Replication of “Decision Making and the Avoidance of Cognitive Demand”
Kool, W., McGuire, J., Rosen, Z., Botvinick, M.
Veronica Laughlin, Jenny Davis, Lara Anderson, Kameron Mikesell, Eliza Anatsui, Shayla Miller, and Hunter Hamblin
INTRODUCTION
We are doing a replication of Kool, McGuire, Rosen, and Botvinick’s
(2010) study, “Decision Making and the Avoidance of Cognitive Demand.” The original researchers of the study looked at the behavioral
and economic theories that have shown that people’s actions are reflected in how much energy they exert and through their unconscious
choices of how much work is required of them. The researchers refer
to this principle as the law of less work where people will take the
path of least resistance (Hull, 1943). The research that they have
looked at supports physical exertion and the researchers wanted to
look at the law of less work when paired with cognitive demand.
Kool et al. (2010) contended that physical exertion and the exertion of
thinking are one in the same. People are cognitive misers and dislike
exerting mental effort. There are costs when one exerts mental effort
such as time and energy. Based on the research, people do not actively seek out cognitive demanding tasks. The researchers’ hypothesis is that people will exert less effort in a task that requires both low
and high cognitive demand and they expected the participants to
show a consistent bias with both high and low cognitive demands.
HYPOTHESES
1. Participants showing a preference for a task that requires less cognitive demand will consistently show preference for the low-demand
tasks.
2. Participants with location-related preferences for cues will not consistently favor either low or high cognitive demand tasks when the location is unpredictable.
METHODS
Participants
Prior to data collection, we were planning to reach 37 participants for
our study in an effort to replicate the original study as closely as possible. Our recruitment efforts enabled us to reach 29 participants from
Brigham Young University-Idaho in total. Participants were recruited
from general psychology classes and a few upper division psychology
classes. For some students, course credit was offered by psychology
professors as an incentive. We also provided cookies at the study.
Materials
Materials for the study included computers running Windows 10,
along with the computer software MATLAB and the program Psychtoolbox. We also had a consent form and instruction sheet. All required materials for these programs are accessible via the following
link: https://osf.io/rcaud/. A copy of the participant instructional script is
also available. Lastly, a debriefing questionnaire was used at the
close of each participant’s session.
METHODS CONTINUED
Procedure
Using an online scheduling tool, participants signed up for 45 minute
slots to participate in the study. We collected data from one to two participants at a time in the same room. Upon arrival, participants signed
in with their names and professors so that we could report their participation to their professors for credit. We got their consent, gave them
instructions, and answered any questions that they may have had. We
gave instruction sheets to the participants to refer to during the practice rounds of the experiment. Afterwards, the real experiment began
and the computer screen presented each participant with a trial of two
diagonally placed abstract color patch cues, from which the participants had to choose by going to the white dot in the center, and then
hovering over one cue with the mouse.
Once a cue was chosen, it revealed a blue or yellow colored number
between one and nine, except the number five. If the number was
blue, the participant had to indicate whether the number was ‘less than
five’ by clicking the left mouse button. If the blue number was ‘not less
than five’, the participant had to indicate so by clicking the right mouse
button. If the number was yellow, the participant had to indicate whether the number was ‘even’ by clicking the right mouse button, and clicking the left mouse button if the number was ‘not even’. The program
registered the participants’ response times and moved the cue positions. The participants repeated this trial eight times, amounting to one
session. Each participant completed a total of 75 sessions. We then
presented each participant with a debriefing questionnaire to assess
the choices that they made and why. We notified the participants of the
true purpose of the experiment, thanked them, and dismissed them.
RESULTS
Data Collection —The data collection process yielded 29 participants.
Of the 29 participants, one participant was excluded for explicitly stating the use of patterns, such as switching evenly between the two
cues (N = 28).
Task performance—Mean accuracy of number judgments was 0.952
(0.016) for the low-demand alternative and 0.934 (0.017) for the highdemand alternative, and the difference between these rates are significant (signed-rank, p = 0.002 ). Target keypress RTs for task switch and
task repetition were analyzed in a two-way repeated measures ANOVA. These results revealed a significant main effect of the alternative
chosen (high-demand vs. low-demand; F(1,27) = 4.445, p < 0.05), a
main effect of task switch vs. repetition (F(1,27) = 58.054, p < 0.001),
and a significant interaction between the two (F(1,27) = 19.73, p <
0.001).
RESULTS CONTINUED
Demand selection—The mean rate of low-demand selections was
0.64; these results did not vary significantly from 0.50 (Wilcoxon
signed-rank p = 0.066). It reveals that individual subjects’ responses
ranged mainly from indifference to aversion toward high demand; no
participants showed an extreme rate of bias in the high-demand direction.
DISCUSSION
In this replication study we found many similarities to the original research done by Kool, but we also found differences. The participant
reaction times in our study for the low demand cues were lower than
those for the high demand cues. The reaction times were also lower
for cues that used more repetition than for cues which switched up
tasks more often. This was similar to the findings in Kool’s original research and validates the idea that tasks which use less cognitive demand will take less time. Unfortunately we found a difference between
our replication research and Kool’s original research in regards to the
idea that people will prefer completing easier tasks over harder tasks.
Our study did not show any significance for the mean rate of low demand selection, meaning that we failed to reject the null of our hypothesis. The participants did not show a preference for the low cognitive demand choices which does not support the law of less work.
A few things we suggest future studies consider is to make the cues
more uniform with simpler colors because we had quite a few participants choose cues based on irrelevant factors like which color they
liked best or which cues were easier to read. Future studies should also be more clear to participants about not following a pattern when
choosing between cues. Despite the fact that we failed to reject the
null regarding the law of less work in our study, we believe we were a
major factor in understanding human behavior and cognition. Further
research in this area could help the field of psychology better understand human motivation and why we do the things we do.
ACKNOWLEDGMENTS
We would like to thank Dr. Brady Wiggins for his help and guidance
in completing this replication study. We would also like to thank the
Collaborative Replications and Education Project for reviewing and
approving our study.