Churn prediction in digital game-based learning using data mining techniques: Logistic regression, decision tree, and random forest-Reference-Cited by-同舟云学术

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Churn prediction in digital game-based learning using data mining techniques: Logistic regression, decision tree, and random forest

Published:2022-03 Issue: Volume:118 Page:108491
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Kiguchi Mai,Saeed Waddah^ORCID,Medi Imran^ORCID

Publisher

Elsevier BV

Subject

Software

Reference49 articles.

1. 10 Charts that explain the global education technology market;HolonIQ,2019

2. Learning and motivational effects of digital game-based learning (DGBL) for manufacturing education –The life cycle assessment (LCA) game;Perini;Comput. Ind.,2018

3. New report on virtual education: ‘it sure sounds good. As it turns out, it’s too good to be true;Strauss,2019

4. Benchmarks for subscription E-commerce;Recurly,2019

5. User segmentation for retention management in online social games;Fu;Decis. Support Syst.,2017

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