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What is Educational Data Mining (EDM)

Handbook of Research on Equity in Computer Science in P-16 Education
Educational data mining is defined as an approach of applying machine learning or data mining algorithms on log data generated from educational environments in order to understand learners and learning environments ( Romero, López, Luna, & Ventura, 2013 ).
Published in Chapter:
A Conceptual Educational Data Mining Model for Supporting Self-Regulated Learning in Online Learning Environments
Eric Araka (Technical University of Kenya, Kenya), Robert Oboko (University of Nairobi, Kenya), Elizaphan Maina (Kenyatta University, Kenya), and Rhoda K. Gitonga (Kenyatta University, Kenya)
DOI: 10.4018/978-1-7998-4739-7.ch016
Abstract
Self-regulated learning is attracting tremendous researches from various communities such as information communication technology. Recent studies have greatly contributed to the domain knowledge that the use self-regulatory skills enhance academic performance. Despite these developments in SRL, our understanding on the tools and instruments to measure SRL in online learning environments is limited as the use of traditional tools developed for face-to-face classroom settings are still used to measure SRL on e-learning systems. Modern learning management systems (LMS) allow storage of datasets on student activities. Subsequently, it is now possible to use Educational Data Mining to extract learner patterns which can be used to support SRL. This chapter discusses the current tools for measuring and promoting SRL on e-learning platforms and a conceptual model grounded on educational data mining for implementation as a solution to promoting SRL strategies.
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More Results
Advancing Research in Game-Based Learning Assessment: Tools and Methods for Measuring Implicit Learning
An emerging research discipline that provides a suite of methods and research approaches from statistics, machine learning, and data mining to analyze data collected during teaching and learning.
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Leveraging Learning Analytics to Support Learners and Teachers: An Introduction
It delves into learning outcomes through mining and analyzing data as taught.
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Navigating the AI Landscape: Student and Teacher Perceptions of AI in Assessments in High School and College Settings
The process of analyzing educational data to improve learning outcomes. EDM can use AI techniques to identify patterns and provide insights into student learning behaviors.
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The Importance of Teacher Bridging in Game-Based Learning Classrooms
An emerging research discipline that provides a suite of methods and research approaches from statistics, machine learning, and data mining to analyze data collected during teaching and learning.
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New Personal Learning Ecosystems: A Decade of Research in Review
A research field concerned with the application of data mining, machine learning, and statistics to information generated from educational settings.
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