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An experimental test on the causal effect of moral self-concept on university students’ cheating behavior – pre-registration of a study design
Last registered on April 28, 2021

Pre-Trial

Trial Information
General Information
Title
An experimental test on the causal effect of moral self-concept on university students’ cheating behavior – pre-registration of a study design
RCT ID
AEARCTR-0007613
Initial registration date
April 27, 2021
Last updated
April 28, 2021 10:31 AM EDT
Location(s)

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Primary Investigator
Affiliation
Research Center for Educational and Network Studies, Hungarian Academy of Sciences, Centre for Social Sciences; TÁRKI Social Research Institute, Budapest
Other Primary Investigator(s)
Additional Trial Information
Status
In development
Start date
2021-05-06
End date
2021-12-31
Secondary IDs
Abstract
We pre-register a large-scale experiment to test the direct causal effect of moral self-concept on fraudulent behavior (cheating). We follow the theoretical considerations of self-concept maintenance theory [SCMT], which describes mechanisms that allow people to enjoy the benefits of cheating and still maintain a positive self-concept. Following the logic of SCMT’s attention-to-standards mechanism, we hypothesize that if people are mindful of their moral standards, they cheat less since cheating triggers downgrading of people’s moral self-concept, which they aim to avoid. We will measure students’ cheating using the die-under-the-cup task. We employ a narrow definition of moral self-concept, which rests on the self-reported honesty that we externally induce by a random intervention. Our light-touch pre-tested intervention consists of an affirmation message that empowers students’ moral self-concept. Under the assumption that the intervention affects the outcome only via self-concept, we interpret the intervention as an instrumental variable for the causal effect of self-reported honesty. Therefore, we can directly test the hypothesized negative causal effect between self-concept and cheating that prior research has assessed through indirect and non-causal mediation analysis. Confirmed hypotheses will indicate that moral self-concept has a direct negative effect on cheating. Falsified hypotheses will suggest that our narrowly defined, externally induced, and self-reported moral self-concept does not prevent people from cheating. Thus, researchers should find out different experimental settings to explore the causal effect of moral self-concept on fraudulent behavior within the framework of SCMT.
External Link(s)
Registration Citation
Citation
Keller, Tamas. 2021. "An experimental test on the causal effect of moral self-concept on university students’ cheating behavior – pre-registration of a study design." AEA RCT Registry. April 28. https://doi.org/10.1257/rct.7613-1.0.
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Experimental Details
Interventions
Intervention(s)
Half of the students are randomly assigned to the treated group based on the value of a random number. The remaining half of the students are assigned to the control group.
We manipulate students’ moral self-concept through positive affirmation messages that empower students’ honesty with a language praising and acknowledging students’ honesty. Treated students receive the affirmation message, and control students do not.
Intervention Start Date
2021-05-06
Intervention End Date
2021-06-30
Primary Outcomes
Primary Outcomes (end points)
Students' engagement in fraudulent behavior (cheating)
Primary Outcomes (explanation)
We tempt students to cheat by using the die-under-the-cup task (Fischbacher & Föllmi-Heusi, 2013), in which people roll a standard, six-sided dice in private and report the rolled number. The task will be monetarily incentivized. People’s pay-off (in our experiment, the chance of winning) depends on the rolled number. Therefore, participants are incentivized to report large numbers. Since people roll in private, researchers cannot reveal individual cheating behavior, which circumstance provides a secure environment for developing dishonest behavior.
The reported number corresponds to points. For example, if a student reports 1, she earns 0 points in that round. If she reports 6, she earns 5 points.
The outcome variable (Y) equals the sum of the points collected throughout the ten rounds of dice rolling. Thus, the outcome variable ranges between 0 and 50. One unit of Y equals a one percentage point increase in the chance of taking part in the lottery. We treat the outcome variable as a scale.
We will infer cheating from the sum of the collected points under the assumption that a larger sum signals more cheating. We assume that students will deliberately misreport the numbers they roll to secure a larger chance of winning.
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The experimental setting contains the following four steps:

1. random manipulation of moral self-concept [self-reported honesty]
2. measuring self-reported honesty
3. making moral standards accessible to people by strengthening the link between self-concept and cheating
4. tempting students and measuring their engagement with fraudulent behavior

We provide a direct test of how self-concept affects cheating. By doing so, we provide an experimental random manipulation (treatment) of people’s self-concept. We interpret the randomized treatment as an instrument that affects cheating via self-concept. Thus, based on some recent work (Sobel, 2008), we turn to instrumental variable estimation to investigate self-concept maintenance as a causal mechanism that affects cheating.
Experimental Design Details
Not available
Randomization Method
based on the value of a random number
Randomization Unit
University students
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
3000 students
Sample size: planned number of observations
3000 students
Sample size (or number of clusters) by treatment arms
approximately 1500 treated and 1500 control students
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We calculate the power using the program Optimal Design (Spybrook et al., 2011). The calculated minimum detectable Cohen’s d effect size for the p-value of 0.05 (one-sided test) and sample size of 3,000 is 0.09. Thus, our design has 80% power to detect substantially small effects.
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Research Ethics Committee, ELKH Centre for Social Research
IRB Approval Date
2021-04-06
IRB Approval Number
N/A
Analysis Plan

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