继续使用或收集灰尘? 一项混合方法研究影响农村中学学生对人工智能驱动的自适应学习系统持续使用意向的因素
Jining Han1, Geping Liu1, Xinmiao Liu2
1Faculty of Education, Southwest University, Chongqing, China.
Heliyon
|July 18, 2024
概括
计算机的自我效能,享受,系统质量和反显著影响中国农村学生继续使用AI自适应式学习系统. 这些发现有助于为农村地区开发更好的AI教育工具.
科学领域:
- 教育技术的教育技术
- 教育中的人工智能
- 人与计算机的交互
背景情况:
- 由人工智能驱动的自适应学习系统提供个性化的教育.
- 了解用户采用对于有效实施至关重要,特别是在农村环境中.
- 关于中国农村中学学生采用人工智能适应性学习系统的研究有限.
研究的目的:
- 调查影响AI驱动自适应学习系统持续使用意向的因素.
- 确定农村学生对人工智能教育工具持续参与的关键决定因素.
- 为改善农村教育环境中的AI适应性学习系统提供见解.
主要方法:
- 采用了一种混合方法的方法.
- 该研究整合了技术接受模型3 (TAM3).
- 从中国西部农村中学收集经验数据.
主要成果:
- 计算机的自我有效性是使用意图的重要预测因素.
- 感知到的享受对持续使用的意图产生了积极的影响.
- 系统质量和反的感知被确定为关键决定因素.
- 这些因素共同塑造了学生继续使用AI自适应学习系统的意愿.
结论:
- 计算机的自我效能,感知的享受,系统质量和反对于在中国农村中学采用人工智能自适应学习系统至关重要.
- 结果为设计更有效和更有吸引力的AI教育工具提供了实用策略,用于农村学习者.
- 这项研究有助于理解人工智能在弥合贫困地区教育差距方面的作用.
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