教学设计学生机器学习以增强学习动机的计算思维技能
Hung-Hsiang Wang1, Chun-Han Ariel Wang2
1Department of Industrial Design, National Taipei University of Technology, 1, Sec. 3, Zhongxiao E. Rd., Taipei 10608, Taiwan.
Acta psychologica
|December 3, 2024
概括
引入机器学习工具来设计学生显著提高了他们对计算思维 (CT) 的动机. 虽然Weka增强了学习动机和算法技能,但它可能减少了协作,强调了需要平衡的教学.
科学领域:
- 设计教育设计教育教育
- 人与计算机的交互
- 设计中的人工智能
背景情况:
- 在设计教育中计算思维 (CT) 的整合尚未得到充分探索.
- 数字工具和人工智能为设计创新提供了新的途径.
- 传统的设计思维教学需要用计算方法来增强.
研究的目的:
- 调查机器学习工具对设计学生动机和CT技能的影响.
- 探索在产品设计教学中使用无代码机器学习工具.
- 评估学习动机,策略,协作和批判性思维的变化.
主要方法:
- 实验教学涉及56名工业设计学生超过八周.
- 利用怀卡托知识分析环境 (Weka),一个无代码的机器学习工具.
- 测试前和测试后数据的共变量分析,以比较Weka和没有Weka的组.
主要成果:
- 维卡小组显示了明显更高的一般学习动机.
- 在学习策略,协作或批判性思维方面没有观察到显著差异.
- 维卡使用增强的算法思维和动机,但潜在的合作减少.
结论:
- 无代码机器学习工具可以有效地提高设计学生对CT的动机.
- 需要仔细的课程设计,以平衡计算技能发展与协作实践.
- 整合人工智能工具为设计学生提供了一条与新兴技术互动的途径.
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