Supporting the initial work of evidence-based improvement cycles through a data-intensive partnership. Issue 9 (29th July 2021)

• Record Type: Journal Article
• Authors: Bowers, Alex J.; Krumm, Andrew E.
• Is Part Of: Information and learning sciences. Volume 122:Issue 9/10(2021)
• Page Start: 629
• Page End: 650
• Publication Date: 2021-07-29
• Subjects: Cluster analysis -- Data analysis -- School leadership -- Data use -- Data science -- Data-driven decision-making -- Researcher practitioner partnerships -- Evidence-based improvement cycles -- Algebra I -- Case study -- Visual data analytics -- Heatmaps; Information science -- Periodicals; Library science -- Periodicals; Information theory in education -- Periodicals; Libraries and education -- Periodicals; 020
• DOI: 10.1108/ILS-09-2020-0212
• Languages: English
• ISSNs: 2398-5348

Abstract

Abstract : Purpose: Currently, in the education data use literature, there is a lack of research and examples that consider the early steps of filtering, organizing and visualizing data to inform decision-making. The purpose of this study is to describe how school leaders and researchers visualized and jointly made sense of data from a common learning management system (LMS) used by students across multiple schools and grades in a charter management organization operating in the USA. To make sense of LMS data, researchers and practitioners formed a partnership to organize complex data sets, create data visualizations and engage in joint sensemaking around data visualizations to begin to launch continuous improvement cycles. Design/methodology/approach: The authors analyzed LMS data for n = 476 students in Algebra I using hierarchical cluster analysis heatmaps. The authors also engaged in a qualitative case study that examined the ways in which school leaders made sense of the data visualization to inform improvement efforts. Findings: The outcome of this study is a framework for informing evidence-based improvement cycles using large, complex data sets. Central to moving through the various steps in the proposed framework are collaborations between researchers and practitioners who each bring expertise that is necessary for organizing, filtering and visualizing data from digital learning environments and administrative data systems. Originality/value: The authors propose an integrated cycle of data use in schools that builds on collaborations between researchers and school leaders to inform evidence-based improvement cycles.