Abstract
In a societal institution as fundamental as education, when teaching practitioners or researchers apply artificial intelligence in academic processes such as assessments, it is important to study the divide between what may be ethically permissible and not permissible. This study applied a systematic literature mapping methodology to scour extant research, so as to holistically
structure the landscape into explicit topical research clusters. Through topic modelling and network analyses, research mapped ten key ethical principles to five research archetypical domains, and reviewed the contribution and intensity of these ethical principles in each thematic domain. The study extended this review, by mapping out ethics programs and activities that can be applied in practice, alongside their relevant underpinning theories. This study provides a comprehensive treatment of this subject matter to date. We hope the findings of this research can provide researchers and practitioners the insights into the application
methods of AI in assessments, and in particular, in terms of their intertwined ethical challenges and how these challenges may be addressed, for follow up studies.
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