文章基本信息

标题：Learning analytics and flipped learning in online teaching for supporting preservice teachers’ learning of quantitative research methods
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作者：Erkko Sointu ; Teemu Valtonen ; Susanne Hallberg 等
期刊名称：Seminar.net
电子版ISSN：1504-4831
出版年度：2022
卷号：18
期号：1
DOI：10.7577/seminar.4686
语种：English
出版社：Lillehammer University College
摘要：Research methods, including those of a quantitative nature, are an important part of preservice teacher training in Finland. However, quantitative research methods are considered challenging, often feared, and even hated among preservice teachers. This may be due to previous negative experiences and emotions associated with their use, which also influence other aspects of learning such as self-regulation, self-efficacy, and orientations. Given such circumstances, new ways to teach and support the learning of quantitative methods are needed. Here, we investigate the self-regulation, self-efficacy, orientations, and emotions of preservice teachers (N = 38) enrolled in a quantitative methods online course incorporating learning analytics and a flipped learning approach. Dispositional learning analytics data from five measurement points were used, and data were analyzed via descriptive statistics, internal consistency (Cronbach alpha), bootstrapped paired sample t-test (between first and final measurement point), and profiles based on mean. The results demonstrate that in this teaching context, preservice teachers’ time management skills can be improved, and task avoidance, anxiety, and boredom towards quantitative methods decreased. The meaning of these results from the teaching context perspective are also examined, as are the limitations and implications of this study.