Predicting Academic Dishonesty Based on Competitive Orientation and Motivation: Do Learning Modes Matter?

Predicting Academic Dishonesty Based on Competitive Orientation and Motivation: Do Learning Modes Matter?

Автор: Hanif Akhtar, Retno Firdiyanti

Журнал: International Journal of Cognitive Research in Science, Engineering and Education @ijcrsee

Рубрика: Original research

Статья в выпуске: 3 vol.11, 2023 года.

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Previous studies suggest that competition and motivation are reliable predictors of academic dishonesty. However, little is known about the role of situational factors in predicting academic dishonesty. Some studies have found that online learning is more prone to academic dishonesty, but others have found the opposite. This study focuses on academic dishonesty, how it relates to competitive orientation and motivation, and how that differs in two class modes (online vs offline). This study was conducted in Indonesia during early 2022, transitioning from online learning due to the Covid-19 pandemic to normal-offline learning. A total of 404 university students participated in this study. Most participants (74.2%) reported they cheated more frequently in online than in offline learning. The independent sample t-test indicated that students in the online learning group showed higher academic dishonesty than students in the offline learning group. Latent regression analysis showed that amotivation, hypercompetitive orientation, and learning mode are significant predictors of academic dishonesty. These findings imply that transitioning from offline to online learning during the pandemic negatively affected academic integrity.

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Academic dishonesty, hyper-competition, motivation, online learning

Короткий адрес: https://sciup.org/170200020

IDR: 170200020   |   DOI: 10.23947/2334-8496-2023-11-3-439-447

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