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The Impact of AI Literacy on Undergraduate Autonomous Learning

Koravick Thiangtham et al.

Electronic Journal of e-Learning2026https://doi.org/10.34190/ejel.24.2.4188article
AJG 1
Weight
0.50

What the paper says

This study explores the factors driving autonomous learning (AU) among undergraduate students in AI-enhanced education. It specifically examines the role of AI literacy (AI-L), critical thinking (CT), self-regulation (SR), and self-efficacy (SE). Data collected from Thai university students were analyzed using Structural Equation Modeling (SEM). The results show that AI-L demonstrated a strong and significant positive influence on all three mediating variables—SE (β = 0.99, t = 20.00), SR (β = 0.93, t = 18.53), and CT (β = 0.70, t = 7.30). SE exerted as the most powerful predictor of AU (β = 0.52, t = 6.38), while critical thinking had a smaller direct impact. The findings suggest that AI-L is a foundational competency that requires metacognitive support. Consequently, educators should utilize strategies like blended learning and reflective practice. These insights encourage a learner-centered approach to digital education, fostering future-ready, autonomous learners.

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https://doi.org/https://doi.org/10.34190/ejel.24.2.4188

Or copy a formatted citation

@article{koravick2026,
  title        = {{The Impact of AI Literacy on Undergraduate Autonomous Learning}},
  author       = {Koravick Thiangtham et al.},
  journal      = {Electronic Journal of e-Learning},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.34190/ejel.24.2.4188},
}

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The Impact of AI Literacy on Undergraduate Autonomous Learning

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.