在数据分析技术课程中探索大学生继续学习的意图:自我有效性的调节作用
Liqiong Liu1, Pinghao Ye1, Joseph Tan2
1School of Business Administration, Wuhan Business University, Wuhan, China.
Frontiers in psychology
|October 30, 2023
概括
大学生大学的学生.
科学领域:
- 教育技术的教育技术
- 数据科学教育数据科学教育
背景情况:
- 数据分析技能在数字经济中至关重要.
- 大学正在专注于数据分析技术课程.
- 了解学生的学习意图是有效课程设计的关键.
研究的目的:
- 探索影响大学生继续学习数据分析技术的意图的因素.
- 调查自我效能在互动性和学习意图之间发挥的调节作用.
主要方法:
- 利用了刺激-有机体-反应模型和流理论.
- 通过在线调查收集了314份有效的问卷.
- 使用SmartPLS验证了研究模型.
主要成果:
- 认知兴趣和自我效能对持续学习意图产生了积极影响.
- 互动性对自我效能产生了积极的影响.
- 自我有效性显著缓和了互动性和持续学习意图之间的关系.
结论:
- 认知兴趣和自我效能对于数据分析的持续学习至关重要.
- 互动性增强了自我效能,这反过来又提高了学习持久性.
- 教育技术干预应侧重于建立自我效能和培养兴趣.
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