在高等教育中探索生成人工智能:一个RAG系统来增强学生与科学文献的接触
Dominik Thüs1, Sarah Malone1, Roland Brünken1
1Department of Education, Saarland University, Saarbrücken, Germany.
Frontiers in psychology
|October 28, 2024
概括
一个AI学习工具OwlMentor被评估为大学生. 虽然没有证明直接学习的收益,但在用户中发现了更高的收益,自我有效性影响了系统采用.
科学领域:
- 教育技术的教育技术
- 教育中的人工智能
- 高等教育教学的教学.
背景情况:
- 大学学生经常与复杂的科学文本作斗争.
- 由人工智能驱动的工具为增强理解提供了潜在的解决方案.
- 参与式设计对于开发有效的教育技术至关重要.
研究的目的:
- 实施和评估OwlMentor,一个用于科学文本理解的AI学习环境.
- 用技术接受模型评估学生对OwlMentor的接受程度.
- 探索一般自我效能对系统采用和使用的影响.
主要方法:
- 在两个学期内参与设计和代开发OwlMentor.
- 将OwlMentor集成到大学课程中.
- 通过技术接受模型评估系统接受度.
- 检查学习成果和自我效能的影响.
主要成果:
- 在感知易用性,实用性和实际系统使用之间观察到复杂的关系.
- 没有发现OwlMentor使用与测量学习收益之间的直接相关性.
- 描述性分析表明,OwlMentor用户与非用户的学习收益更高.
- 一般的自我有效性强烈预测了感知到的有用性,使用意图和实际使用.
结论:
- 系统接受模型可能需要更具动态性,以反映复杂的用户交互.
- 将人工智能工具与学生的需求和学习策略结合起来,是教育影响的关键.
- 一般的自我效能在人工智能学习工具的采用和使用中发挥着重要作用.
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