A systematic review of academic dishonesty in online learning environments.

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 co...

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Publicado en:Journal of Computer Assisted Learning Vol. 38; no. 4; pp. 907 - 929
Autores principales: Chiang, Feng‐Kuang, Zhu, Dan, Yu, Wenhao
Formato: research systematic review tables/charts Journal Article
Publicado: Wiley-Blackwell Aug2022
Acceso en línea:Ver este registro en EBSCOhost
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      jtl: Journal of Computer Assisted Learning
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      dt: Aug2022
      vid: 38
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1111/jcal.12656
        157845798
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        atl: A systematic review of academic dishonesty in online learning environments.
      aug:
        au:
          Chiang, Feng‐Kuang
          Zhu, Dan
          Yu, Wenhao
        affil: Center for Future Education, School of Education, Shanghai Jiao Tong University, Shanghai, China
      sug:
        subj:
          Student Misconduct Evaluation
          Online Education
          Learning Environment
          Human
          Systematic Review
          Content Analysis
          Educational Technology
          COVID-19 Pandemic
          Health Knowledge
          Student Attitudes
          Motivation
          Behavior Therapy
      ab: 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 & high technological complexity, individual AD & low technological complexity, collective AD & high technological complexity, and collective AD & low technological complexity. These findings provide a comprehensive understanding and guidance of AD in the online environment for relevant managers, designers and developers. Lay Description: 1. Systematic review of academic dishonesty in online learning environments. 2. To review followed the PRISMA procedure for selecting 59 eligible articles. 3. Factors influencing AD behaviour in online learning under the BEM framework. 4. To explore the types of interventions for AD in online environments.
      pubtype: Academic Journal
      doctype:
        research
        systematic review
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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