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Strong Teachers (leerKRACHT)

Training programmes are confronted with an increased heterogeneity in their inflow and a stable or decreasing learning efficiency. They are faced with the challenge of guiding all students in this heterogeneous group in an appropriate way and encouraging them to develop their competences (Donche, Coertjens, Van Daal, De Maeyer & Van Petegem, 2014). This requires a sustainable innovation that takes into account the specific training context. Research shows that such an innovation is difficult to achieve through individual initiatives (Stes, 2008). Teacher Design Teams (TDTs) are put forward by the literature as a way to achieve a sustainable innovation. Through the Strong Teachers project, we want to investigate the functioning of TDTs (research objective 1) and the impact of the learning environments developed by these teams on students' perceptions and learning outcomes (research objective 2). More specifically for the first research objective, we want to investigate to what extent and in what way TDTs make use of research data and a didactic model for the development of a new learning environment. The multi-layered model of teacher learning and student learning functions as a framework for the research outline. The research is set up at the teacher training programme for secondary education (PBA-SO). Teachers (n=24) will rework the learning environment for the course applied didactics in TDTs of 4 to 6 persons.

In order to map out how the TDTs work, we will use video diaries. The impact of participation on the approach of the professors involved will be assessed via lesson observations. In addition, we also examine the impact on the perception on the learning environment and the learning outcomes of students, after having reviewed their inflow profile. We use a quasi-experimental design with different cohorts. This is collected by means of self-report questionnaires, among other things. The analytical methods vary from descriptive statistics on correlation and cluster analysis to structural comparison models. The data and the analyses from the verification condition act as the above-mentioned research data for the TDTs.