HIGHER EDUCATIONAL INSTITUTIONS STUDENTS CO-CONSTRUCTING ACADEMIC INTEGRITY IN JAMAICA IN THE AGE OF ARTIFICIAL INTELIGENCE
This study investigated the perceptions of Jamaican higher education (HE) students regarding the development of artificial intelligence (AI) policies, and identified key elements deemed essential for effective regulation. Employing a quantitative approach framed by social constructivism and the Technology Acceptance Model (TAM), data were gathered from a proportionally stratified sample of 636 students across three institutions. Determined by a priori power analysis, the sample was recruited via a non-probability, off-campus strategy. Data analysis involved descriptive and inferential statistics with strict adherence to ethical protocols. The findings revealed a paradox: while students are overwhelmingly positive about AI’s potential, this optimism is critically undermined by their deep frustration with being excluded from policy development. This creates a perspective of dissonance, wherein students see an urgent need for governance but feel alienated by a top-down institutional approach. This research further indicates that students prioritize foundational, principle-based frameworks, such as mandatory faculty training and clear ethical guidelines, over granular, task-specific rules. They advocate a holistic overhaul of assessment methods, viewing various strategies as an interconnected package of reforms essential for maintaining academic integrity. This study provides critical, evidence-based insights for crafting AI policies that are not only effective but also legitimate, underscoring the necessity of a student-centric participatory approach to bridge the current governance gap and foster widespread acceptance within Jamaican HEIs.
Institutions
- Texila American University (GY)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-08-15
- DOI
- https://doi.org/10.5281/zenodo.16934705
- Primary Topic
- Geochemistry and Geologic Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00