Exploratory Data Analysis in Schools: A Logic Model to Guide Implementation

• Published in: International journal of education policy and leadership Vol. 17; no. 4
• Main Author: Courtney, Matthew B.
• Format: Journal Article
• Language: English
• Published: Vancouver Canadian Institute for Studies in Publishing Press Simon Fraser University 01.01.2021; PDK International, Faculty of Education at Simon Fraser University, and College of Education and Human Development at George Mason University
• Subjects: Academic Achievement; Action Research; Anniversaries; Archives & records; Assessment Literacy; Collaboration; Data Analysis; Data science; Data Use; Decision Making; Departments; Discovery Processes; Education; Educational Change; Educational Improvement; Educational leadership; Guidelines; Leaders; Leadership; Learning; Logical Thinking; Measurement Techniques; Outcomes of Education; Program Evaluation; Research Methodology; School Culture; Schools; Statistical Data; Students; Teachers
• ISSN: 1555-5062; 1555-5062
• DOI: 10.22230/ijepl.2021v17n4a1041

Exploratory data analysis (EDA) is an iterative, open-ended data analysis procedure that allows practitioners to examine data without pre-conceived notions to advise improvement processes and make informed decisions. Education is a data-rich field that is primed for a transition into a deeper, more purposeful use of data. This article introduces the concept of EDA as a necessary structure to be embedded in school activities by situating it within the literature related to data-driven decision making, continuous school improvement systems, and action research methodologies. It also provides a succinct six-part framework to guide practitioners in establishing EDA procedures.