The Influence of AI-Assisted Instruction on College Students' learning Psychology

This paper systematically reviews the dual effects of artificial intelligence-assisted instruction on College Students' learning motivation, learning strategy selection, and cognitive load, and puts forward optimization suggestions. It argues that in terms of learning motivation, artificial intelligence technology can not only enhance learning motivation by meeting students' basic psychological needs and providing external driving, but also weaken motivation due to overemphasizing results, reducing interaction and overuse. In terms of learning strategy selection, artificial intelligence technology can promote deep learning and enhance metacognitive strategies, but it may also make students' learning strategies remain at a superficial stage or weaken their metacognitive ability. In terms of cognitive load, artificial intelligence technology can effectively regulate cognitive load, but it may also cause abnormal load. Based on this, the artificial intelligence for teaching should be optimized from the three aspects of technology development, teaching practice and students' training, so as to balance the technical efficiency and students' psychological needs.

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Publication Details

Journal
Lecture Notes in Education Psychology and Public Media
Published
2025-09-09
DOI
https://doi.org/10.54254/2753-7048/2025.ns26709
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
0.00
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article

The Influence of AI-Assisted Instruction on College Students' learning Psychology

Xu Cheng
Lecture Notes in Education Psychology and Public Media
Online Learning and Analytics
article

The Influence of AI-Assisted Instruction on College Students' learning Psychology

Xu Cheng
article en

Abstract

This paper systematically reviews the dual effects of artificial intelligence-assisted instruction on College Students' learning motivation, learning strategy selection, and cognitive load, and puts forward optimization suggestions. It argues that in terms of learning motivation, artificial intelligence technology can not only enhance learning motivation by meeting students' basic psychological needs and providing external driving, but also weaken motivation due to overemphasizing results, reducing interaction and overuse. In terms of learning strategy selection, artificial intelligence technology can promote deep learning and enhance metacognitive strategies, but it may also make students' learning strategies remain at a superficial stage or weaken their metacognitive ability. In terms of cognitive load, artificial intelligence technology can effectively regulate cognitive load, but it may also cause abnormal load. Based on this, the artificial intelligence for teaching should be optimized from the three aspects of technology development, teaching practice and students' training, so as to balance the technical efficiency and students' psychological needs.

Lecture Notes in Education Psychology and Public MediaVol. 113(1)
South China Normal University (CN)
Openalex Percentile: Top 72%
Online Learning and Analytics
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