Daniel Kangwa, Mgambi Msambwa Msafiri, Antony Fute
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引用次数: 0
Abstract
Background
This study explored the factors that influence the balance between academic integrity and the effective use of GenAI tools in higher education. It focused on the role of institutional guidelines in enhancing the responsible use of GenAI technologies to enhance academic integrity.
Objectives
The study was theoretically grounded in the Technology Acceptance Model and the Theory of Planned Behaviour to investigate the factors that promote academic integrity in using GenAI tools (RQ1), their impact and institutional strategies to effectively mitigate ethical risks (RQ2) and the model practices to support the ethical and effective use in higher education (RQ3).
Methods
The PRISMA framework was used to systematically review and thematically synthesise the results of 213 peer-reviewed articles published between January 2021 and May 2025.
Results
Finding indicates that academic support, defined by structured training, technical scaffolding, and perceived usefulness, is critical to enabling ethical GenAI use. Additionally, student self-regulation, as influenced by behavioural control and goal setting, was associated with greater academic integrity in GenAI-mediated learning. Whereas institutional policies varied widely, those with transparent, adaptive and discipline-responsive governance frameworks more effectively mitigated academic misconduct. Indeed, the model practices included GenAI ethics committees, interactive GenAI literacy modules, and the developer-educator collaborations to promote algorithmic transparency.
Conclusions
A comprehensive systems-based approach that encompasses academic support, self-regulation and ethical guidelines is critical for the responsible use of GenAI tools in education. Hence, to preserve academic integrity while nurturing innovation, institutions should integrate GenAI ethics into curricular design, faculty development and cross-sectoral policy frameworks. Future research may expand into multilingual and longitudinal analyses to support equitable and sustainable GenAI integration across diverse educational settings.
期刊介绍:
The Journal of Computer Assisted Learning is an international peer-reviewed journal which covers the whole range of uses of information and communication technology to support learning and knowledge exchange. It aims to provide a medium for communication among researchers as well as a channel linking researchers, practitioners, and policy makers. JCAL is also a rich source of material for master and PhD students in areas such as educational psychology, the learning sciences, instructional technology, instructional design, collaborative learning, intelligent learning systems, learning analytics, open, distance and networked learning, and educational evaluation and assessment. This is the case for formal (e.g., schools), non-formal (e.g., workplace learning) and informal learning (e.g., museums and libraries) situations and environments. Volumes often include one Special Issue which these provides readers with a broad and in-depth perspective on a specific topic. First published in 1985, JCAL continues to have the aim of making the outcomes of contemporary research and experience accessible. During this period there have been major technological advances offering new opportunities and approaches in the use of a wide range of technologies to support learning and knowledge transfer more generally. There is currently much emphasis on the use of network functionality and the challenges its appropriate uses pose to teachers/tutors working with students locally and at a distance. JCAL welcomes: -Empirical reports, single studies or programmatic series of studies on the use of computers and information technologies in learning and assessment -Critical and original meta-reviews of literature on the use of computers for learning -Empirical studies on the design and development of innovative technology-based systems for learning -Conceptual articles on issues relating to the Aims and Scope