Computers and Education Open (Dec 2022)
Preservice teacher cluster memberships in an edtech course: A study of their TPACK development
Abstract
Researchers have been examining preservice teachers’ development of TPACK in edtech courses for years. However, most empirical studies used small samples to look at preservice teachers’ TPACK development in the edtech courses. With a small dataset, it is hard to know whether there consistently exist knowledge gaps in preservice teachers’ prior knowledge and TPACK development in the edtech course. Studies with large samples are needed because they provide a large amount of empirical data that can be used as strong evidence for justifying whether the edtech course has any impact on preservice teachers’ TPACK development across all demographic and prior knowledge groups. Thus, the purpose of this study was to examine eighteen cohorts of preservice teachers’ pre-TPACK scores and their cluster assignment, as well as their post-TPACK scores in a required edtech course. A two-step cluster analysis was used based on pre-TPACK scores and demographics to identify groups of preservice teachers that share common characteristics in their pre-TPACK scores. A two-cluster model was a good fit (cluster 1 - lower pre-TPACK scores and cluster 2 - higher pre-TPACK scores). Independent-sample t-tests were run to test whether there were differences in the post-TPACK scores. Findings revealed that cluster 2 preservice teachers had higher post-TPACK scores. These results might help teacher educators make data-driven decisions to design targeted instructions for diverse preservice teacher groups. Details on potential actions for designing the edtech course and practices for developing TPACK were discussed.
