Ethics, generative artificial intelligence, and educational assessment: An analysis of university students’ perceptions

Abstract

Introduction: The ethical use of generative artificial intelligence (GAI) in Education, particularly in learning assessment, is an issue of growing importance in higher Education due to its impact on values and academic integrity. Objective: This research aimed to examine university students’ perceptions regarding the ethical use of GAI in evaluative practices, based on five pre-established ethical dimensions. Method: A quantitative, non-experimental and cross-sectional study was conducted. A questionnaire of 16 closed-ended Likert- scale items was administered to 2684 students from ten degrees at Santa Elena Peninsula State University, Ecuador. The processing and analysis followed this sequence: item-level descriptive analysis, dimensional scales using measures of central tendency and dispersion, correlations based on Spearman´ Rho to identify relationships, and finally, principal components analysis (PCA) to identify structure and latent factors. Results: The results revealed a strong consensus on regulations, ethical principles and academic honesty, but also differences in trust, responsibility and formative impact. Two main factors emerged: one highly consistent factor combining norms, responsibility and impact, and another reflecting differences in honesty and trust. Conclusions: It is concluded that, while ethics in the use of GAI is generally accepted, it’s insufficiently understood and applied in assessment practice, revealing discrepancies and diverse positions evident, indicating that this is an area of critical analysis and further educational work.

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