One-size does not fit all: Towards an adaptive model to develop preservice teachers’ digital competencies

Jo Tondeur, Sarah K. Howard, Jie Yang

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)


Despite the existing knowledge base, it remains unclear how to best prepare preservice teachers with different profiles. While it is generally agreed that multiple strategies are required to develop preservice teachers' digital competency, the question remains how these strategies may come together to support preservice teachers' different needs in training. Therefore, this study examines 1) the key relationships among strategies to develop preservice teachers’ digital competencies and 2) how the self-organization of these strategies changes in relation to pre-service teachers' attitudes towards digital technology. To explore these questions, we analyzed preservice teacher questionnaire data (N = 931) from 20 teacher training institutions in Belgium. Data is analyzed through the grouping of preservice teachers based on high and low attitudes towards digital technologies. Association rules analysis was then run on each group to identify patterns among six strategies to teach digital competency. Results were visualised as directed graphs. Findings show different patterns of associations among strategies for the two groups. Results from preservice teachers with more positive attitudes showed a very specific focus on Collaboration, while those with lower attitudes had an emphasis on Feedback. This finding suggests that important differences may exist in how preservice teachers experience the development of digital competency in their training, which can inform future design of teacher training programs.

Original languageEnglish
Article number106659
JournalComputers in Human Behavior
Publication statusPublished - Mar 2021


  • Attitudes
  • Data mining
  • Digital competence
  • SQD strategies
  • Teacher training


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