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.

Data literacy is a prerequisite for making data-based decisions. This paper focuses on the extent to which educators develop components of data literacy during a 1-year data use intervention, as well as what they learn and struggle with concerning these data literacy components. In the data use intervention, teams of teachers, school leaders and a data expert use data to solve an educational problem at their school. We employed a mixedmethods approach, combining data from a pre-and post-test data literacy test (N = 27), interviews (N = 12), evaluations of meetings (N = 33), and logbooks. Findings show that educators' data literacy increased significantly. Participants and the data coach indicated that educators had learned, for example, to analyze data with Excel, and to refute misconceptions. Still, there is room for further improvement. For example, educators struggled with formulating a data use purpose that is plausible, sufficiently concrete and measurable.

h i g h l i g h t s Identifies top five classroom assessments teachers initiate in the classroom. Teachers conduct peer and self-assessment in only 10%e25% of their lessons. Teachers use data for instruction in only 25%e50% of their lessons. Identifies top five prerequisites teachers consider important for AfL and DBDM. Highlights the need for professional development for teachers in AfL and DBDM.

Teacher professional learning is considered crucial for improving the quality of education. Teacher collaboration in professional learning communities can contribute to the effectiveness of professional development efforts. In the past decade, there has been a shift from within-school to between-school professional learning communities. However, results regarding their effectiveness have been inconsistent. In this study, we examine the effects of 23 networked professional learning communities in the Dutch context, using a mixed-methods approach. Results showed moderately positive effects on teachers’ perceived satisfaction; the knowledge, skills, and attitude developed; and their application to practice. Considering the early stage of development of these professional learning communities, teachers’ participation in networked professional learning communities seems promising for enhancing their professional learning.