No abstract

Background: Data-based decision-making in education often focuses on the use of summative assessment data in order to bring about improvements in student achievement. However, many other sources of evidence are available across a wide range of indicators. There is potential for school leaders, teachers and students to use these diverse sources more fully to support their work on a range of school improvement goals. Purpose and sources of evidence: To explore data-based decisionmaking for school improvement, this theoretical paper discusses recent research and literature from different areas of data use in education. These areas include the use of formative assessment data, educational research study findings and 'big data'. In particular, the discussion focuses on how school leaders and teachers can use different sources of data to improve the quality of education. Main argument: Based on the literature reviewed, an iterative model of data use for school improvement is described, consisting of defining goals for data use, collecting different types of data or evidence (e.g. formal data, informal data, research evidence and 'big data'), sense-making, taking improvement actions and evaluation. Drawing on the literature, research insights are discussed for each of these components, as well as identification of the research gaps that still exist. It is noted that the process of data use does not happen in isolation: data use is influenced by system, organisation and team/individual level factors. Conclusions: When it comes to using data to improve the quality of teaching and learning, it is evident that some of the most important enablers and barriers include data literacy and leadership. However, what is less well understood is how we can promote the enablers and remove the barriers to unlock, more fully, the potential of data use. Only then can data use lead to sustainable school improvement.

a b s t r a c tAlthough many researchers acknowledge that Assessment for Learning can significantly enhance student learning, the factors facilitating or hindering its implementation in daily classroom practice are unclear. A systematic literature review was conducted to reveal prerequisites needed for Assessment for Learning implementation. Results identified prerequisites regarding the teacher, student, assessment and context. For example, teachers must be able to interpret assessment information on the spot, student engagement in the assessment process is vital, assessment should include substantial, constructive and focussed feedback, and the school should have a school-wide culture that facilitates collaboration and encourages teacher autonomy. The results of this review contribute to a better understanding of the multiple facets that need to be considered when implementing Assessment for Learning, from both a theoretical and a practical standpoint.

Although data-based decision making can lead to improved student achievement, data are often not used effectively in schools. This paper therefore focuses on conditions for effective data use. We studied the extent to which school organizational characteristics, data characteristics, user characteristics, and collaboration influenced data use for (1) accountability, (2) school development, and (3) instruction. The results of our hierarchical linear modeling (HLM) analysis from this large-scale quantitative study (N = 1073) show that, on average, teachers appear to score relatively high on data use for accountability and school development. Regarding instruction, however, several data sources are used only on a yearly basis. Among the factors investigated, school organizational characteristics and collaboration have the greatest influence on teachers' data use in schools.ARTICLE HISTORY

The use of data for educational decision making has never been more prevalent. However, teachers and school leaders need support in data use. Support can be provided by means of professional development in the form of "data teams". This study followed the functioning of 4 data teams over a period of 2 years, applying a qualitative case study design. The findings show that data use is not a linear process, and that teams go through different feedback loops to reach higher levels of depth of inquiry. The data team procedure is a promising way of enhancing data-based decision making in schools.