Mathematics

Knowledge management

Statistics

Psychiatry

Political science

Psychology

Psychological intervention

Systematic review

Cheating

Academic dishonesty

MEDLINE

Descriptive statistics

Computer science

Social psychology

Journal of Computer Assisted Learning

Background During the COVID‐19 pandemic, online learning has played an increasingly crucial role in the educational system. Academic dishonesty (AD) in online learning is a challenging problem that represents a complex psychological and social phenomenon for learners. However, there is a lack of comprehensive and systematic reviews of AD in online learning environments. Objectives This study presents a systematic study of AD in online learning environments to delineate its trends and uncover potential areas for further research. Methods We conducted this review based on various sources of evidence‐based research and followed the guidelines of the PRISMA statement and procedure for selection. After the exclusion criteria were employed, 59 eligible articles were selected and then analysed in a descriptive overview. Two frameworks were identified in the structured content analysis to analyse these articles. One was the framework of Gilbert's Behaviour Engineering Model (BEM), and the other was the types of interventions for online AD, where 36 articles were analysed. Results and Conclusions The descriptive results showed that most studies used quantitative methods and focused on students. The analysis results of influencing factors under the BEM framework showed that the category of environment support and tools accounts for the largest proportion. And the types of interventions for online AD we classified include individual AD &amp; high technological complexity, individual AD &amp; low technological complexity, collective AD &amp; high technological complexity, and collective AD &amp; low technological complexity. These findings provide a comprehensive understanding and guidance of AD in the online environment for relevant managers, designers and developers.

A systematic review of academic dishonesty in online learning environments