数据分析实例
- Kupers, E., Mouw, J. M., & Fokkens-Bruinsma,M. (2022). Teaching in times of COVID-19: A mixed-method study into teachers’ teaching practices, psychological needs, stress, and well-being. Teaching and Teacher Education (以286名中小学教师为对象,综合运用调查研究和访谈法,对教师的教学实践、心里需求、压力和幸福感等进行了聚类分析,包括谱系聚类(HAC)和多元方差分析(MANOVA),发现在疫情期间有三类教师群体:放松型、焦虑型以及工作狂型。)
- Ye, D., & Pennisi, S. (2022). Using trace data to enhance Students' self-regulation: A learning analytics perspective. The Internet and Higher Education,54. (以67名参与一门生物学在线异步课程的本科生和研究生为对象, 使用K-means clustering method对学生在LMS的学习跟踪数据和自我调节学习的问卷数据,分别进行了聚类分析,并比较了两者聚类分析结果的异同.)
- Yoon, I., & Kim, M.(2022). Dynamic patterns of teachers’ professional development participation and their relations with socio-demographic characteristics, teacher self-efficacy, and job satisfaction. Teaching and Teacher Education, 109. (使用TALIS2018的数据,对教师参与专业发展的情况做了聚类分析,发现有5种不同的类型;接着分析了性别、教龄以及学校位置在这五类特征方面的显著性差异)