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This study applies the Self-Determination Theory (SDT) to examine the factors influencing students’ autonomous behavior of learning AI, with a particular focus on how intrinsic and extrinsic motivations shape their learning behaviors. Using a BP (Backpropagation) artificial neural network (ANN) model, the research analyzes a dataset collected from university students to predict the likelihood of students independently pursuing AI education. The results reveal that both internal and external factors contribute to students autonomous learning of AI.

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A Self-determination Theory Approach Using BP Artificial Neural Network to Predict College Students’ AI Learning Behavior

  • 会议论文

  • 发表日期：

    2025年

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  • Meiling Hong,
  • Xu Huang

摘要

This study applies the Self-Determination Theory (SDT) to examine the factors influencing students’ autonomous behavior of learning AI, with a particular focus on how intrinsic and extrinsic motivations shape their learning behaviors. Using a BP (Backpropagation) artificial neural network (ANN) model, the research analyzes a dataset collected from university students to predict the likelihood of students independently pursuing AI education. The results reveal that both internal and external factors contribute to students autonomous learning of AI.