Examining the relationship between student attitude and academic cheating

ABSTRACT

Academic cheating has long been persistent and pervasive on college campuses. Informed by the theory of planned behavior (TPB), we studied how factors collectively influence academic cheating among undergraduate students. Consistent with prior research, we found a lack of self-control, attitude toward academic misconduct, subjective norm, and perceived behavioral control relates to college student engagement in academic cheating. Notably, we found that attitude toward academic cheating not only directly relates to student academic cheating but mediates the relationship between lack of self-control and student academic cheating. Given that the attitude toward academic cheating is malleable, such findings have important implications for reducing academic misconduct among college students.

KEYWORDS:

• Lack of self-control
• attitude
• mediation
• academic cheating

ACKNOWLEDGMENTS

The authors would like to thank Templeton World Charity Foundation (TWCF) for their funding support. We appreciate Gallup organization for survey administration and data collection activities. And we are grateful for two anonymous reviewers who offer insightful comments and feedback.

DISCLOSURE STATEMENT

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be considered as a potential conflict of interest.

DATA STATEMENT

Authors agree to make dataset supporting the results or analyses presented in the paper available upon reasonable request.

Notes

¹ Due to the limited number of items assessing attitude and perceived behavioral control, we suggest readers interpret the research findings with caution.

² McDonald’s omega (ω) is a better alternative relative to Cronbach alpha (α). The latter assumes tau-equivalence (e.g., every indicator contributes equally to the factor see Trizano-Hermosilla & Alvarado, 2016). If the assumption is violated, the true reliability will be underestimated. McDonald’s omega (ω) on the other hand, does not require such assumption and is more appropriate in applied research studies (Dunn et al., 2014).

³ Maximum likelihood parameter estimates with standard errors and a mean- and variance-adjusted chi-square test statistic that are robust to non-normality.

⁴ Chi-square different test was also performed c² =30.064 DF=2 p=.0000. Yet it should be noted that Chi-square difference tests applied to nested models are directly affected by sample size. For large samples, even trivial differences might make Chi-square difference significant (Werner & Schermelleh-Engel, 2010).

Additional information

Funding

This work was supported by a grant (No. 0060) from Templeton World Charity Foundation (TWCF). TWCF has no further role in study design, in the data collection and analysis, writing of the manuscript, or decision to submit it for publication.