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

• URL: http://arxiv.org/abs/2501.14779v1
• Date: Thu, 02 Jan 2025 14:50:30 GMT
• Title: The Use of Generative Artificial Intelligence for Upper Secondary Mathematics Education Through the Lens of Technology Acceptance
• Authors: Mika Setälä, Ville Heilala, Pieta Sikström, Tommi Kärkkäinen,
• Abstract summary: The study investigated the students' perceptions of using Generative Artificial Intelligence (GenAI) in mathematics education. The results demonstrated a strong influence of perceived usefulness on the intention to use GenAI. The inclusion of compatibility improved the model's explanatory power, particularly in predicting perceived usefulness.
• Score: 0.3749861135832073
• License:
• 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.

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