Generative AI and knowledge management in higher education: the impact of human development on student perceptions

Abstract

Purpose This study aims to explore how the Human Development Index (HDI) is associated with students’ perceived academic, personal and skill-development outcomes related to the integration of generative artificial intelligence, particularly ChatGPT, into higher education. From a knowledge management perspective, the research examines adaptive use of AI tools, structuring of information and support of autonomous learning in countries with varying development. Design/methodology/approach The study draws on 11,910 valid responses from the 2024 Global ChatGPT student survey, covering 58 countries. Based on 33 Likert-scale items, three reflective constructs were identified. To explore the relationships between HDI, usage intensity and perceived impacts, the analysis combined descriptive statistics, K-means clustering and a partial least squares structural equation modeling (PLS-SEM) mediation model. Findings The regression analysis showed a weak but statistically significant negative correlation between HDI and perceived impacts: students from lower-HDI countries tended to view ChatGPT’s impacts more positively. The PLS-SEM results indicated that higher national development is associated with lower perceived academic, developmental and skill-related benefits. This relationship appears both direct and indirect, as students in more developed countries report using ChatGPT less frequently and less creatively for academic purposes. Practical implications The findings highlight the need for context-sensitive, pedagogically grounded artificial intelligence strategies, particularly in highly developed countries and in the support of students from disadvantaged backgrounds. Originality/value This study is among the first to examine how national development levels shape perceived ChatGPT impacts in higher education. By combining HDI, cluster analysis and mediation modeling, it offers a novel perspective on digital inequality.

Ähnliche Arbeiten