Exploring the relationships among perceived AI ability, academic self-efficacy and independent learning disposition in the tertiary contexts

As generative AI (GenAI) becomes increasingly embedded in higher education, this study examines how students' perceived AI ability (AIA) relates to their independent learning disposition (INL) and academic self-efficacy (ASE). We administered a quantitative survey to 302 undergraduate students in Hong Kong. Results indicated significant positive correlations among AIA, INL, and ASE. Mediation analysis further showed that INL mediates the association between AIA and ASE: students who perceive themselves as more capable with AI also report stronger independent learning dispositions, which in turn are linked to higher academic self-efficacy. We discuss the potential of AI tools to scaffold self-directed learning and strengthen students’ academic confidence, outline pedagogical implications for embedding AI competency training in curricula, and propose directions for future research.

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Publication Details

Journal
Computers and Education Artificial Intelligence
Published
2025-11-29
DOI
https://doi.org/10.1016/j.caeai.2025.100516
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.00
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article

Exploring the relationships among perceived AI ability, academic self-efficacy and independent learning disposition in the tertiary contexts

Lok Ming Eric Cheung, Huiwen Shi, On‐Ting Lo
Computers and Education Artificial Intelligence
Online Learning and Analytics
article

Exploring the relationships among perceived AI ability, academic self-efficacy and independent learning disposition in the tertiary contexts

Lok Ming Eric Cheung, Huiwen Shi, On‐Ting Lo
article en

Abstract

As generative AI (GenAI) becomes increasingly embedded in higher education, this study examines how students' perceived AI ability (AIA) relates to their independent learning disposition (INL) and academic self-efficacy (ASE). We administered a quantitative survey to 302 undergraduate students in Hong Kong. Results indicated significant positive correlations among AIA, INL, and ASE. Mediation analysis further showed that INL mediates the association between AIA and ASE: students who perceive themselves as more capable with AI also report stronger independent learning dispositions, which in turn are linked to higher academic self-efficacy. We discuss the potential of AI tools to scaffold self-directed learning and strengthen students’ academic confidence, outline pedagogical implications for embedding AI competency training in curricula, and propose directions for future research.

Computers and Education Artificial IntelligenceVol. 9
Openalex Percentile: Top 61%
Online Learning and Analytics
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