The data coach in action: a systematic review regarding the different tasks, roles and activities

Abstract

In the past decades, data-based decision-making (DBDM) to inform practices in education has increased (Mandinach & Schildkamp, 2021). DBDM is a means to maintain and improve the quality of education as well as student learning and achievement (Schildkamp, 2019; Schildkamp et al., 2013; Prenger & Schildkamp, 2018). Despite the growing importance of DBDM, research has pointed out that although teachers and school teams have access to various types of data, they often fail to respond to these data and use it to adjust classroom instruction (Marsh, Bertrand & Huguet, 2015). Furthermore, teachers do not use data in a way that leads to profound changes in instruction or practice because they do not have the necessary skills and knowledge to formulate questions, interpret results and develop instructional responses (Cosner, 2012; Heritage et al., 2009; Marsh et al., 2006; Means et al., 2011; Oláh et al., 2010; Young, 2006; Goertz et al., 2009).

Various studies investigated the factors that enhance DBDM. Human support such as involving data coaches seems to be one of the enabling conditions to promote educator’s use of data and to support the data-team in DBDM (Lachat et al., 2006; Marsh, 2012; Marsh et al., 2006; Marsh et al., 2010; Marsh et al., 2015; Schildkamp et al., 2014). Data coaches can support teachers to become more experts in interpreting data, understanding student thinking and making instructional changes (Marsh et al., 2010; Means et al., 2010).

Although research has highlighted the importance of data coaches, limited research has focused on this role. To further investigate the profile, tasks and roles of data coaches, a systematic literature review was performed. This review has three main objectives. The first goal is to analyse literature on the specific functions, tasks, and roles of a data coach. Next, the study investigates how the professionalization of the data coaches takes form and how the coaches ensure the sustainability of DBDM-practices in schools. Lastly, the study explores how collaboration between data coaches and school leaders takes place since this is still unclear. Exclusion criteria included research that focused on education in kindergarten, nursery schools, higher education, special needs education and research in which the role of the data coach was unclear and/or minimally described. In total nineteen articles were included and analysed using NVivo.

Results show that there are a lot of differences regarding the role of a data coach. Many differences are found, such as the name, the appointment of the role, the effects and the competencies. Similarities are found regarding the range of tasks a data coach fulfills. The coach often takes a guiding and supportive role rather than a steering one. Professionalization of the role is rarely present. Finally, school leaders are often part of the data team and facilitate the data coach's work.

This study investigates which profile data coaches need to have to offer added value. The research reveals the many different interpretations and implementations the role has in practice. Further research is necessary to deepen this role and the necessary professionalization.