Exploring the Impact of AI-driven Adaptive Learning Systems in University Education: An Empirical Study of Learning Engagement Based on NSSE Data

Research investigation looks into the effect of student interaction and academic results with artificial intelligence adaptive education platform in college situations. The research in this study is based on the research data provided by National Survey of Student Engagement (NSSE), and the regression analysis and ANOVA together with factor analysis are used to understand learning outcomes from the usage of AI. AI engagement has a good association with GPA achievement and students who use AI systems inevitably do better in GPA scores than those who don't. Utilizing Factor Analysis, the “AI Learning Engagement” factor clearly exceeds the others, and is the determinant of academic success variations as much as 35%. The GPAs of the students in the two groups are shown to be different by the ANOVA statistical analysis. The research shows that AI makes personalized education and personalized educational results better than institutions need to adopt AI into their curriculum. But following promising results, the study requires additional scientific investigation to determine extent of positive outcomes and readiness of operations in other types of educational environments.

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Published
2025-04-18
DOI
https://doi.org/10.1145/3746469.3746501
Primary Topic
Educational Technology and Pedagogy
Type
article
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article

Exploring the Impact of AI-driven Adaptive Learning Systems in University Education: An Empirical Study of Learning Engagement Based on NSSE Data

Li Yang
Educational Technology and Pedagogy
article

Exploring the Impact of AI-driven Adaptive Learning Systems in University Education: An Empirical Study of Learning Engagement Based on NSSE Data

Li Yang
article en

Abstract

Research investigation looks into the effect of student interaction and academic results with artificial intelligence adaptive education platform in college situations. The research in this study is based on the research data provided by National Survey of Student Engagement (NSSE), and the regression analysis and ANOVA together with factor analysis are used to understand learning outcomes from the usage of AI. AI engagement has a good association with GPA achievement and students who use AI systems inevitably do better in GPA scores than those who don't. Utilizing Factor Analysis, the “AI Learning Engagement” factor clearly exceeds the others, and is the determinant of academic success variations as much as 35%. The GPAs of the students in the two groups are shown to be different by the ANOVA statistical analysis. The research shows that AI makes personalized education and personalized educational results better than institutions need to adopt AI into their curriculum. But following promising results, the study requires additional scientific investigation to determine extent of positive outcomes and readiness of operations in other types of educational environments.

Huazhong University of Science and Technology (CN)
Openalex Percentile: Top 88%
Educational Technology and Pedagogy
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