Predictors of K-12 Teachers’ Instructional Strategies with ICTs

Cheeraporn Sangkawetai, Jariya Neanchaleay, Ravinder Koul, Elizabeth Murphy

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

The goal of this study is to identify the relationship between K-12 teachers’ self-efficacy beliefs, classroom goal structure and use of instructional strategies. The study also aims to determine if there is variance in the relationship between these constructs for primary versus secondary school teachers. Data collection involved completion of a self-report survey by 810 primary and secondary school teachers in Thailand. Results revealed that personal and ICT teaching self-efficacy directly predicted both mastery and performance classroom goal structures for K-12 teachers. Mastery classroom goal structure predicted deep learning. Performance classroom goal structure predicted surface learning. ICT teaching self-efficacy was the strongest predictor of teachers’ instructional strategies with ICTs. Results also revealed that primary teachers’ performance classroom goal structure was positively associated with the use of deep-learning strategies with ICTs and student-centered learning with ICTs. In contrast, for secondary teachers, mastery classroom goal structure was positively associated with student-centered learning with ICTs, whereas both mastery and performance classroom goal structures were positively associated with the use of deep-learning strategies with ICTs. Results of this study suggest that classroom goal structure may be different for ICT classrooms than for regular classrooms. Implications relate to the need to help teachers design ICT activities that reflect both performance and mastery classroom goal structures.

Original languageEnglish (US)
Pages (from-to)149-177
Number of pages29
JournalTechnology, Knowledge and Learning
Volume25
Issue number1
DOIs
StatePublished - Mar 1 2020

All Science Journal Classification (ASJC) codes

  • Mathematics (miscellaneous)
  • Education
  • Human-Computer Interaction
  • Computer Science Applications

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