Research on the Impact of Artificial Intelligence-Assisted Learning Environments on Students’ Learning Motivation

DOI

10.2991/978-94-6463-674-1_12How to use a DOI?

Keywords

Artificial Intelligence; Learning Motivation; Educational Innovation

Abstract

This article, based on the Self-Determination Theory, uses questionnaire surveys, behavioral log analysis, and semi-structured interviews to study the impact of AI-assisted learning environments on intrinsic motivation, extrinsic motivation, and amotivation levels. The study employed an AI system based on adaptive learning algorithms, which can analyze students’ learning behaviors and mastery of knowledge points in real-time, generating personalized learning paths, providing immediate feedback, and presenting multimodal resources. The experimental results indicate that the AI system significantly enhances the level of learning motivation, while also improving learning efficiency, task completion rates, and knowledge retention rates.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Sijin Dang
PY  - 2025
DA  - 2025/03/17
TI  - Research on the Impact of Artificial Intelligence-Assisted Learning Environments on Students’ Learning Motivation
BT  - Proceedings of the 2024 Seminar on Educational Technology and Management Information Systems (ETMIS 2024)
PB  - Atlantis Press
SP  - 96
EP  - 103
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-94-6463-674-1_12
DO  - 10.2991/978-94-6463-674-1_12
ID  - Dang2025
ER  -