通过教育数据挖掘确定学生选修课程选择模式和满意度决定因素
Serhiy O Semerikov1,2, Olha V Bondarenko3,4, Pavlo P Nechypurenko3,4
1Kryvyi Rih State Pedagogical University, Kryvyi Rih, 50086, Ukraine. semerikov@gmail.com.
Scientific reports
|February 1, 2026
概括
这项研究使用教育数据挖掘来分析学生对选修课程的满意度. 研究结果揭示了影响选择和满意度的关键因素,为个性化学习路径优化提供了信息.
科学领域:
- 教育技术的教育技术
- 教育中的数据挖掘.
- 高等教育研究 高等教育研究
背景情况:
- 数字化转型正在重塑高等教育课程.
- 越来越多地强调学生代理和个性化的学习路径.
- 了解学生在选修课程中的偏好对于课程优化至关重要.
研究的目的:
- 通过教育数据挖掘分析学生的偏好和对选修课程的满意度.
- 确定课程选择中的模式和满意度的决定因素.
- 评估个人教育轨迹框架的有效性.
主要方法:
- 应用了教育数据挖掘技术.
- 分析了1089名学生的课程选择模式和满意度决定因素.
- 根据偏好和满意度确定不同的学生群体.
主要成果:
- 确定了四个不同的学生群体,具有不同的偏好和满意度概况.
- 信息的可用性,职业目标的一致性,教学质量和课程的相关性显著预测学生的满意度.
- 该研究确定了影响学生选择和学生在选修课程中的满意度的关键因素.
结论:
- 提出了一个数据驱动的框架来优化选修课程系统,整合学习分析和个性化建议.
- 教育技术可以增强学生在课程定制中的代理权.
- 这些发现支持可持续发展目标4,通过促进包容性,个性化的教育,为未来的就业提供支持.
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