Closing the Loop: Automated Data-Driven Cognitive Model Discoveries Lead to Improved Instruction and Learning Gains
Item
Title
Closing the Loop: Automated Data-Driven Cognitive Model Discoveries Lead to Improved Instruction and Learning Gains
Abstract/Description
As the use of educational technology becomes more ubiquitous, an enormous amount of learning process data is being produced. Educational data mining seeks to analyze and model these data, with the ultimate goal of improving learning outcomes. The most firmly grounded and rigorous evaluation of an educational data mining discovery is whether it yields better student learning when applied. Such an evaluation has been referred to as
Author/creator
Date
In publication
Volume
9
Issue
1
Pages
25-41
Resource type
Research/Scholarly Media
Resource status/form
Published Text
Scholarship genre
Empirical
Open access/full-text available
Yes
Peer reviewed
Yes
ISSN
2157-2100
Citation
Liu, R., & Koedinger, K. R. (2017). Closing the Loop: Automated Data-Driven Cognitive Model Discoveries Lead to Improved Instruction and Learning Gains. Journal of Educational Data Mining, 9(1), Article 1. https://doi.org/10.5281/zenodo.3554625
Rights
Copyright (c) 2017 JEDM - Journal of Educational Data Mining
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