Closing the Loop: Automated Data-Driven Cognitive Model Discoveries Lead to Improved Instruction and Learning Gains

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: Liu, Ran; Koedinger, Kenneth R.
Date: 2017
In publication: Journal of Educational Data Mining
Volume: 9
Issue: 1
Pages: 25-41
Resource type: en Research/Scholarly Media
Resource status/form: en Published Text
Scholarship genre: en Empirical
Language: en
Open access/full-text available: en Yes
Peer reviewed: en Yes
ISSN: 2157-2100
DOI: 10.5281/zenodo.3554625
URL: Open Access Publisher's Webpage (Zenodo)
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
Abbreviation: JEDM
Rights: Copyright (c) 2017 JEDM - Journal of Educational Data Mining

Comments

No comment yet! Be the first to add one!

Name

Website

Comment

To prove you are not a robot, answer this question: How much is 4 plus 1?

I agree with terms of use and I accept to free my contribution under the licence CC BY-SA.