Abstract
To embrace why and how people learn and how to combine learner characteristics for recommending foreign language learning mobile applications (apps), this research presents a recommender system based on the relative importance weights of learner-related variables. In developing the system, 100 adult learners used 4-6 foreign language learning apps, resulting in 557 user-satisfaction data to calculate the relative importance of 14 learner-related variables in four categories: (a) demographic information, (b) motivational orientation for language learning (instrumental/integrative), (c) learning style, and (d) learning experience. The result showed that the model considering the relative importance weights of learner-related variables outperforms the dummy model in predicting users' satisfaction with the apps.
Original language | English |
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Title of host publication | 30th International Conference on Computers in Education Conference, ICCE 2022 - Proceedings |
Editors | Sridhar Iyer, Ju-Ling Shih, Ju-Ling Shih, Weiqin Chen, Weiqin Chen, Mas Nida MD Khambari, Mouna Denden, Rwitajit Majumbar, Liliana Cuesta Medina, Shitanshu Mishra, Sahana Murthy, Patcharin Panjaburee, Daner Sun |
Publisher | Asia-Pacific Society for Computers in Education |
Pages | 410-412 |
Number of pages | 3 |
ISBN (Electronic) | 9789869721493 |
State | Published - 28 Nov 2022 |
Event | 30th International Conference on Computers in Education Conference, ICCE 2022 - Kuala Lumpur, Malaysia Duration: 28 Nov 2022 → 2 Dec 2022 |
Publication series
Name | 30th International Conference on Computers in Education Conference, ICCE 2022 - Proceedings |
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Volume | 1 |
Conference
Conference | 30th International Conference on Computers in Education Conference, ICCE 2022 |
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Country/Territory | Malaysia |
City | Kuala Lumpur |
Period | 28/11/22 → 2/12/22 |
Bibliographical note
Funding Information:This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT)(No. 2020R1F1A1073469).
Publisher Copyright:
© 30th International Conference on Computers in Education Conference, ICCE 2022 - Proceedings.
Keywords
- Feature Importance
- Learner Variables
- Mobile Applications
- Recommender System