The Use of Generative Artificial Intelligence for Upper Secondary Mathematics Education Through the Lens of Technology Acceptance

TL;DR

This study explores Finnish upper-secondary students' perceptions of using Generative AI in mathematics education, highlighting the importance of perceived usefulness, enjoyment, and compatibility in AI adoption.

Contribution

It introduces an extended model incorporating Compatibility, enhancing understanding of factors influencing AI acceptance in mathematics education.

Findings

Perceived usefulness strongly influences intention to use GenAI.

Perceived enjoyment significantly affects perceived usefulness and ease of use.

Including Compatibility improves the model's explanatory power.

Abstract

This study investigated the students' perceptions of using Generative Artificial Intelligence (GenAI) in upper-secondary mathematics education. Data was collected from Finnish high school students to represent how key constructs of the Technology Acceptance Model (Perceived Usefulness, Perceived Ease of Use, Perceived Enjoyment, and Intention to Use) influence the adoption of AI tools. First, a structural equation model for a comparative study with a prior study was constructed and analyzed. Then, an extended model with the additional construct of Compatibility, which represents the alignment of AI tools with students' educational experiences and needs, was proposed and analyzed. The results demonstrated a strong influence of perceived usefulness on the intention to use GenAI, emphasizing the statistically significant role of perceived enjoyment in determining perceived usefulness and ease of use. The inclusion of compatibility improved the model's explanatory power, particularly in predicting perceived usefulness. This study contributes to a deeper understanding of how AI tools can be integrated into mathematics education and highlights key differences between the Finnish educational context and previous studies based on structural equation modeling.