Academic cheating is common, but little is known about its early emergence. It was examined among Chinese second to sixth graders (N = 2094; 53% boys, collected between 2018 and 2019) using a machine learning approach. Overall, 25.74% reported having cheated, which was predicted by the best machine learning algorithm (Random Forest) at a mean…

Prevalence of contract cheating and outsourcing through organised methods has received interest in research studies aiming to determine the most suitable strategies to reduce the problem. Few studies have presented an international approach or tested which variables could be correlated with contract cheating. As a result, strategies to reduce…

Dishonest academic behavior (DAB) by students in Chinese higher education institutions has become a significant concern. However, the related study of academic dishonesty in mainland China is very limited. This study fills this gap by examining the theory of planned behavior and its three extended versions, validating the effectiveness of…

In prior studies, academic procrastination has been discussed as an influencing factor of academic misconduct. However, empirical studies were conducted solely cross-sectionally and investigated only a few forms of academic misconduct. This large scale web-based study examined the responses of between 1359 and 2207 participants from different…

We tested the interaction between task value and self-efficacy on defensive pessimism, academic cheating, procrastination and self-handicapping among 574 Korean 11th graders in the context of English as a foreign language. We hypothesised that perceiving high value in tasks or domains for which self-efficacy was low would pose a threat to…

This paper identifies those behaviours that students perceive to be academically dishonest and sheds light on several demographic, academic and situational factors that predict students' perceptions of academic dishonesty. Data for this investigation were obtained through self-administered questionnaires from a sample of 321 undergraduate students…

Academic dishonesty is a persistent problem in institutions of higher education, with numerous short- and long-term implications. This study examines undergraduate students' self-reported engagement in acts of academic dishonesty using data from a sample of 321 participants attending a public university in a western Canadian city during the fall…

Academic dishonesty has recently been described as an epidemic illness and a phenomenon to be definitely prevented. Accordingly, prospective teachers are expected to have high ethical judgement levels. The section who suffers most from academic dishonesty is also teachers who serve in various ranks. Individuals with high ethical judgement levels…

The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…

The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…