AI Across Borders: Exploring Perceptions and Interactions in Higher Education

2024-12-15

arXiv.org

AI Summary

This study investigates cross-cultural differences in undergraduate students’ perceptions of and attitudes toward generative artificial intelligence (GenAI) across higher education institutions in Northern Ireland and India. Drawing on mixed-method data from 1,211 students—including Likert-scale responses and open-ended comments—the analysis employs multivariate regression, ANOVA, and thematic coding to assess the influence of institutional affiliation, academic discipline, and gender. It presents the first systematic, cross-national comparison of GenAI awareness and attitudinal landscapes in higher education contexts. Key findings reveal high attitudinal convergence among Computer Science students—underscoring the strong formative role of disciplinary training; significant inter-institutional variation in GenAI perception; no statistically significant main effect of gender; and individual GenAI usage experience emerging as the strongest predictor of attitude—validating an “experience-driven cognition” mechanism. The study provides empirical evidence and theoretical grounding for context-sensitive design of global AI literacy curricula.

Technology Category

• Humans and AI: Game Design — Procedural Content Generation & Storytelling
• Application Domains: Humanities & Computational Social Science
• Philosophy and Ethics of AI: Artificial General Intelligence

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• User Modeling, Personalization and Recommendation: Fairness-aware retrieval and ranking

Abstract

This study investigates students'perceptions of Generative Artificial Intelligence (AI), with a focus on Higher Education institutions in Northern Ireland and India. We collect quantitative Likert ratings and qualitative comments from 1,211 students on their awareness and perceptions of AI and investigate variations in attitudes toward AI across institutions and subject areas, as well as interactions between these variables with demographic variables (focusing on gender). We find that: (a) while perceptions varied across institutions, responses for Computer Sciences students were similar; and (b) after controlling for institution and subject area, we observed no effect of gender. These results are consistent with previous studies, which find that students'perceptions are predicted by prior experience. We consider the implications of this relation and some considerations for the role of experience.

Problem

• Investigates students' perceptions of GenAI in Higher Education
• Examines variations in AI attitudes across institutions and subjects
• Analyzes interactions between demographic factors and AI perceptions

Innovation

• Quantitative Likert ratings and qualitative comments
• Cross-cultural comparison in Higher Education
• Interaction analysis of demographic and academic factors