





































4848

Graduate Student Journal of Psychology
2023, Vol. 21

Copyright 2023 by the Department of Counseling and Clinical Psychology
Teachers College, Columbia University

Interference Effects on Procedural Memory:
 An Assessment of Problem-Solving Task Performance

Samuel A. Birkholz1, Eric E. Hessler2, & Michael Root3

1, 2 Department of Psychology, University of Minnesota Duluth,
3 Department of Psychology, Minnesota State University Moorhead

Three experiments were conducted to assess interference effects acting on procedural task learning and performance 
using the Tower of Hanoi puzzle. In Experiment 1, participants in the no-interference group completed the Tower 
of Hanoi faster than the retroactive interference groups, with no differences between the types of tactile interference. 
These results indicate that retroactive interference may hinder procedural task performance but does not differentiate 
between consolidation and retrieval. Experiment 2 addressed retroactive interference placement by manipulating the 
delay prior to the interference task. Interfering with only consolidation or recall did not produce interference effects, but 
qualitative feedback regarding emotion raised questions about the effects of affect induction. Experiment 3 attempted 
to address the influence of a proactive and retroactive affect induction technique but did not produce a dichotomous 
happy versus neutral effect. Overall, the series of experiments conducted provides a conceptual replication of some pre-
vious research while contradicting other findings. This research not only extends our current understanding but also 
highlights the need to continue to explore factors that may influence the practice or acquisition of novel procedural tasks.
 Keywords: procedural learning, interference, affect, memory, Tower of Hanoi

 Memory refers to the ability of an organism to 
store, retain, and retrieve information over time (At-
kinson & Shiffrin, 1968; Baddeley & Hitch, 1974; 
Cowan, 1999). It is a complex process that involves 
multiple brain regions and neural networks (for re-
view, see Squire et al., 1993). There are several types 
of memory, including working memory, short-term 
memory, and long-term memory. Working memo-
ry refers to the cognitive system responsible for tem-
porarily holding and manipulating information in 
the mind to perform complex cognitive tasks, while 
long-term memory refers to the storage and reten-
tion of information over a prolonged period, ranging 
from minutes to years, that is retrieved when needed 
(Cowan, 2008). Long-term memory is further di-
vided into different subtypes, such as episodic mem-
ory, semantic memory, and procedural memory.
 Procedural memory is the type of memory that en-
ables us to learn and recall skills and procedures neces-
sary for daily life, from simple actions such as brushing 
our teeth to complex activities such as playing an in-
strument or driving a car. This type of memory is crit-
ical for our ability to perform tasks efficiently and ac-
curately without conscious effort or thought. It is also 
involved in the acquisition of new skills and the refine-
ment of existing ones, making it essential for personal 
and professional development (Squire et al., 1993).
Comparing Procedural Memory to Other Types 
of Memory
 Procedural memory is often implicit, meaning it 
operates outside of conscious awareness and without 

deliberate effort (Squire et al., 1993). When perform-
ing a skilled task, the individual is not necessarily aware 
of every step involved in the process, but rather, their 
body and mind learn the sequence of movements and 
actions through repetition and practice (Fitts, 1964). 
This type of memory is often referred to as muscle 
memory since the movements become autonomous 
and are often performed with little or no conscious 
thought (for review, see Packard & Knowlton, 2002).
 Another key feature of procedural memory 
is its resistance to forgetting (Squire et al., 1993). 
Once a skill or procedure has been learned and 
stored in procedural memory, it can be retrieved 
and executed with little effort or conscious thought, 
even after years of disuse. This is because procedur-
al memory is primarily stored in the basal ganglia, 
cerebellum, and motor cortex regions of the brain, 
which are involved in motor control and movement 
planning (Packard & Knowlton, 2002). This is in 
stark contrast to episodic and semantic memories.
 Episodic memory is a type of long-term memory 
that involves storing and retrieving personal experienc-
es, events, and episodes (Baddeley, 2000). Examples of 
episodic memory include remembering one’s first day 
of school, a family vacation, a significant life event, or 
simply how to complete a puzzle. Episodic memory.
involves conscious effort and is associated with the 
hippocampus and related brain regions (Tulving & 
Markowitsch, 1998). Another trademark of episodic 
memory is that it is declarative, meaning that it in-
volves conscious recollection. This is a similarity that 



49

ASSESSING INTERFERENCE EFFECTS

episodic and semantic memory share (Tulving, 1999).
 Compared to episodic memory, semantic memo-
ry involves the storage and retrieval of general knowl-
edge and information about the world rather than 
specific events (for review, see Tulving, 1999). Se-
mantic memory is associated with the neocortex and 
related brain regions, and it differs from other forms 
of memory in that it is more abstract (for review, see 
Allen & Fortin, 2013). However, extensive research 
indicates that episodic and semantic memory is prone 
to interference (Eakin & Smith, 2012; Flaisch et al., 
2016; Wohldmann et al., 2008; Yang et al., 2013).
Interference in Different Forms of Memory
 Various factors can influence the accuracy and 
reliability of stored information. One such factor is 
interference, which can disrupt the encoding or re-
trieval of information, leading to memory errors or 
loss (Unsworth et al., 2013; for review, see Robertson, 
2012). Interference can be broadly classified as pro-
active and retroactive. Proactive interference (PI) is 
where previously learned information interferes with 
the encoding or retrieval of new information, while 
retroactive interference (RI) is where newly learned 
information interferes with the rehearsal or retrieval of 
previously learned information. For example, imagine 
trying to remember a previously learned list of items 
but then learning a new list of similar items. The 
new list may retroactively interfere with the retrieval 
of the old list, making it more difficult to remember.
 Unsworth et al. (2013) conducted a series of exper-
iments to understand how PI and RI affect memory re-
call for word lists. In Experiment 1, participants recalled 
words from either one or two lists. Both interference 
types caused lower recall, more intrusions (incorrect 
items recalled), and longer recall times. The hypothesis 
that participants might search both lists simultaneous-
ly but eliminate intrusions before recall was tested in 
Experiment 2. Participants recalled words from both 
lists, resulting in roughly equal intrusions from Lists 1 
and 2. Rejecting intrusions was harder, and clustering 
indicated contextual cues helped recall. Experiment 3 
examined recall with varying set sizes. Recall of Lists 
1 and 2 was worse than control lists. Recalling both 
lists had worse results than recalling only one, repli-
cating the "only effect" where combining lists led to 
larger search sets. Participants still included irrelevant 
items, causing interference. Finally, Experiment 4 used 
distinct categories for each list. Recall outcomes were 

similar for all three lists, suggesting distinct categories 
focused on participants' search and reduced interfer-
ence, resulting in comparable recall without intrusions.
 Unsworth et al.’s (2013) results also might sug-
gest that the effects of RI vary depending on the type 
of information being retrieved. For example, RI may 
have a greater effect on semantic memory than ep-
isodic memory. Another factor that has been well 
documented to influence the extent of RI in humans 
(Osgood, 1946; Wickelgren, 1965) and non-human 
primates (Medin et al., 1980) is the degree of sim-
ilarity between the old and new information. The 
greater the similarity, the more likely it is that RI will 
occur. A third factor is the amount of time that has 
elapsed since the new information was learned, with 
more recently learned information being less suscep-
tible to RI (Reyna, 1995). Yet, these patterns of re-
sults might be limited to declarative forms of memory.
 The mechanisms underlying RI in procedural 
memory are not fully understood. However, stud-
ies suggest that RI may affect different stages of pro-
cedural memory processing, including encoding or 
acquisition, consolidation, and retrieval (for review, 
see Robertson et al., 2004). Acquisition refers to the 
initial learning of a new motor skill. Studies have 
shown that RI can impair the acquisition of proce-
dural memory. For example, in Brashers-Krug et al. 
(1996), participants learned to compensate for ve-
locity-dependent forces on a manipulandum and 
were immediately tested on a second task. Learning 
the second task within a short time period interfered 
with the retention of the first task. However, this RI 
was gradually reduced with the increase in the time 
interval between the two tasks. The study provides 
evidence that human motor memory is transformed 
rapidly with time and in the absence of further prac-
tice, in addition to providing evidence that RI occurs 
in tasks that rely heavily on procedural memory. This 
means that learning a new motor task can interfere 
with the consolidation of a previously learned task, 
making it more difficult to acquire the new task. This 
also suggests that RI may interfere with the encoding 
or consolidating new motor skills, lead ing to mem-
ory errors or loss. However, Brashers-Krug et al. did 
not differentiate between consolidation and retrieval. 
 Similar results are reported by Friedman and 
Korman (2016). In their study, participants complet-
ed a finger opposition task where they touched their 



50

BIRKHOLZ ET AL.

thumb and another finger in a specific sequence. They 
first did four test trials and then 10 training trials with 
the sequence shown on the screen. Then, half of the 
participants did an interference training session with 
a different sequence. All participants were tested again 
24 hours later on the original sequence and a different 
sequence with both hands. Analyses suggested that RI 
prevented delayed gains in correct sequences but not 
accuracy and that two types of processes contributed 
to procedural learning: one sensitive to interference 
(consolidation) and one independent (recall). Yet, 
similar to Brashers-Krug et al. (1996), Friedman and 
Korman (2016) did not attempt to interfere with the 
recall or retrieval process independent of other stages.
 Retrieval refers to the process of accessing and 
using previously learned information. When further 
scrutinized, Brashers-Krug and colleagues’s (1996) 
results also appear to suggest that RI may not affect 
the retrieval of procedural memory, but their meth-
ods do not address this directly. More recent research 
has shown that RI can interfere with the retrieval of 
a previously learned task, possibly across memory 
types, making it more difficult to execute the previous-
ly learned task. Gagné and Cohen (2016) used a ran-
domized controlled trial to investigate how interfer-
ence between memory systems affects skill acquisition. 
Participants were assigned to one of four groups, each 
receiving a different combination of verbal and motor 
interference tasks during a finger-tapping sequence 
learning task. The authors used various measures to 
assess performance, including reaction time, accuracy, 
and the number of correct sequences produced. Par-
ticipants were tested on the task immediately follow-
ing the learning phase and again 24 hours later. Only 
the control group showed offline improvement, and 
introducing a visuospatial task before motor recall 
eliminated the gains, thereby suggesting interference 
between memory systems during subsequent motor 
recall. This suggests that various factors may cause RI 
and that RI may also negatively impact some of the 
retrieval processes of previously learned motor skills. 
Within other types of memory, the idea that other 
factors such as similarity, time, and the amount of 
practice influence performance is not new, but these 
are not the only possible contributors to performance.
Emotion and Memory
 Emotional state can influence our ability to learn 
different types of information, including a new pro-

cedural skill. Procedural memory is closely linked to 
the brain's motor system, which is also involved in 
processing emotions (Packard & Knowlton, 2002). 
Studies have shown that emotional arousal can en-
hance memory formation and retention. For exam-
ple, LaBar and Phelps (1998) found that emotionally 
arousing words resulted in better memory retention 
than neutral words. The authors suggested that emo-
tional arousal enhanced the consolidation of semantic 
memory. Conversely, Rimmele et al. (2011) found 
that participants who were exposed to negative emo-
tional stimuli reported better memory retention 
than those who were exposed to neutral stimuli, 
even though their performance was actually worse. 
These mixed results suggest that our understanding 
of how emotion interacts with memory is lacking, 
especially within procedural memory paradigms or 
when emotion is evoked using different methods
 Regarding PI, Yang et al. (2011) induced positive 
affect in participants by giving them candy as a token 
of appreciation. Participants’ memory was then test-
ed using word- and operation-span tasks, presented 
in increasingly difficult order. The word- and opera-
tion-span tasks were 10 trials each, with two trials at 
each set size ranging from three to seven presented in 
random order. An increase in positive affect appeared 
to moderate memory improvements for words and 
numbers. Although similar anecdotal (e.g., an athlete 
reporting that feelings influence performance) and 
empirical evidence suggest similar effects may exist 
within procedural memory (Steidl et al., 2006), our 
understanding is far from comprehensive. However, 
one study does find an effect of emotion on procedur-
al skill learning within offline consolidation processes.
Javadi et al. (2011) recruited 99 participants who were 
divided into nine groups, with each group having a 
combination of retention type and emotional content 
conditions. Participants completed a mirror-tracing 
task where stimuli included faces that were negative, 
positive, or neutral in expression, with a significant dif-
ference between the valence scores of positive and neg-
ative images but no significant difference in the arousal 
scores. The experiment was composed of two sessions 
(training and testing) with either a 12- or 24-hour 
retention interval. Participants also completed a fin-
ger-tapping task, which was used to evaluate alertness. 
The results suggest negative content during encoding 
improves later performance on the mirror-tracing task 



51

ASSESSING INTERFERENCE EFFECTS

more than neutral or positive content. In fact, participants 
who learned with negative images had greater skill im-
provement over time compared to those who learned with 
neutral or positive images. Another relevant but secondary 
finding suggests that alertness does not play a role in perfor-
mance differences, which might suggest that physiological 
arousal is not as important as other factors. Although the 
most basic forms of PI and RI are not widely disputed, there 
is still some debate on the effects of emotion on learning, 
as the research findings have not always been consistent. 
Research has found positive and negative emotional states 
may enhance learning (Javadi et al., 2011; LaBar & Phelps, 
1998; Yang et al., 2011). However, other studies have found 
that negative emotional states may hinder learning (Flaisch 
et al., 2016; Rimmele et al., 2011). Furthermore, interac-
tions between variables such as level of skill expertise and 
affective tone have not been widely examined outside of 
video game literature (Weinreich et al., 2015), leaving gaps 
in the literature that should be addressed by basic research.
 Overall, while there is some debate on the effects of 
emotion on procedural learning, it is clear that emotional 
states can impact the learning and retention of procedur-
al skills. The exact nature of this impact, and whether it is 
positive or negative, may depend on various factors, such 
as the type of task, the individual's level of expertise, and 
the specific emotional stimuli involved. More research is 
needed to fully understand the complex relationship be-
tween emotion and procedural learning. To this end, we 
report on a series of three experiments conducted to (a) 
replicate the existing literature that demonstrates RI can 
directly impact procedural learning and performance, (b) 
clarify the importance and independence of the consolida-
tion and recall processes within procedural paradigms, and 
to (c) explore the specific impact of unexpected rewards 
on novel procedural task acquisition and performance.

Experiment 1
 Experiment 1 attempted to replicate previous liter-
ature that establishes RI within procedural paradigms 
(Brashers-Krug et al., 1996; Friedman & Korman, 2016; 
Gagné & Cohen, 2016; Robertson et al., 2004). We used 
the Tower of Hanoi as the target procedural memory task 
(see Figure 1), because it requires learning a specific set of 
rules and steps (Vakil & Heled, 2016) which can be taught 
instead of used as a measure of problem-solving. We ex-
pected that peg puzzles (see Figure 2) would produce the 
most interference due to their similarity to the Tower of 
Hanoi (Osgood, 1946; Wickelgren, 1965). Ring puzzles 

(see Figure 3) are less like the Tower of Hanoi and 
were not expected to cause the same level of inter-
ference, but interference was still expected to occur 
compared to the writing control task. Therefore, 
the hypotheses for Experiment 1 were as follows: 
1. RI that occurs between learning the Tow-

er of Hanoi and the final performance test 
was expectedto cause completion time 
(s) to increase significantly within the peg 
and ring interference groups when com-
pared to the no interference control group.

2. Participants in the ring interference group 
were expected to complete the task faster 
than participants in the peg interference 
group when retested on the Tower of Hanoi.

Method
Participants
 One hundred eight participants (30 men, 78 
women; 18–50 years of age) were recruited via a 
bulletin board flyer and received course credit for 
their participation. Data from one participant in 
the ring group were excluded because they could 
not complete the post-interference Tower of Ha-
noi task. Data from one participant in the peg 
group were removed due to a pre-interference 
completion time that was over three standard de-
viations from the mean. Data from two more par-
ticipants (one peg group, one ring group) were ex-
cluded for having a post-interference completion 
time that was over three standard deviations from 
the mean. Therefore, data from 104 participants 
were included in the final analyses (see Table 1).
Materials
 The Tower of Hanoi (see Figure 1) required 
participants to move a tower of discs from a start 
peg to a target peg. There were two rules for moving 
the discs: (a) only one disc could be moved at a time 
and (b) a larger disc could not be placed on a small-
er disc. The Tower of Hanoi task varies in difficulty 
based on the number of discs used. The minimum 
number of moves the puzzle can be completed in 
is calculated using the equation f(x) = 2n-1, where 
f(x) represents the fewest number of moves and n 
equals the number of discs. Typically, the puzzle 
consists of three pegs and three disks. Difficulty in-
creases as the number of discs increases. To make the 
task moderately difficult, the Tower of Hanoi task 



52

BIRKHOLZ ET AL.

used in this study consisted of three pegs and four 
discs. Successful completion of the Tower of Hanoi 
requires a set procedure that must be carried out in a 
specific order. The specific sequence extends the task 
beyond motor memory and forces participants to use 
spatial problem-solving skills and procedural memory.
 Some participants in the study worked with either 
three different peg puzzles or eight different ring puz-
zles, each with a unique goal and set of rules. The three 
peg puzzles (see Figure 2) were the in-line puzzle (left 
panel), the elimination puzzle (center panel), and the 
addition peg puzzle (right panel). The in-line puzzle re-
quired participants to move pegs so that they switched 
sides, while the elimination puzzle involved removing 
all but one peg from play by jumping one over anoth-
er to an open spot. The addition peg puzzle required 
filling all holes but one by tracing preset lines between 
them, with the caveat that a move could not be made if 
it led to a previously filled slot. For the ring puzzles (see 
Figure 3), participants had to disconnect two linked 
metal pieces by twisting, sliding, or pulling them apart, 
using similar strategies for each puzzle. Completion 
times in seconds were recorded using a stopwatch.
Procedure
 First, each participant learned how to complete the 
4-disc Tower of Hanoi puzzle with verbal, written, and 
visual instructions. Written instructions were given to 
each participant and read aloud, briefly outlining the 
objective and rules of the task. The visual instructions 
(see Figure 4) were provided in the form of an animat-
ed .gif (Karwath, 2005), and by one researcher demon-
stration. The discs were color-coded by size. Once the 
animation began, the discs moved from the start peg, 
following the best sequence possible (a total of 15 
moves) to complete the task. The video lasted approx-
imately 30 s and was replayed six times for each partic-
ipant. After the instruction, participants were allowed 
two min to practice the Tower of Hanoi without the 
animation. This training method is modified slightly 
from Vakil and Heled (2016). Participants then ran 
through the Tower of Hanoi another time, complet-
ing it as quickly and efficiently as possible. Out of view 
of the participant, the researcher recorded the comple-
tion times (s) and the total number of moves made. 
 Following the practice phase, participants were 
randomly assigned to complete one of the three tasks: 
Writing control, ring puzzles, or peg puzzles. During a 
10-min period, control participants wrote a detail-ori-

ented description of the events of their day. If they 
finished early, they were instructed to write a detailed 
description of their favorite place on campus. Partici-
pants in the ring and peg puzzle groups solved as many 
of their respective puzzles as possible within 10 min. 
For both of those groups, puzzles were introduced 
verbally and in writing, with one visual demonstration 
by the experimenter. Participants repeated puzzles if 
they completed all of them within the 10-min period. 
Immediately following the interference task, Tower of 
Hanoi’s performance was assessed again using the same 
method described for the pre-interference assessment.

Results
 Homogeneity of variance was not violated for Be-
fore Interference completion time (p = .776) and com-
pletion time data appeared to be normally distributed. 
An initial analysis of variance (ANOVA) comparing 
completion times between groups before interference 
showed the effect of the Interference Group was not 
significant, F(2, 101) = 0.496, p = .611, η2 = .010, sug-
gesting that performance did not differ across groups 
prior to completing their respective interference or 
control task. Performance on the Tower of Hanoi 
was then examined using a series of 3 (Interference 
Group: Control, Ring Puzzle, Peg Puzzle) x 2 (Test 
Trial: Before Interference, After Interference) mixed 
ANOVAs on the dependent variables completion time 
and number of moves (power = 1.0). Homogeneity of 
variance was not violated for After Interference com-
pletion time (p = .615), Before Interference number 
of moves (p = .287), or After Interference number 
of moves (p = .158). Both of the main effects of In-
terference Group, F(2, 101) = 3.225, p = .044, ηp

2 = 
.060, and Test Trial, F(1, 101) = 17.587, p < .001, ηp

2 

= 0.148, were significant on completion time. The In-
terference Group x Test Trial interaction was also sig-
nificant on completion time, F(2, 101) = 12.883, p < 
.001, ηp

2  = 0.203. None of the main effects were signif-
icant on the number of moves, which suggests that all 
participants not only learned the puzzle but retained 
the steps equally well. Interpretations of the signif-
icant effects on completion time are provided below.
 A series of t-tests using Tukey’s correction were 
used to follow up on the significant main effect of the 
Interference Group. The Control and Ring Puzzle 
groups were significantly different (p = .038). Comple-
tion time was longer in the Ring Puzzle group (M = 



53

ASSESSING INTERFERENCE EFFECTS

23.914, SD = 6.807) than in the Control group (M = 
20.472, SD = 6.077), regardless of Test Trial. No oth-
er comparisons were significant. The significant main 
effect of Test Trial indicated that completion time was 
longer After Interference (M = 23.420, SD = 7.609) 
than Before Interference (M = 21.080, SD = 5.503), 
hinting that at least one group’s performance changed. 
Simple effects were run to follow up on the significant 
interaction effect and to further explore both within- 
and between-group differences. The simple effects of 
Test Trial at Ring Puzzle, F(1, 101) = 22.61, p < .001, 
r = .44, and Peg Puzzle, F(1, 101) = 16.82, p < .001, r 
= .32, were significant. Completion times were longer 
after completing the ring and peg puzzles than before 
completing them (see Figure 5). In contrast, the simple 
effect of Test Trial at Control was not significant, mean-
ing there was no difference in completion time before 
and after performing the control task. Simple effects 
also indicated that differences were driven by comple-
tion times being different across groups following their 
respective tasks, F(2, 101) = 7.92, p = .001, while no 
differences were observed in completion times before 
the conditions deviated, F(1, 101) = .500, p = .611.

 Experiment 1 Discussion
 Previous research has shown the potential for RI 
in procedural memory (Brashers-Krug et al., 1996; 
Friedman & Korman, 2016; Gagné & Cohen, 2016; 
Robertson et al., 2004). Experiment 1 aimed to exam-
ine the effect of interference tasks on the retrieval of 
procedural memory of the Tower of Hanoi puzzle. Re-
sults showed that the writing control group completed 
the Tower of Hanoi puzzle faster than the peg and ring 
interference groups after the respective interference 
tasks. However, the peg task, which was subjectively 
more similar to the Tower of Hanoi than the ring task 
did not produce larger interference effects. Notably, 
the results also suggested that the level of interference 
did not affect the participant’s total number of moves. 
These results support Hypothesis 1, but Hypothesis 2 
was not supported. Experiment 1, like other research, 
did not compare the effects of consolidation and retriev-
al on RI (Brashers-Krug et al., 1996; Friedman & Kor-
man, 2016). Experiment 2 was conducted to investigate 
the importance and potential independence of these 
processes in procedural memory and skill acquisition.

Experiment 2
 Javadi et al. (2011) focused on retrieval as the 
point of action for RI. Another important process po-
tentially affected by RI is the consolidation of newly 
acquired memories (Brashers-Krug et al., 1996; Fried-
man & Korman, 2016). Consolidation aids in memo-
ry retention by organizing material in working memo-
ry and preparing it for transfer into long-term memory 
(Squire, 1986). Without the consolidation process, 
memory would not transfer. This study aims to address 
the effects of RI on the differentiable processes of con-
solidation and retrieval by examining both potential 
points of action within the same RI paradigm as Ex-
periment 1. Using the Tower of Hanoi again as a target 
task, our hypotheses for Experiment 2 were as follows: 
1. Immediate forms of interference were ex-

pected to produce the greatest performance 
decline due to the learner’s inability to con-
solidate newly learned information (Brash-
ers-Krug et al., 1996; Friedman & Korman, 
2016). 

2. Delayed interference, acting directly before 
retrieval, was expected to have no perfor-
mance-inhibiting effects due to allowing 
consolidation to complete automation of the 
procedural task (Javadi et al., 2011).

3. Participants in the control group were ex-
pected to perform better than participants 
in any other condition when retested on the 
Tower of Hanoi.

Method
Participants
 One hundred and thirty-two participants (51 men, 
81 women; 18–30 years of age) were recruited via the 
university’s online research recruitment website and 
received research credit for their participation. Four 
participants were removed from the analysis due to not 
following the rules for completing the Tower of Hanoi 
puzzle, data from two more participants were removed 
due to incomplete data collection, and data from six 
more participants were removed due to their initial test 
completion time (s) being over three standard devia-
tions from the mean. Therefore, a total of 120 partici-
pants were included in the final analyses (see Table 2).
Materials 
 The same 4-disc Tower of Hanoi puzzle that was 
used in Experiment 1 was used in Experiment 2. In 



54

BIRKHOLZ ET AL.

the interference conditions, participants worked with 
ten different ring puzzles instead of eight. Completion 
times in seconds were recorded using a stopwatch.
Procedure
 The progression for Experiment 2 was similar to 
Experiment 1 with a few minor modifications. Each 
participant learned how to complete the 4-disc Tow-
er of Hanoi puzzle following the same procedure as 
in Experiment 1. Participants were then instructed to 
complete the Tower of Hanoi again, completing it as 
quickly as possible and in as few moves as possible. Out 
of view of the participant, the researcher recorded pre-
test completion time (s) and total number of moves. 
 Following the practice phase, participants were 
randomly assigned to complete one of the three condi-
tions. During a 13-min period, no interference partici-
pants wrote a detail-oriented description of the events 
of their morning. If completed before time expired, 
they were asked to describe their favorite location at 
the university. Participants in the immediate inter-
ference group solved as many ring puzzles as possible 
within 10-min immediately following the pre-test, 
then had a three-min waiting period. Participants in 
the delayed interference group waited three minutes 
after the pre-test, and then were instructed to solve as 
many ring puzzles as possible within 10 minutes. Ring 
puzzle instruction was the same as in Experiment 1. 
Immediately following the experimental phase, Tower 
of Hanoi’s performance was assessed again using the 
same method described for the pre-test assessment.

Results
 The pre-test number of moves between groups 
was examined to gauge similarity in levels of mastery 
across groups. Homogeneity of variance was violated 
(p = .001) but completion times appeared to be nor-
mally distributed and the achieved power was .999. 
A Kruskal-Wallis H test indicated the median pre-test 
number of moves did not differ across conditions, 
χ2(2) = 0.594, p = .743. Homogeneity of variance was 
also violated for pre-test completion times (p = .029) 
and non-parametric tests were used for all subsequent 
analyses. A Kruskal-Wallis H test suggested that nei-
ther pre-test, χ2(2) = 0.061, p = .970, nor post-test, 
χ2(2) = 0.150, p = .928, completion times differed 
across groups, meaning the groups performed the 
Tower of Hanoi similarly before and after any inter-
vention. Within-group performance between pre-test 

and post-test completion times was examined using a 
series of Wilcoxon signed-rank tests which suggested 
a significant difference within the Immediate Inter-
ference group (z = -2.197, p = .028, r = .571), with 
median post-test completion times (Mdn = 19) being 
faster than median pre-test completion times (Mdn 
= 21). All other comparisons were not significant.
 Exploratory analyses conducted after removing 
all participants whose pre-test completion times were 
over three standard deviations from the mean of Ex-
periment 1’s Before Interference completion times 
yielded the same overall result, except that no signifi-
cant difference was observed in the Immediate Inter-
ference group when comparing median pre-test com-
pletion times to median post-test completion times.

Experiment 2 Discussion
 Experiment 1 indicated procedural memory per-
formance can decline when RI tasks are introduced. 
Experiment 2 did not reveal the same findings when 
a three-min waiting period was added either imme-
diately after the pre-test or immediately before the 
post-test. Offline performance gains were observed 
within the Immediate Interference group while per-
formance did not change within the Control and 
Delayed Interference groups. These gains might be 
explained by offline practice, but previous research 
has only observed these gains within consolidation, 
suggesting that interfering with retrieval seems to, at 
least initially, cancel out these gains (Gagné & Cohen, 
2016; Javadi et al., 2011). This highlights the impor-
tance of work implicating retrieval as an important yet 
separate mechanism within procedural memory per-
formance and skill acquisition, suggesting that retriev-
al is less susceptible to RI than previously reported 
(Javadi et al., 2011). Experiment 2 suggests RI acting 
on the consolidation process apart from the retrieval 
process yields different results as compared to acting 
on both processes. However, another important fac-
tor was highlighted during the debriefing process.
 Many participants noted that the ring puzzles 
elicited frustration. Experiment 2 did not quantify 
emotion as a possible variable acting on performance, 
but feelings of frustration may have inadvertently en-
hanced RI within Experiment 1 as other experiments 
have shown (Flaisch et al., 2016; Rimmele et al., 2011; 
Weinreich et al., 2015). However, participants did 
not provide similar informal feedback after complet-



55

ASSESSING INTERFERENCE EFFECTS

ing Experiment 1. Experiment 2 may have also inad-
vertently introduced boredom or decreased motiva-
tion, factors that have been found to influence both 
learning and memory (Moore et al., 2014), although 
this is contrasted by research suggesting alertness 
does not impact procedural performance (Javadi et 
al., 2011). The mixed results warranted further re-
search to address why RI did not occur and to exam-
ine potential influences of emotion observed in pre-
vious research (Javadi et al., 2011; Steidl et al., 2006).

Experiment 3
 Previous research across memory types has im-
plicated emotion as a factor that moderates perfor-
mance (Flaisch et al., 2016; Javadi et al., 2011; LaBar & 
Phelps, 1998; Packard & Knowlton, 2002; Rimmele et 
al., 2011; Yang et al., 2011), with interventions rang-
ing from emotionally-valenced images or word lists 
and the receipt of an unexpected gift. However, the 
research discussed earlier suggests that affect induction 
has mixed results and the effects are observed as both PI 
and RI. Experiment 3 was designed to address the im-
plications of positive affect induction via receipt of an 
unexpected gift either before (PI) or after (RI) learning 
a novel procedural skill. We hypothesized the following: 
1. Positive affect such as joy or happiness was ex-

pected to improve test performance regardless 
of placement (Javadi et al., 2011; Yang et al., 
2011). 

2. Improvements in performance were expected 
to be accounted for by an improved ability to 
learn the task (Yang et al., 2011). 

3. Changes in alertness were not expected to im-
pact skill acquisition or retrieval (Javadi et al., 
2011).

Method
Participants
 Seventy-eight participants (33 men, 45 women; 
18-24 years of age) were recruited. Participants received 
General Psychology course credit and a $10 Amazon.
com gift card for participation. Data from two par-
ticipants were removed after the manipulation check 
analysis due to worsening completion times during 
practice. Data from one outlier was removed within 
the Delayed Gift group based on the first timed test 
immediately following the practice phase being greater 
than three standard deviations from me mean. Data 

from three more participants were removed due to in-
complete data collected, and therefore up to 72 partic-
ipants were included in the final analyses (see Table 3).
Materials
 The Tower of Hanoi was also used in Experi-
ment 3. However, participants learned the 3-disc pro-
cedure. A transfer task was added which utilized the 
4-disc procedure that was used in Experiments 1 and 
2. The Positive and Negative Affect Schedule Expand-
ed Form (PANAS; Watson & Clark, 1994) measured 
self-reported state affect during the experiment. Par-
ticipants rated to what extent they agreed with state-
ments with either positive or negative connotations. 
Higher scores on either positive affect words or neg-
ative affect words correspond to either higher positive 
affective tone or higher negative affective tone respec-
tively. Within the general dimension portion, 10 re-
sponses were coded as general positive affective words 
while 10 others were coded as general negative affec-
tive words. Positive and negative emotionally charged 
words were broken down further into subgroups and 
categorized to analyze these additional dependent 
variables: joviality, attentiveness, sadness, fatigue, and 
surprise. These subgroups were identified logical-
ly as pertinent to this study while other subgroups 
such as fear, hostility, and shyness were excluded.
Procedure
 Each condition’s specific procedural sequence is 
depicted in Figure 6. One control group first complet-
ed the PANAS. Next, these participants were taught 
how to complete the 3-disc Tower of Hanoi puzzle 
with verbal, written, and visual instructions. Written 
instructions were read aloud and given to each partic-
ipant briefly outlining the objective and rules of the 
task. Visual instructions were provided in the form 
of one researcher demonstration. After instruction, 
all participants were allowed five minutes to practice 
the Tower of Hanoi. The number of practice trials and 
successful completions during practice were recorded. 
Completing the puzzle or restarting marked the begin-
ning of a new practice trial. Initial test performance 
on the Tower of Hanoi puzzle was measured (s) out 
of sight of the participant. The total number of moves 
was not counted as participants were allowed more 
practice time, and this should only have increased 
puzzle mastery. Immediately following learning and 
initial testing participants read a psychology magazine 
for five minutes. Immediately following, participants 



56

BIRKHOLZ ET AL.

were retested on the Hanoi puzzle. Following the sec-
ond testing phase, transfer was tested using the 4-disc 
version of the Tower of Hanoi with no instruction. 
After the transfer measure, participants were award-
ed a $10.00 Amazon.com gift card. Another control 
group followed a similar process except they did not 
complete PANAS before learning the Tower of Ha-
noi. Instead, participants in this group completed the 
PANAS after learning instead of a five-minute waiting 
period. One experimental group followed the same 
process as the first control group except participants 
were awarded a $10.00 Amazon.com gift card be-
fore completing the PANAS. A second experimental 
group followed the same process as the second con-
trol group except participants were awarded a $10.00 
Amazon.com gift card before completing the PANAS.

Results
PANAS
 A series of 2 (Affect: positive, neutral) x 2 (Place-
ment: before learning, after learning) independent 
groups ANOVAs were used to examine the following 
dependent variables: General positive, general nega-
tive, joviality, attentiveness, sadness, fatigue, and sur-
prise. Homogeneity of variance was not violated for 
any of the affective variables and the distributions ap-
peared to be normal. The achieved power was not as 
high as in other analyses but was sufficient: .817. Re-
sults indicated a significant main effect of Placement 
on attentiveness, F(1, 71) = 6.441, p = .013, ηp

2 = .087 
(see Figure 7). On average, attentiveness was higher 
after learning (M = 14.971, SD = 3.339) than before 
learning (M = 13.216, SD = 2.583) free of the affective 
condition. No other main effects or interactions were 
significant.
Practice
 Each participant was required to complete at 
least two of the practice trials being analyzed for 
their data to be included in the practice trial anal-
yses. Five participants were excluded from all prac-
tice trial analyses (two from control group 1, two 
from control group 2, and one from experimental 
group 1), leaving up to 67 participants for analyses 
of the practice phase while achieving power = 1.0.
 A 2 (Affect) x 2 (Placement) x 2 (Practice: practice 
two, practice three) mixed ANOVA was conducted to 
examine completion time differences between practice 
trials and across conditions. Homogeneity of variance 

was not violated for either Practice Two completion 
time (p = .325) or Practice Three completion time (p 
= .077), and sphericity was assumed. Practice had a 
significant main effect on completion time, F(1, 58) 
= 5.189, p = .026, ηp

2 = .082. There was also a signif-
icant Affect x Practice interaction, F(1, 68) = 4.18, p 
= .040, ηp

2 = .071 (see Figure 9). No other main ef-
fects or interactions were significant. Simple compar-
isons were conducted to follow up on the significant 
interaction. Results indicated the positive groups’ 
times differed significantly from one practice trial 
to the other F(1, 60) = 10.90, p = .002, r = .39, with 
practice three (M = 16.469, SD = 5.486) being faster 
than practice two (M = 19.231, SD = 9.964; see Fig-
ure 8). No other simple comparisons were significant.
 A power function (y = kxn; r = .635, SD = .233) 
and a quartic function (y = ax4 + bx3 + cx2 + dx + e; 
r = .753, SD = .166) were calculated for each partic-
ipant’s practice period, and the quartic function was 
determined to have a better-fit coefficient. A 2 (Affect) 
x 2 (Placement) ANOVA was conducted as a precau-
tion to ensure function fit was not different across 
conditions, resulting in no significant main effects or 
interaction. The derivative of each quartic equation 
was taken and solved at the points equal to the second, 
third, and fourth practice trial times. These derivatives 
gave the rate of change for each participant’s power 
curve at each point. The rates of change were analyzed 
using a 3 (Practice: practice two, practice three, prac-
tice four) x 2 (Affect) x 2 (Placement) mixed ANOVA 
to examine changes in completion time (s). Homoge-
neity of variance was not violated within practice two 
(p = .095), practice three (p = .094), or practice four 
(p = .092). The main effect of Practice, F(2, 126) = 
10.311, p < .001, ηp

2 = 0.141, on rate of change was 
significant. Pairwise comparisons for the main effect of 
Practice indicated changes in completion time differed 
between practice two and practice three (p = .006), 
practice two and practice four (p = .006), and practice 
three and practice four (p = .007). Respectively prac-
tice two completion times changed fastest (M = 0.577, 
SD = 0.1.525), then practice three (M = 0.378, SD = 
1.015), and practice four (M = 0.280, SD = 0.761). 
No other main effects or interactions were significant.
 Finally, a 2 (Affect) x 2 (Placement) indepen-
dent groups ANOVA was used to examine poten-
tial differences in the number of attempted practice 
trials between groups. Unsuccessful trials were in-



57

ASSESSING INTERFERENCE EFFECTS

cluded in the analysis. Homogeneity of variance was 
not violated (p = .706), and neither the main effect 
of Affect nor Placement on the number of attempt-
ed practice trials was significant. In addition, the 
Affect x Placement interaction was not significant.

Test and Transfer
 A 2 (Affect) x 2 (Placement) x 2 (Timed Trial: first 
test, second test) mixed ANOVA was used to examine 
differences in performance between conditions and 
across timed trials. Homogeneity of variance was not 
violated for Timed Trial completion times (p = .947), 
and achieved power was 1.0. There was a significant 
main effect of Placement, F(1, 68) = 4.339, p = .041, 
ηp

2 = 0.060, with completion of the PANAS before 
learning resulting in slower average test completion 
times (M = 7.740, SD = 1.608) than when the PANAS 
was completed after learning the Tower of Hanoi (M 
= 6.996, SD = 1.579) regardless of affective condi-
tion. No other main effects or interactions were sig-
nificant. The main effect of Placement was explored 
further using a series of independent sample t-tests 
comparing the first and the second test completion 
times based on PANAS placement being either be-
fore or after learning, which indicated the significant 
main effect was due to a difference in the second test 
completion times, t(70) = 2.100, p = .039, d = .495, 
with later PANAS placement resulting in faster com-
pletion times (M = 7.021, SD = 1.509) than early 
PANAS placement (M = 7.773, SD = 1.529). No dif-
ference arose between the first test completion times.
A 2 (Affect) x 2 (Placement) independent groups  
ANOVA was used to examine the dependent variable 
of transfer time. Homogeneity of variance was not vi-
olated (p = .369), and there were no significant effects.

Experiment 3 Discussion
 Previous research has used an unexpected gift of 
candy to induce a higher momentary positive affect be-
fore completing a task (Yang et al., 2011). In this study, 
a $10 gift card was used. It appears that the manipu-
lation failed to produce the desired effects but there 
were notable changes in attentiveness. However, these 
changes are limited to after learning how to complete 
the Tower of Hanoi. This suggests that the interven-
tion did not have a significant impact on attentiveness, 
but instead simply engaging in learning a novel puzzle 
might have caused the increase. In turn, the improve-

ments observed across practice trials between the posi-
tive and neutral affective groups might be attributable 
to non-significant differences in initial practice perfor-
mance. This post hoc explanation is supported by the 
evidence suggesting that no group exhibited greater 
practice trial-to-practice trial performance changes. 
Therefore, the affective results of this study are large-
ly inconclusive. That being true, it appears that the 
PANAS placement between the first and second tests 
may have facilitated performance in some way, but the 
extent and specific mechanisms of this influence are 
also unclear. Granted, all groups were able to master the 
3-disc version of the puzzle, but transfer performance 
may have been better if a variable training method was 
used (Vakil & Heled, 2016). Overall, the changes in at-
tentiveness are particularly interesting and will be cov-
ered in greater detail within the General Discussion.

General Discussion
 This series of experiments had three main objec-
tives: (a) Replicating existing literature demonstrating 
the impact of retroactive interference (RI) on proce-
dural learning and performance, (b) clarifying the sig-
nificance of consolidation and recall processes within 
procedural paradigms, and (c) exploring the influence 
of unexpected rewards on procedural task acquisition 
and performance. Experiment 1 replicated prior re-
search on RI in procedural memory using the Tower 
of Hanoi task and various puzzles. Our first hypothe-
sis was supported that both interference groups would 
perform worse than the control group. The amount 
of interference in the peg and ring groups was similar 
when participants were retested on the Tower of Hanoi, 
which was contrary to our second hypothesis. Howev-
er, Experiment 1 did not differentiate between consol-
idation and retrieval processes. Experiment 2 aimed to 
clarify the impact of interference on the consolidation 
and retrieval processes in procedural memory perfor-
mance. We hypothesized that immediate interference 
would lead to the largest performance decline, while 
delayed interference would have no effect. However, 
the results were not consistent with that hypothesis. 
We observed that emotions such as frustration and 
boredom might have influenced performance, which 
led to conducting Experiment 3. Experiment 3 did not 
yield the expected effects, though the interpretation 
of the results paralleled that of Experiment 2, except 
for the intriguing differences in alertness observed 



58

BIRKHOLZ ET AL.

before and after learning the Tower of Hanoi puzzle.
Affect Induction 
 Previous research has found that we can in-
duce different affective states using various meth-
ods (Flaisch et al., 2016; Javadi et al., 2011; LaBar & 
Phelps, 1998; Packard & Knowlton, 2002; Rimmele 
et al., 2011; Yang et al., 2011). While Experiment 3 
utilized an intervention based on previous work, we 
assumed that participant affect would be impacted 
by the surprise receipt of a $10 gift as compared to a 
small piece of candy (Yang et al., 2011). Given the re-
sults, we must acknowledge that there may be a rea-
son why this particular intervention is not common-
ly used or reported (Zhang et al., 2014). This may 
explain why the methods used in Experiment 3 did 
not produce a clear positive and neutral dichotomy. 
 Future replication of Experiment 3 should use a 
different method to change participant affective tone. 
Zhang et al. (2014) tested four different commonly 
used affect induction procedures (recall with music, 
guided imagery, visual images with music, and embod-
iment) and found that all are effective in inducing both 
pleasant and unpleasant affective changes. However, 
some procedures are more effective than others. View-
ing evocative photographs while listening to music 
and recalling an affectively salient event while listening 
to music were the most effective in inducing a pleasant 
affective tone, while viewing evocative photographs 
while listening to music was the most effective in in-
ducing unpleasant affect. Overall, these results suggest 
that combining evocative images with music is a pow-
erful way to manipulate affective states, while all four 
methods are equally effective in modifying arousal. Us-
ing these methods before learning the Tower of Hanoi, 
or imposing an effective strategy post-learning, might 
increase the likelihood of achieving the desired effect. 
This would provide further insight into if the placement 
of emotionally-valenced interference impacts various 
stages of procedural skill acquisition and performance.
Alertness and Procedural Memory
 Previous research found that alertness was not a 
factor in procedural performance changes (Javadi et 
al., 2011). However, the definition of alertness mat-
ters. Previous literature defines ‘alert’ or ‘alertness’ in 
many ways, but we believe the following definition, 
modified and adapted from Oken et al. (2006) and 
Shapiro et al. (2006), is both recurrent in the literature 
and appropriate for this discussion. Alertness refers 

to a heightened state of readiness or vigilance corre-
sponding to the ability to maintain focus and atten-
tion on a task or situation. Javadi et al. (2006) used a 
self-report questionnaire and a finger-tapping task to 
measure alertness, whereas in Experiment 3, we used 
the PANAS. Another main difference is that in Exper-
iment 3, we tracked changes in performance across the 
acquisition stage. This allowed us to determine what 
mechanisms might be driving overall performance dif-
ferences if they arose. The differences in the results of 
Experiment 3 and those reported by Javadi et al. (2011) 
warrant further exploration into how the construct of 
alertness interacts with procedural skill acquisition.
 In Experiment 3 we observed that alertness ap-
peared to increase after participants’ engagement in 
learning how to complete the Tower of Hanoi. We 
cannot attribute these changes to the monetary in-
tervention, and therefore conclude that there is some 
other relationship between alertness and learning a 
procedural skill. This brings us back to the definition 
of alertness, and how previous research has linked it 
to changes in performance. Much of the early research 
exploring the role of alertness on memory defined 
alertness as needing sleep or not (Aguirre et al., 1985; 
Gorissen et al., 1997; Rogers & Rosenberg, 1990). 
However, contemporary research has expanded our 
understanding of alertness to include momentary 
fluctuations that influence both attentional control 
and memory processes (deBettencourt et al., 2018, 
2019; Keene et al., 2022). We also better understand 
the neuroanatomical structures responsible for mod-
ulating alertness (Ross & Van Bockstaele, 2021; Van 
Egroo et al., 2022). However, there are still gaps in 
our understanding of the results of Experiment 3.
 To date, there appears to be little or no research 
that systematically examines the influence of alert-
ness on procedural memory processes. However, we 
might be able to glean some insight from other mem-
ory domains such as long-term memory encoding and 
working memory. Within these systems, vigilance, 
or the ability to maintain focus on a given task, can 
be measured using response time and pupillometry. 
Faster response times in decision-making tasks and 
larger pupil size compared to an individual’s baseline 
are predictive of errors. In turn, errors suggest that 
not enough attentional resources are being allocated 
to the task. To clarify the relationship between vigi-
lance and working memory, Adam et al. (2015) used 



59

ASSESSING INTERFERENCE EFFECTS

the whole report change detection paradigm. Partici-
pants were presented with a memory display, followed 
by a test array, and had to indicate whether it was the 
same or different. Instead of the standard same/dif-
ferent response, participants were presented with a 3 
x 3 matrix of colors and had to select the individual 
color that appeared at the same location as in the orig-
inal display. The researchers used a lapse model and an 
attentional control model to explain fluctuations in 
performance and found that the attentional control 
model best explained working memory performance. 
These findings suggest that attention lapses contribute 
to individual differences in working memory capac-
ity. Further evidence to support an attentional con-
trol explanation was reported by deBettencourt et al. 
(2019). Participants completed a task in which they 
had to identify if an array consisted of colored circles 
or squares by pressing a button. The circles appeared 
more frequently than the squares, causing errors to 
occur when participants had to switch to identify-
ing the squares. To measure the relationship between 
vigilance and working memory, a whole-report color 
task was added to the task at random intervals. Results 
showed that attention lapses, identified by faster reac-
tion times, were related to errors in working memory. 
 Similar observations are made in long-term mem-
ory. deBettencourt et al. (2018) had participants com-
plete a task where they identified indoor or outdoor 
scenes and then performed a recognition memory test 
with 200 images. Sustained attention was measured 
using the average reaction time over the previous three 
trials and was found to predict memory performance. 
Infrequent images preceded by faster reaction times 
in the initial decision-making task were less likely to 
be remembered in the surprise long-term recognition 
memory task than those preceded by slower reaction 
times. This suggests that an individual’s level of vig-
ilance during encoding affects which memories are 
formed. These recent studies might also give us insight 
into the results from Experiment 3, and at least give 
us an idea of why increases in alertness appear to co-
incide with procedural skill acquisition. When alert, 
individuals are more attentive and able to process in-
formation more efficiently, which can lead to better 
retention and retrieval of information. Additionally, 
alertness can lead to increased motivation (Neigel et 
al., 2017), which may encourage individuals to en-
gage in more deliberate and focused practice, leading 

to improved skill acquisition. Furthermore, alertness 
can increase the capacity for mental flexibility and 
problem-solving (Greenberger et al., 1971; Ren et al., 
2011), allowing individuals to adapt their strategies 
and approaches to the task at hand. However, we can-
not rule out the possibility that simply engaging in a 
cognitively demanding process, such as procedural 
skill learning, might inherently increase attentiveness.
Conclusion
 Collectively, these experiments offer mixed support 
for our hypotheses, emphasizing the need for further 
research employing diverse methods to induce affective 
tone. Such studies can shed more light on the impact 
of emotionally-valenced interference at various stages 
of procedural skill acquisition and performance. Addi-
tionally, these experiments underscore the importance 
of replication in psychology research and highlight the 
replication crisis, which pertains to the challenges of 
reproducing published research findings, especially in 
fields like psychology and other social sciences. Repli-
cation promotes transparency, openness, and research 
reproducibility, facilitating systematic progress in our 
understanding of the subject, rather than leaving gaps 
in the literature, as is currently the case with our limit-
ed understanding of alertness in procedural memory.

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Table 1

Descriptive Statistics for Experiment 1

Note. This table displays the descriptive statistics of the final data used in Experiment 1, after initial data removals, 

and separated by condition.

* Significant differences between mean completion times measured before and after respective condition tasks as 

indicated by the simple effects analysis (p < .001).



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Table 2

Descriptive Statistics for Experiment 2

Note. This table displays the descriptive statistics of the final data used in Experiment 2, after initial data removals, 

and separated by condition.

* Significant differences between median completion times measured before and after respective condition tasks as 

indicated by the Mann-Whitney U test (p < .05).



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Table 3

Descriptive Statistics for Experiment 3

Note. This table displays the descriptive statistics of the final data used in each Experiment 3 analysis, after initial 

data removals, and separated by condition. PANAS = positive and negative affect schedule; CT = completion time 

(s); NM = total number of moves.
a Attentiveness, as measured by the PANAS, was higher in the Delayed PANAS conditions compared to the Im-

mediate PANAS conditions (p < .05).
b CT of practice trials two and three were different within the Positive groups (p < .005).
c The rate of change was significantly different across practice trials two, three, and four (p < .001).
d Second test CTs significantly differed between the Immediate and Delayed PANAS groups (p <.05).



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Figure 1

Tower of Hanoi Puzzle

Note. The Tower of Hanoi is a wooden puzzle that involves moving a stack of discs, one at a time, from a starting 

peg (the left peg in this image) to a target peg (the right peg in this image). There are specific rules to follow: only 

one disc can be moved at a time, and a larger disc cannot be placed on top of a smaller one. To complete the tower 

with four discs, it takes a minimum of 15 moves. The first step is to place the smallest disc on the middle peg (see 

Karwath, 2005). The rules determine this choice. The next move is to put the smallest disc on the right peg, which 

creates space for moving the second largest disc to the middle peg. After building a three-disc tower on the middle 

peg, it becomes possible to move the largest disc to the target peg on the right. Then, participants can rebuild the 

tower on the target peg.



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Figure 2

Ring Puzzles

Note. A ring puzzle is typically a metal piece bent into a ring-like shape and linked with another piece. They are 

solved by twisting, sliding, or pulling the pieces apart.



6868

Figure 3

Peg Puzzles

Note. The left panel shows a peg puzzle requiring all pegs to switch sides. The center panel illustrates an elimina-

tion peg puzzle involving the removal of pegs from play by jumping one over another to an open spot. The right 

panel exhibits a peg puzzle requiring all holes but one to be filled by starting in any position and then tracing 

preset lines between holes. 

BIRKHOLZ ET AL.



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Figure 4

Animated Procedure for Solving the Tower of Hanoi

Note. Three slides from the digital .gif designed by Karwath (2005) illustrate an animated procedure for copleting 

the Tower of Hanoi puzzle with 4 discs.

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Note. Experiment 1 Tower of Hanoi completion time (s) before and after interference in the control, ring puzzle, 

and peg puzzle groups. Error bars denote one standard error around each mean.

Figure 5

Tower of Hanoi Completion Times Before and After Interference



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Figure 6

Procedural Sequences in Experiment 3

Note. Experiment 3 procedures for each group respectively highlight differences in placement and affective tone. 

C = control; E = experimental; PANAS = positive and negative affect schedule expanded form.



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Figure 7

Attentiveness Before and After Learning the Tower of Hanoi

Note. Experiment 3 self-reported attentiveness measured before and after learning the Tower of Hanoi. Error bars 

denote one standard error around each mean.



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Figure 8

Tower of Hanoi Completion Times Before and After Affect Induction

Note. Experiment 3 practice trial completion time measured at practice two and practice three, separated by affec-

tive condition. Error bars denote one standard error around each mean.




