Factors Influencing College Students' Generative Artificial Intelligence Usage Behavior in Mathematics Learning: A...

Area of Science:

• Educational Technology
• Artificial Intelligence in Education
• Mathematics Education

Background:

• Generative artificial intelligence (GAI) is emerging as a significant tool in higher education.
• Understanding factors influencing GAI adoption for mathematics learning is crucial.

Purpose of the Study:

• To analyze factors affecting college students' use of GAI for mathematics learning.
• To investigate the role of mathematics motivation within the Unified Theory of Acceptance and Use of Technology (UTAUT) framework.

Main Methods:

• Survey of 331 Chinese college students.
• Application of the Unified Theory of Acceptance and Use of Technology (UTAUT).
• Data analysis using Partial Least Squares Structural Equation Modeling (PLS-SEM).

Main Results:

• Performance expectancy, social influence, personal innovativeness, and mathematics motivation positively influenced behavioral intention to use GAI.
• Mathematics motivation, facilitating conditions, individual demand, and behavioral intention directly affected GAI usage.
• Mathematics motivation was the most significant predictor for both intention and behavior.
• Effort expectancy and individual demand did not significantly impact intention to use GAI.

Conclusions:

• Mathematics motivation is a critical driver for GAI adoption in mathematics learning among college students.
• Findings provide insights for integrating GAI effectively into mathematics education.
• Individual demand and mathematics motivation positively moderate the relationship between intention and behavior.