Objective: This study examines the efficacy of enculturation of academic integrity, in the context of an automated student plagiarism management system (ASPMS) at a private higher education institution (PHEI) to provide heuristics for related endeavours.
Theoretical Framework: In this topic, the main theory underpinning the research is the Actor-Network Theory (ANT).
Method: The methodology adopted for this research comprises a mixed approach, incorporating both qualitative thematic analysis of transcripts of interviews with human actors and quantitative analyses of data gathered from the ASPMS.
Results and Discussion: A nuanced, gestalt-like composition of ANT relationships emerged, from which many meaningful heuristics could be derived for both enhancing, and avoiding pitfalls in, enculturation of academic integrity. The ANT perspective allows for the essential roles of human and non-human actors in the network to be assessed for efficacy in achieving the objectives of the network. Overarching heuristics include ongoing cyclic-iterative refinement of the automated system; the underpinning regulatory framework and related organisational structures; and the education/training of human actors.
Research Implications: Incorporating automation in academic integrity measures, allows for the delegation of onerous tasks to non-human actors in the system. Notwithstanding, acknowledged disruptors in this evolving context, such as the advent of Large-Language Model Artificial Intelligence (LLM-AI) tools (notably, Chat-GPT), increasingly confound the detection and assessment of plagiarism. Advancing heuristics towards designing systems for enculturating academic integrity– and for concomitant evaluation of the efficacy of such actor networks (as per ANT) – comprises the major implications of this study.
Originality/Value: While this study involves a relatively esoteric context – a case study involving a bespoke ASPMS at a single PHEI campus in South Africa – the heuristics have application in many systems (actor networks), with or without automation, in which academic integrity is fostered.