Abstract
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.
Highlights
Data use leads to educators concentrating more on students’ deficits than their assets
We focused on the following research question: How do formal school leaders apply leadership behaviors and strategies to support the work of the data team in the data team intervention?
Referring to leaders who Facilitate data use, for example, by providing time for accessing, analyzing and reflecting on data Coach and delegate challenging tasks with regard to data use Provide feedback with regard to data use Referring to leaders who Encourage teachers to challenge their beliefs and assumptions about data use Are role models for other data team members with regard to data use and working in the data team, for example, by completing extra tasks to prepare for the data team meeting Engage teachers in discussions about data use and lead discussions about data use with teachers Distribute and share decision-making authority, for example, by letting staff develop effective instructional practices based on data
Summary
Data use leads to educators concentrating more on students’ deficits than their assets. An emphasis on data use leads to cheating on tests and teaching to the test (Booher-Jennings 2005; Hargreaves et al 2018). Instead data can inform decisions, which, combined with the professional knowledge of educators, can contribute to achievement and learning in schools. This type of data use does not focus solely on achievement on a narrow set of topics, but can be used to work on different sets of goals (e.g., literacy and numeracy, and well-being, arts, critical thinking, and creativity, see Hargreaves et al 2018). This new wave of data use is studied in many countries around the world, such as Belgium (e.g., Van Gasse et al 2016; Vanhoof et al 2012; Vanlommel et al 2016), Canada (e.g., Earl and Katz 2006; Katz and Dack 2014), New Zealand (e.g., McNaughton et al 2012; Lai et al 2014), Norway (e.g., Mausethagen et al 2018; Prøitz et al 2017), Germany (e.g., Demski and Racherbäumer 2017), Sweden (e.g., Blossing et al 2018), England (e.g., Downey and Kelly 2013; Schildkamp et al 2014), South Africa (e.g., Archer et al 2013), Trinidad and Tobago (e.g., De Lisle 2015; De Lisle et al 2013), the US (e.g., Datnow and Park 2018; Mandinach and Gummer 2013), and the Netherlands (e.g., Schildkamp and Poortman 2015; Van der Scheer and Visscher 2016; Van Geel et al 2016)
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