficulty Level (Minimum Number of Moves)
Perfect Solution Accuracy
An age by difficulty level repeated measures ANOVA revealed both a main effect
of difficulty level, F(3, 117) = 18.05, p < .001, and of age, F(2, 39) = 4.54, p < .05, but
no interaction effect (Figure 3-1).
2 3 4 5
Percent Solved 34)
89(19) 68(29) 66(38) 44(34)
First Move Time 6 09(277) 746(426 9 17(628) 841 (435)
Extra Moves 37 (89) 26 ( 56) 63 (1 33) 99 (2 24)
1.0 -C 3 year Olds
G.9 A --i-year Olds
2 3 4 5
Minimum Number of Moves
Figure 3-1 Average percent correct by difficulty level for each age group
Follow-up t-tests were run to analyze the overall differences in performance
between successive difficulty levels. Results generally suggested that accuracy decreases
as difficulty level goes up at each level, p < .01, with the exception of 3-move and 4-
move problems (Table 3-1).
When the effects of age were analyzed more closely it was revealed that significant
differences existed among 3- and 5-year-olds' performance, t(16) = 3.51,p < .01, and
between 4- and 5-year olds' performance t(16) = 2.50, p < .05.
First Move Time
As with the perfect solves analysis, first move time the analysis revealed a main
effect of difficulty level (F(3, 81) = 3.70, p < .05), a main effect of age (F(2, 27) = 3.99,
p < .05), but unlike the analysis of perfect solves, there was a significant interaction of
age and difficulty level (F(6, 81) = 2.86, p < .05).
In general, as difficulty level increases all children took more time to begin
problem solving. However, overall the older the children took less time before beginning
to solve. To explain the interaction, t-tests were run to compare 3-, 4-, and 5-year-olds
first move time at each difficulty level. It was noted that differences in first move time
occur on 2-move and 3-move problems between 3- and 4-year-olds and between 3- and
5-year-olds and on the easiest 2-move problems for 4- and 5-year-olds (all p < .05).
Interestingly there were no significant differences between first move times on 4- or 5-
move problems upon each age comparison. However, there is a marked decrease in first
move time for those 3-year-olds who solved 5-move problems from their 4-move first
move time. Only 5 of the 7 three year-olds were able to solve the 5-move problems which
may have dampened a potential significant effect.
When extra moves were considered, more extra moves were made on the most
difficult problems (F(3, 87) = 5.41, p < .01). As predicted, a main effect of age shows
that younger children also made more extra moves overall (F(2, 29) = 7.44, p < .01).
However, follow up t-tests showed that this difference was significant for 3- and 4-year-
olds, and 3- and 5-year-olds, but not for 4- and 5-year-olds. There were no interactions
produced between age and difficult level for extra moves.
The occurrence of violations did not follow the expected trend as there were no
significant effects of age or difficulty level.
For these analyses, age served as the independent variable (n = 43) and the
dependent variables were percent correct and average latency of the last eight trials of the
session. Preliminary analysis showed that the last half of the test trials represented the
most challenging trials (Figure 3-2).
: 1 2
Figure 3-2 Average percent correct for each trial block by age group
This was shown by a significant effect of trial block when it was found that the
participants were significantly more successful on the first 8 trials (M= .77, SD = .24)
compared to the last eight trials (M= .71, SD = .32), t(42) = 2.08, p < .05. Furthermore,
the first 8 trials did not produce an age effect. Taking this information into consideration
all remaining analysis was conducted on the last 8 trials of the Stroop. No age effects
were demonstrated upon an Analysis of Variance of age on these last eight trials (F(1, 39)
= .096, p > .05), though mean data did suggest that older children performed
outperformed younger children on these trials, 3-year-olds (M= .61, SD = .32), 4-year-
olds (M= .69, SD= .34), and 5-year-olds (M= .82, SD= .32) (Table 2).
As with percent correct, there were no significant differences in response latency
Like the Stroop, for all children the easier 0-back condition (M= .69, SD = .21)
proved to be significantly easier than the more challenging 1-back (M= .52, SD = .27), t
= 3.63, p < .01. Therefore, the N-back was analyzed using only performance on the most
challenging level, the 1-back (n = 40). The age analysis a Univariate ANOVA examined
the dependent variable percent correct responses on the 1-back and age. The analysis
revealed a trend for age, F(2, 43) = 2.98, p = .06. Descriptive statistics for means showed
that 5-year-olds (M= .65) performed better than both 3- and 4-year-olds (Ms = .43, .48;
respectively) (Table 3-2). Due to program error, the response times were not recorded
accurately and were not analyzed.
Table 3-2 Average results for all tasks by age group
Measure 3-year-olds 4-year-olds 5-year-olds Total
n=7 n=25 n=11 n=43
TOL .55 (.22) .64 (.22) .81 (.10) .68 (.21)
(Percent Solved Correctly)
Stroop .61 (.27) .69 (.34) .82 (.32) .71 (.33)
Spatial N-back .44 (.26) .49 (.19) .65 (.20) .55 (.21)
If the TOL task requires both an ability to inhibit ineffective moves and working
memory, as predicted, performance on the Day-Night Stroop and the spatial N-back
should correlate positively with TOL performance. If the TOL demands similar cognitive
processes in children as for adults, a test of regression model that includes both Stroop
and N-back regressions on TOL should indicate that both inhibition and WM explain a
significant amount of TOL performance variance replicating the results of Welsh et al.
(1999) with adults. There are no hypotheses regarding the extent to which either
inhibition or WM contribute independently.
For all inter-task relationships the most challenging aspects of each measure was
examined, last 8 trials of the Stroop, the 1-back level of the N-back, and percent of
perfectly solved 4-and 5-move TOL. This approach was taken so that difficulty level
between tasks could be relatively controlled. This is not to say that there are still no
inherent difficulty differences between the tasks, but that this difference will be
minimized. Percent correct for all tasks were run under bivariate correlations to examine
the relationship among all tasks.
Cross correlations of all three tasks variables (Table 3-3) showed that though all
bivariate correlations were positive, only Stroop and TOL correlation was significant, r =
.39,p < .05.
Table 3-3 Correlation matrix for all tasks and age
TOL N-back Stroop Age (months)
TOL .245 .391* .450**
N-back .202 .281
*p < .05
**p < .01
Because age and TOL are highly correlated (r = .45, p <.05), a partial correlation
was performed to see if the relationship still held with the effects of age controlled. TOL
and Stroop remained positively correlated, r = .41, p < .05, and slight improvement over
the simple bivariate correlation. Performance on the N-back held a positive, but non-
significant relationship with both Stroop, r = .20, and TOL, r = .25 without controlling
for age. The correlation coefficients are even further reduced when age is controlled, N-
back and Stroop, r = .11, and N-back and TOL, r = .15.
To assess the combined effects of variables as predictors of TOL performance, age,
percent accuracy for Stroop, and percent accuracy for N-back were analyzed in a forced
entry linear regression model for their ability to predict perfect solution accuracy on the
most difficult TOL, 4-move and 5-move, problems. First the variables were considered
for any independent contribution. Analysis revealed that performance on the Stroop
significantly predicted 15% of TOL performance variance, R2 = .15, F(1, 42) = 7.22, p <
.05, P =.35.
N-back performance did not predict TOL performance, R2 = .06, F(1, 39) = 2.36, P
=.34, p > .05. To remove any effect of age the analysis were run again with age in
included in the model for each variable independently. A forced entry method was chosen
so age could enter in the first position and the R2A could be examined to determine the
amount of variance in TOL performance is explained after removing age. The model with
age included showed that Stroop now contributed 31%, R2A = .10 to the variance
observed in TOL performance when age was removed. This model is significant, F(2, 41)
= 5.77, p < .05. A test of the model's standardized regression coefficients showed that
they are significantly different than zero, Age: = .02, p < .01; Stroop: P = .29, p < .05.
Like the Stroop, when age effects were removed first, N-back contributed more to TOL
performance variance, R2 = .19 with age removed, resulting in a significant model, F(2,
38) = 4.08, p < .05, showing a significant standardized regression coefficient for, Age: P
= .02, p < .05; but not for N-back: P = .20, p > .05 (Figure 3-3)
0 Actual Values I Predicted Values Linear (Predicted Values)
lo00 g O 0
0 050 7U O 0 0
o oo ---- 0 -- C -- O 0---,--
000 020 040 060 080 100
1-Back % Target Accuracy
Figure 3-3 Working memory and TOL performance regression plot. Predicted values are
unstandardized predictions of working memory with age removed
Finally the full model was tested using the forced entry method. This model tested
the effect of Stroop on TOL performance with Age and N-back accounted for:
1. TOL = Constant + Age + N-back + Stroop
This model was significant and explained 32% of the TOL variance, F(3, 39) =
5.39,p < .01 (Figure 3-4).
0 Actual Values I Predicted Values Linear (Predicted Values)
100 0 0
2* I EEE OI U0 0
o 0 60
0 I50I so I mma 0 0 0
000 010 020 030 040 050 60 070 080 090 100
Stroop % Correct
Figure 3-4 Inhibition and TOL performance regression plot. Predicted values are
unstandardized predictions of inhibition with age removed
However, upon examination of the R2A statistic it was noted that the model did not
significantly benefit with the addition of the N-back. Therefore, the best predictors of
TOL performance in young children seem to be Age and Stroop performance. It should
be noted that the model can be run to test the effects of N-back with Age and Stroop
accounted for, however the results are similar; the model does not benefit with the
addition of N-back.
The purpose of the current study was twofold. The first objective was to expand our
knowledge of how normally developing children perform on the TOL task as an EF
measure. The second, and major focus of the study, was to examine what cognitive
processes are devoted to performance on the TOL as there remains debate as to what
cognitive constructs make up EF. Overall results demonstrated that the ability to
successfully inhibit a prepotent response is necessary for successful TOL performance in
young children. These results are inconsistent with what is found with adults (Welsh et
al., 1999), but, as discussed below, are consistent with what is found in one report with
children (Bull et al., 2004). Taken together it seems that TOL performance may rely on
different cognitive mechanisms for adults and children.
With regard to the first goal, several aspects of the results suggest that executive
functioning can be successfully measured in preschoolers. This was especially illustrated
in the current study when using graded difficulty levels to capture the change in these
higher level cognitive processes. The TOL proved to be particularly useful to examine the
qualitative differences in problem solving by age. This was also true for the Day/Night
Stroop inhibition task. By carefully examining performance over all presented trials there
was a clear indication that only the last half of the trials were challenging for the children.
Surprisingly this result was distinguishable with only 8 Stroop trials. These results reveal
the importance of looking at a range of difficulty when examining EF in children.
To help illustrate the differences in young children's TOL performance the TOL
was subjected to discrete quantitative analysis. Analysis of the accuracy performance
showed the expected trend in that 2-move problems were easier than 3-move, 4-move and
5-move. Also, as expected, older children outperformed younger children overall. This is
especially exemplified in that the oldest children solved an average of 26% more
problems than the youngest children.
Like the accuracy measure, the amount of time taken before executing the first
move showed a general increase with difficulty level. As indicated by the interaction, as
the difficulty level increased from 2-move problems to 3-move problems the latencies of
older children were shorter than those of younger children were but this difference was
not significant for 4- or 5-move problems. This could be because there were only five 3-
year-olds that solved the 5-move problems accurately suggesting there may have been
lack of statistical power. Overall, older children started problem solving faster than
younger. This result combined with the accuracy result, suggests that the older children
are taking a more efficient approach to problem solving in that they are not comprising
accuracy for speed.
With regard to the second goal, determining the contribution of inhibition and
working memory to children's planning, the results demonstrated that inhibition was
more closely related to planning performance as measured by the TOL than was working
memory. This held true even after controlling for age and working memory. Working
memory, on the other hand, did not produce any significant contribution independently,
nor when age was controlled, nor when age and inhibition was controlled. This is an
important finding since working memory is a cognitive construct thought to be a central
aspect of EF (Baddeley, 1996; Miyake et al., 2000). The results from the current study
can be compared to similar studies conducted with adults to shed light on their
developmental significance. Welsh et al. (1999) found that the model that included both
WM and inhibition significantly predicted TOL performance in young adults. Adults
showed a similar pattern of results in a separate study conducted by Phillips et al. (2003).
Taken together it seems that for young adults planning as assessed by TOL performance
is best predicted by a conglomerate of higher level cognitive components. However, this
may not be true for normal young children.
The study conducted by Bull and colleagues (2004) complement those found in the
current study in that inhibition, and not WM was proven to be the predictive factor for
TOL performance for normal young children. In fact, this result was amplified for those
problems that were the most complex in the subset given. Moreover, Bull et al. found no
relationship between TOL performance and short term memory. However, it can be
argued that the digit span task the researcher chose may not show a relationship because
it is not tapping the kind of working memory used for TOL solving. A short term memory
task that tests the ability to recall digits in the correct order may not be the same as a
working memory task that tests for the ability to hold, manipulate, or update information
pertaining to the repercussions of some future move in your memory. The current study
used a version of the spatial n-back which requires that the participant hold a piece of
information related to the spatial location of an object (which square the star was in the
previous trial) to use for the current trial. This information, if held correctly, is then
updated in relation to the current trial and used to make an accurate response (same
square, press smiley face; different square, press unhappy face). This task is more closely
related to the spatial working memory task given in the Welsh et al. study. In this study,
the WM task required the participants to generate as many unique spatial sequences as
possible by touching four white squares. To generate all 24 unique sequences within the
session required that the participant hold and update information about the sequences
already generated and those that still exist. The typed of tasks used in the current study
and the Welsh et al study were used specifically to assess the kind if working memory
that is more likely tapped in TOL performance.
Although Bull et al. (2004) found inhibition to be a significant contributor to TOL
performance, their discussion suggests that the correlation between inhibition and TOL
performance may be misleading because for the TOL the children were given move
information prior to beginning to solve. Specifically they suggest that this added
information may have somewhat forced an inhibiting response that was used to
successfully monitor the number of moves being made for the TOL. The current study
can speak directly to that hypothesis and suggest that the relationship between inhibition
and TOL is not artificial as there was no move information given to the participants.
There were certain limitations in the current study that should be addressed. First,
there was a lack of the expected age differences in inhibition and WM. This may be due
to the unequal age distribution in the sample (Figure 12). The majority of the sample
consisted of 4-year-olds which was the middle age group. This left little statistical power
for the 3-year-old age group. On the other hand, there were age differences found for the
TOL. This may suggest that the inhibition and WM tasks used in the current study were
not sensitive enough to detect age differences as the TOL was.
Secondly, it should also be noted that there are still questions that remain about the
cognitive components that make-up successful TOL problem solving. While inhibition
explained over 30% of the variability in TOL performance, there was still a large part that
remained unexplained. For example, one component that could explain a large amount of
the variability is strategy use. A more detailed analysis of TOL problem solving and
strategy use could further distinguish problem solvers into those that make efficient
choices and those that do not. The current study does not attempt to dissolve these
differences as both efficient and inefficient solvers can end up with an accurate solution
and so they are treated equally in the current method of analysis.
In conclusion, EF is often criticized for its lack of a clear definition. Researchers
agree that the array of EF tasks (e.g., TOL, WCST) may tap into different cognitive
components and that this differential may even be pronounced depending on the
cognitive limitations that age presents (Bull et al., 2004; DeLuca, et al., 2003; Lehto et
al., 2003; Phillips et al., 2003; Welsh et al., 1999). Results from this study help bridge the
gap that exists between measurement and definition when it comes to EF. Particularly
this study answered some fundamental questions that exist concerning children's
performance on the TOL, an EF task, through revealing which cognitive components are
best predictors of TOL performance. Further, a comparison of the pattern of results
obtained from the current study and those conducted by others added to the paucity of
knowledge pertaining to the nature of task demands and whether they are similar or
different in adults and children.
N-BACK FORMAT AND VERBAL INSTRUCTIONS
The session will progress increasing in memory load blocked by condition, from
the 0-back condition to the 1-back condition. Each condition will have a set of
instructions, eight practice problems, reminder of the rules, and then proceed with 21 test
trials. For the test trials, the star will appear in a new location every two seconds for 500
ms; the experimenter will manually forward practice trials for learning to take place.
1. General introduction to task format-child is shown boxes with stars in the center.
a. On the screen you will see three boxes. Inside one of the boxes there will be a
blue star (point to star in middle of box)
2. Zero back condition
To play this game I want you to press the "yes" smiley button when the star is in
the box (location will be randomly selected as center, left, right box. In
explanation it will be "center box" or "this (point) box" to avoid using right, and
I want you to press the "no" unhappy button when the star is not in the box
like in this one (point).b. Practice problems (10)
No specific criteria to proceed, but child must demonstrate adequate
understanding of at least the 0- back condition to proceed to any other conditions.
c. Brief reminder of instructions
d. Test trials (21)
3. One- back condition
To play this game I want you to press the "yes" smiley button when the star is in
the same box as one just before it and press the "no" unhappy button when the
star is not in the same box as the one just before itb. Practice problems (10)
c. Brief reminder of instructions
d. Test trials (21: 9 target and 12 distracters)
TOL FORMAT AND VERBAL INSTRUCTIONS
1. Demonstration Problem. After goal board is set, set participants board to start position.
All problems will begin like this.
This is called the puzzle game, do you think you can point to and name all of the
colors of the balls to the puzzle game?
2. If child successfully names all colors, proceed.
I am going to show you how to play. I have one puzzle that's all finished, see?
(experimenter points to their board) You have one just like it, but the balls are all
mixed up. To win the puzzle game you have to fix your puzzle so it looks just like
3. Go around to child's side of the table and move the balls to match the goal state (2-
Watch how I move them to make yours look like mine.
4. Reset the puzzle and allow the child to do the same problem by itself.
Now let's see if you can do that.
5. Explain the Rules by demonstrating them
Before we start there are some rules about how to move the balls. First, you can
only move one ball at a time. Second, you cannot put a ball down anywhere else
but on a stick. The third rule is that the shortest stick can have 1 ball, the medium
stick can have 2 balls, and the big stick can have 3 balls.
When you are done with your problem I want you to press the white button (show)
to tell me you are ready for another problem, OK?
There are a couple of things I want you to try and do while we play the game, OK?
Try to use one hand only (prevents the child from picking up more than one ball at
a time). Try to move only the balls you really need to fix and try to work as fast as
you can. You win the game when your puzzle is fixed exactly like mine and then
you can pick out some stickers.
6. Practice Trials. Set up practice trials using a 2-move problem for the first trial and a 3-
move problem for the second.
Before we start let's do some practice ones, OK?
7. If the child did not successfully the complete practice problem, the experimenter shows
the child how to do it and lets the child try the same problem again, until successful
BOXES FORMAT AND VERBAL INSTRUCTIONS
Like the N-back, the Boxes task will begin with the least difficult 2-box condition
and proceed through the 6-box condition. The Boxes task involves searching through a
set of boxes (3-6 boxes) until a reward (a star) is found. There was one trial presented in
the 3-box condition, two in the 4-box condition, and three each of the 5- and 6-box
condition. The one key rule was that once a star is found in a particular box, that box will
never contain another star over that particular set of boxes. The task was presented on a
touch screen computer and the child "opened" each box by touching it (Figure 3). The
box opened for the child for a duration of 1000 ms to expose whether it was empty or
contained a star on that particular search sequence. If the child found a star, it was
automatically moved to the side of the screen once the box was touched. The stars were
collected at the side of the screen until all stars were found for that particular trial (the
number of stars to be found is equal to the number of boxes presented for the trial). The
child was then verbally praised for finding all of the stars and the next trial started.
In a 6-box condition, the participant must search through all the boxes to find
where the star is hidden without returning to a box that has already been searched and/ or
a star has been found in.
The verbal instructions were as follows:
We are going to play a game where you have to touch some picture boxes on the screen
here, OK? See these boxes? Each box will have one star inside of it, see? To play this
game, you have to touch the boxes to open and find the stars inside. The stars will line up
on the side here. You have to find all the stars to fill up the side and then we will play
again. There is just one rule though. Once there is a star found in a box it can never be
used again to hade a star.
STROOP FORMAT AND VERBAL INSTRUCTIONS
We are going to play a game where you have to touch a picture on the screen as fast
as you can, OK? See these pictures? This is day (point), and this is night (point).
We are going to play two different games with these pictures
To play this game when you see Day (point) I want you to press the Night picture
(point) and when you see Night (point) I want you to press the Day picture (point).
While you are playing, I need you to keep your pointer finger right in the middle of
the pictures, on the bull's eye. Do you see the bull's eye? Can you put your finger
on it? GOOD!
2. Test Trials
Remember when you see day, touch night and when you see night, touch day.
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Christine A. MacDonald attended DeLand High School in DeLand, Florida. After
graduation she moved to Jacksonville, Florida, to attend the University of North Florida
where she graduated with her bachelor's with a major in psychology.