研究芬兰中学生对数学AI工具的接受度，发现有用性最关键。
The Use of Generative Artificial Intelligence for Upper Secondary Mathematics Education Through the Lens of Technology Acceptance
- 用技术接受模型分析学生对数学AI工具的看法
- 感知有用性显著影响使用意愿，趣味性也起关键作用
- 工具与学习体验契合度越高，越容易被接受
本研究探讨了芬兰高中生在中学数学教育中使用生成式人工智能（GenAI）的感知。数据来自芬兰高中生，分析技术接受模型中的核心构念——感知有用性、感知易用性、感知乐趣和使用意愿如何影响AI工具的采纳。首先构建并分析了一个与前期研究对比的结构方程模型；随后提出包含新构念‘兼容性’（即AI工具与学生教育经验及需求的一致性）的扩展模型，并进行分析。结果表明，感知有用性对使用意愿有强烈影响，感知乐趣在决定感知有用性和易用性方面具有统计显著作用。引入兼容性后，模型解释力提升，尤其在预测感知有用性方面表现更优。研究深化了对AI工具融入数学教育的理解，并揭示了芬兰教育背景与以往研究在结构方程建模中的关键差异。
原文摘要 · Abstract (English)
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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