Cognitive and emotional predictors for a decision to support academic integrity standards in interaction with fellow students: “traditional” vs “electronic” academic deception in the student environment
DOI:
https://doi.org/10.33910/2686-9527-2023-5-1-6-23Keywords:
academic deception, students, standards of academic integrity, decision-making, emotions, beliefs, “electronic” academic deceptionAbstract
Introduction. Academic dishonesty is quite common among students, and it has become even more common with the introduction of distance learning, as the use of the internet contributes to the spread of “electronic” forms of academic deception. This article identifies cognitive and emotional predictors for students’ decision to support academic integrity standards when faced with “traditional” and “electronic” academic deception used by their classmates.
Materials and Methods. The study involved 304 students of Russian universities aged 18–25 (19.30±1.59 years, 52.6% female). Empirical data were collected using vignettes which allowed to assess the probability and subjective acceptability of behavior aimed at supporting academic integrity standards in situations of known “traditional” and “electronic” academic dishonesty of classmates. The method also makes it possible to assess the degree of emotional response to academic dishonesty (anger, anxiety), as well as the degree of beliefs about normativity of academic deception and academic integrity.
Results. The participants demonstrated a low readiness to support academic integrity standards in situations of “traditional” and “electronic” academic dishonesty of their classmates. The cognitive and emotional prerequisites for this decision are more consistent insofar as the “traditional” academic deception is concerned, while they are inconsistent in respect of the “electronic” academic deception. Emotional predictors make the most significant contribution to the decision to support the standards of academic integrity in the situation of “traditional” academic dishonesty, whereas in the situation of “electronic” academic deception both cognitive and emotional predictors are important.
Conclusions. The research results can be used in developing programs aimed at promoting academic integrity practices among students. Future research may include a wider range of “traditional” and “electronic” academic deception situations encountered in the student environment, as well as a wider range of vignettes with behavioral models that ensure the support of academic integrity standards.
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Tayan, B. M. (2017) Academic Misconduct: An investigation into male students’ perceptions, experiences & attitudes towards cheating and plagiarism in a middle eastern university context. Journal of Education and Learning, vol. 6, no. 1, pp. 158–166.
Tindall, I. K., Fu, K. W., Tremayne, K., Curtis, G. J. (2021) Can negative emotions increase students’ plagiarism and cheating? International Journal for Educational Integrity, vol. 17, article 25. https://doi.org/10.1007/s40979-021-00093-7
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Vasileva, S., Miklyaeva, A., Tikhomirov, A. (2021) Motivational background of the attitudes to academic cheating with the use of the internet resources. In: T. Noskova, X. Piotrowska (eds.). CEUR Workshop Proceedings. Series 16. “NESinMIS 2021—Proceedings of the 16th International Conference ‘New Educational Strategies in Modern Information Space’ ”. Saint Petersburg: [s. n.]. [Online]. Available at: https://ceur-ws.org/Vol-2920/paper_13.pdf (accessed 17.09.2022).
Vehvilainen, S., Lofstrom, E., Nevgi, A. (2018) Dealing with plagiarism in the academic community: Emotional engagement and moral distress. Higher Education, vol. 75, no. 1, pp. 1–18. https://doi.org/10.1007/s10734-017-0112-6
Walzer, T., Dahl, A. (2022) The moral puzzle of academic cheating: Perceptions, evaluations and decisions. In: D. A. Rettinger, T. B. Gallant (eds.). Cheating academic integrity: Lessons from 30 years of research. London: Jossey-Bass Publ. [Online]. Available at: https://people.ucsc.edu/~audahl/pub/WaltzerDahl(inpress)The%20moral%20puzzle%20of%20academic%20cheating.pdf (accessed 17.09.2022).
Winship, C., Mare, R. D. (1984) Regression models with ordinal variables. American Sociological Review, vol. 49, no. 4, pp. 512–525. https://doi.org/10.2307/2095465
Zhao, L., Mao, H., Compton, B. J. et al. (2022) Academic dishonesty and its relations to peer cheating and culture: A meta-analysis of the perceived peer cheating effect. Educational Research Review, vol. 36, no. 7, article 100455. https://doi.org/10.1016/j.edurev.2022.100455
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Zhao, L., Mao, H., Compton, B. J. et al. (2022) Academic dishonesty and its relations to peer cheating and culture: A meta-analysis of the perceived peer cheating effect. Educational Research Review, vol. 36, no. 7, article 100455. https://doi.org/10.1016/j.edurev.2022.100455 (In English)
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