Navigating Academic Integrity and Student Rationalisations of Generative AI in Vocational Online Learning Environments

Abstract

This longitudinal study examines the perceptions, behaviours, and ethical rationales of Diploma 3 (D3) vocational students across six distinct majors enrolled in e-learning English language courses over one full academic year (two semesters). Utilising an open-resource framework for weekly quizzes alongside a strictly unassisted online final examination model, this research explores how adult vocational learners navigate the boundaries between permissible AI assistance and prohibited use across an extended instructional timeline. Notably, despite the lecturer providing comprehensive, tailored learning materials on the institutional e-learning platform as the sole basis for final assessments, textual analysis revealed that many students consistently copied and pasted AI-generated outputs verbatim without editing or critical evaluation. Grounded in Andragogy and Adult Learning Theory, Cognitive Offloading Theory, Techniques of Neutralization, and Self-Concept Maintenance Theory, this study analyses student rationalisation strategies ranging from pragmatic self-justification and perceived workload pressure to passive silence. The findings unveil how traditional unassisted online evaluation models can fail when learners choose cognitive shortcuts over deep engagement with learning materials. Ultimately, this article concludes with actionable, evidence-based recommendations to realign vocational e-learning assessments with genuine cognitive engagement, advocating for innovative evaluation strategies that accommodate GenAI's presence while maintaining academic rigor, authentic skill mastery, and professional ethics in technical education.