Supporting the Initial Work of Evidence-Based Improvement Cycles Through a Data-Intensive Partnership

Item

Title

Supporting the Initial Work of Evidence-Based Improvement Cycles Through a Data-Intensive Partnership

Abstract/Description

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.

Author/creator

Bowers, Alex J.

Krumm, Andrew E.

Date

2021

In publication

Information and Learning Sciences

Volume

122

Issue

10-Sep

Pages

629-650

Resource type

en Research/Scholarly Media

Resource status/form

en Published Text

Scholarship genre

en Empirical

Keywords

aata use

aata analysis

school leadership

case study

Algebra I

cluster analysis

data science

data-driven decision-making

evidence-based improvement cycles

heatmaps

researcher practitioner partnerships

visual data analytics

Open access/full-text available

en Yes

Peer reviewed

en Yes

ISSN

2398-5348

DOI

10.1108/ILS-09-2020-0212

URL

Official Publisher's Webpage (Emerald Insight)

Open Access Article (Columbia Academic Commons)

Citation

Bowers, A. J., & Krumm, A. E. (2021). Supporting the Initial Work of Evidence-Based Improvement Cycles Through a Data-Intensive Partnership. Information and Learning Sciences, 122(9/10), 629–650. https://doi.org/10.1108/ILS-09-2020-0212

Item sets

Handbook Chapter 20 Citations

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