Data-Based Decision Making at the Policy, Research, and Practice Levels

Data-based decision making (DBDM) can lead to school improvement. However, schools struggle with the implementation of DBDM. In this symposium, we will discuss research and the implementation of DBDM at the national and regional policy level and the classroom level. We will discuss policy issues around DBDM from the perspective of the Ministry of Education in the Netherlands. Next, one of the largest school boards from the Netherlands will provide its view on DBDM, and how it has implemented this in its schools through the so-called data team procedure. Teachers from a school from this school board will discuss the implementation of data teams in their school. Finally, the results of a study investigating the effects of data teams will be presented. To study the effects of the data team procedure a mixed-methods design was used, using a combination of a pretest-posttest and a quasi-experimental, control group design. The results show, for example, that data team participants’ knowledge and skills increased significantly according to a data literacy assessment. Also, teams were able to solve the educational problem they investigated and improve student achievement

Effects of an intervention for data-based decision making on teacher professional development

Schools are increasingly expected to use data for school improvement. However, educators struggle with the use of data (e.g. data-based decision making). Professional development in this area is needed. Therefore, we designed and implemented a professional development program for data use: the data team procedure. This study focuses on the effects of the data team procedure in ten schools. We studied the effects with regard to (1) the satisfaction of teachers with the procedure, (2) attitude, knowledge and skills with regard to data use, (3) use of knowledge and skills, and (4) improved student achievement. A mixed-methods study, using questionnaires, data literacy assessments, and interviews, showed that the participants are satisfied about the professional development program. Also, we found that teachers scored significantly higher on the data literacy assessment compared to the pre-test. The results for using knowledge and skills and improved student achievement were mixed. Some teachers reported using data in their own practice, but several teachers indicated that they did not use data in their own practice (yet). In the paper and presentation we will further discuss the content of the data team procedure, the methodology used to study the effects of the data team procedure, as well as the effects found. The data team procedure is a promising type of suppor

Data-Based Decision Making From a Researcher Perspective

This presentation focuses on the effects of the data team procedure in schools. School improvement in terms of improved student achievement is the ultimate goal of the data team procedure. To accomplish improved student achievement, teachers need to have applied the knowledge and skills as learned in the data team procedure. In addition, teachers need to have actually improved their knowledge, skills, attitudes, and beliefs because of the data team procedure. A prerequisite for learning is that teachers respond positively in terms of their satisfaction about the professional development program. Consequently, we can distinguish four levels of effects for the data team procedure (Guskey, 2000). The results of our quantitative and qualitative analyses show that data team participants are, for example, satisfied about the support and the materials related to the data team procedure. In terms of their use of knowledge and skills, participants significantly improved in collaboration around data use. Finally, several teams found the causes for their problem and implemented measures to improve student achievement. This presentation will further discuss how the use of data in teams can impact teacher professionalization and school improvement

How school leaders can build effective data teams: Five building blocks for a new wave of data-informed decision making

Data-informed decision making is considered important for school improvement. Working in data teams is a promising strategy for implementing data use in schools. Data teams consist of teachers and school leaders, who collaboratively analyze data to solve educational problems at their school. Studies show that school leaders can enable and hinder data use in such teams. This study aims at exploring what types of leadership behaviors are applied to support data use in data teams. The results of this study point to five key building blocks for school leaders wanting to build effective data teams in their school: (1) establishing a vision, norms, and goals (e.g., discussing vision, norms, and goals with teachers); (2) providing individualized support (e.g., providing emotional support); (3) intellectual stimulation (e.g., sharing knowledge and providing autonomy); (4) creating a climate for data use (e.g., creating a safe climate focused on improvement rather than accountability, and engaging in data discussions with teachers); and (5) networking to connect different parts of the school organization (e.g., brokering knowledge and creating a network that is committed to data use). Not only formal school leaders, but also teachers, can display these types of behavior. Finally, it is important to stress here that all these building blocks are needed to create sustainable data use practices. These building blocks can be used in a new wave of data-informed decision making in schools, in which teachers and school leaders collaboratively use a multitude of different data sources to improve education

Effects of a data use intervention on educators’ use of knowledge and skills

Data use is increasingly considered to be important for school improvement. One promising strategy for implementing data use in schools is the data team intervention. Data teams consist of teachers and members of the school leadership team, who collaboratively analyze and use data to solve an education-related problem at the school. This mixed-methods study aims at measuring the effects of working in a data team on the application of data use in ten secondary schools by using questionnaires and case study interviews. The results show that at the end of the intervention period, educators on the data teams did not apply data use more often for accountability actions, but seemed to be more aware of data use for school development and instruction. Furthermore, it seemed that the teachers made a start at applying data use for instructional actions

De datateam® methode:Een concrete aanpak voor onderwijsverbetering

Hoe kan ik ervoor zorgen dat de meerderheid van mijn leerlingen volgende keer wel een voldoende haalt voor geschiedenis? Hoe krijgen we de toetsresultaten Engels omhoog? Welke nieuwe methode moeten we aanschaffen voor wiskunde? Geven we eigenlijk wel voldoende feedback aan onze leerlingen? Hoe verbeteren we de doorstroom van klas 4 naar klas 5? Is de 6 die ik geeft echt een 6? Elke dag staan schoolleiders en docenten voor tal van beslissingen om de kwaliteit van het onderwijs te bewaken en te verbeteren. Veel van deze beslissingen worden ad hoc en (te) snel genomen, op basis van aannames, anekdotes en onderbuikgevoelens. Vaak blijken ze achteraf niet zo goed te zijn. Jammer, want binnen het onderwijs zijn veel data beschikbaar. Op vele scholen worden ze helaas niet of weinig gebruikt voor het verbeteren van onderwijs. Terwijl uit onderzoek blijkt dat het gebruik van data leidt tot beter onderwijs en uiteindelijk tot betere leerprestaties van leerlingen. Om dit patroon van ‘jumping to conclusions’ te doorbreken kunnen scholen de datateam ® methode gebruiken. Deze methode leert hen data effectief te gebruiken om concrete vraagstukken op te lossen en zo hun onderwijs te verbeteren. Meteen worden zowel allerlei mythes over de oorzaken van een probleem ontkracht, als de werkelijke oorzaken achterhaald. De datateam® methode is ontwikkeld aan de Universiteit Twente en uitgebreid onderzocht. In dit boek wordt deze methode stap voor stap beschreven. Het geeft ook vele voorbeelden vanuit scholen die er al mee werke