Background: Data-based decision-making (DBDM) and research-informed teaching practice (RITP) are key to teacher and school improvement. Currently, however, DBDM and RITP represent two distinct approaches to developing evidence-informed practice (EIP) and do not correspond to the all-encompassing notion of EIP envisaged by many academics and commentators. Purpose: DBDM and RITP are usually employed independently of each other. Each is associated with its own theoretical perspectives and research base, and each has its own pitfalls and strengths. Yet the approaches employed appear to be complementary, suggesting that there might be value in combining DBDM and RITP into one overarching process for achieving EIP. This paper presents the conceptual analysis and arguments for this proposal. Sources of evidence: Drawing from literature and previous research in the fields of DBDM, RITP and EIP, we describe both DBDM and RITP, before comparing and contrasting the integral aspects of each. Main argument: Our analysis leads us to suggest that not only is there overlap between these two approaches, but the strengths of each appear to mirror and compensate for the weaknesses of the other. As such, we argue that it is important that decisions in education are based on a combination of personal judgement, research evidence and local school data. This is because such a combination is likely to lead to equitable, effective and efficient decisions that are informed by values and preferences, grounded in context and steeped in practices that have been shown to be effective elsewhere. Conclusions: We suggest that an effective strategy for EIP might be to achieve ‘the best of two worlds’ by integrating DBDM and RITP. In line with evidence-informed practices in medicine and management, this means EIP in education can finally be engaged in as a holistic approach to educational decision-making that critically appraises different forms of evidence before key improvement decisions are made. Our proposed approach, Evidence informed School and Teacher Improvement, is thus designed with the aim of enhancing the quality of educational provision by employing these evidence types as part of a systematic cycle of inquiry, focused on continuously improving the quality of learning in schools.

Science and technology education has become increasingly important. However, for most teachers, it is challenging to provide this content. Therefore, professional development programmes are used to support teachers in this regard. In this qualitative study, effective characteristics that should be present in such programmes were identified. Moreover, four particular professional development programmes were investigated to see whether they included these characteristics. Eleven review studies and meta-analyses were analysed to identify the effective characteristics of professional development programmes for science and technology education. Five content characteristics were distinguished: focus, activities, collaboration, coherence of content, and duration. In addition, three contextual characteristics were distinguished: coherence with context, individual factors, and organisational factors. The materials from four professional development programmes for science and technology education were collected and analysed and interviews were held with principal investigators who were involved in the design of these programmes and with educators who worked with these programmes. The characteristics duration and coherence with context appeared to be fully addressed in respectively two and one programmes. The other characteristics were incorporated to a limited extent or not at all. Overall, the present study illustrated the apparent challenges in designing professional development programmes.

The data team intervention was designed to support Dutch secondary schools in using data while developing a solution to an educational problem. A data team can build school-wide capacity for data use through knowledge sharing among data team members, and knowledge brokerage between the team and other colleagues. The goal of this mixed-methods study is to understand how knowledge sharing and brokerage regarding data use and an educational problem changed over time. Social network data were collected twice at eight schools. These data were used to analyse (1) how well team members were connected with each other (density), (2) whether team members’ relationships were mutual (reciprocity) and (3) whether all team members were equally important for the data team network (centralisation). Moreover, different types of knowledge brokering (inward, outward and forward) were examined to further understand knowledge exchange between data team members and their colleagues. Qualitative data were analysed to triangulate these findings for four particular cases. Among other things, findings illustrated that while knowledge sharing and knowledge brokerage both changed over time, there were considerable differences between teams in the extent and direction of change. It appeared that the dissemination of knowledge within the organisation requires more explicit attention.