In the present research, the authors assessed teaching quality in the context of blended learning in primary STEM; the educational reforms in the authors’ country require a digital transformation of education and a gradual shift to blended learning; therefore, appropriate teaching should follow in STEM classrooms. This research investigates the following research questions: how can we conceptualize teaching and learning in the context of blended learning in order to determine teaching quality? What teaching profiles are characteristic in the analyzed primary STEM lessons and what do the profiles indicate about student opportunities for blended learning? Through the analysis of existing reports about blended learning in STEM, the authors set three categories as important for blended learning to happen, namely opportunities for (1) learning with information and communication technologies (ICTs); (2) self-regulated learning; and (3) deep learning. To answer the research questions, the authors used a quantitative rubric-based evaluation approach. The selected criteria in tandem with level descriptors (from previously developed and validated framework) were used to analyze primary STEM lesson transcripts to determine teaching performance across eight criteria. Furthermore, a profiling approach was developed to uncover patterns in the data describing teaching quality; data analysis revealed four different teaching profiles. The use of ICT in the majority of the 187 analyzed lessons remains at the surface level or is non-existent. Teaching profiles were observed, in which students had various opportunities for self-regulated and deep learning. The student use of ICT was observed in 11% of samples’ lessons and all of those at the surface level. In addition to analyzing primary STEM lessons through a previously validated framework, this study contributes a novel profiling approach that systematically uncovers patterns of teaching performance in a blended learning context. By integrating categories of ICT use, self-regulated learning, and deep learning, the research provides an original lens on teaching quality that can guide both educators and policymakers in implementing effective blended learning strategies.
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Čakāne et al. (2025) studied this question.
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