Journal article
J. Gao, X. Huang, A.K. Dubé, N.G. Lobczowski
Proceedings of the 18th International Conference of the Learning Sciences, 2024
Proceedings of the 18th International Conference of the Learning Sciences, 2024
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APA
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Gao, J., Huang, X., Dubé, A. K., & Lobczowski, N. G. (2024). Exploring Duolingo User’s Learning Experience Through Text Mining. Proceedings of the 18th International Conference of the Learning Sciences. https://doi.org/10.22318/icls2024.669479
Chicago/Turabian
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Gao, J., X. Huang, A.K. Dubé, and N.G. Lobczowski. “Exploring Duolingo User’s Learning Experience Through Text Mining.” Proceedings of the 18th International Conference of the Learning Sciences (2024).
MLA
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Gao, J., et al. “Exploring Duolingo User’s Learning Experience Through Text Mining.” Proceedings of the 18th International Conference of the Learning Sciences, 2024, doi:10.22318/icls2024.669479.
BibTeX Click to copy
@article{j2024a,
title = {Exploring Duolingo User’s Learning Experience Through Text Mining},
year = {2024},
journal = {Proceedings of the 18th International Conference of the Learning Sciences},
doi = {10.22318/icls2024.669479},
author = {Gao, J. and Huang, X. and Dubé, A.K. and Lobczowski, N.G.}
}
This study of 24,390 Duolingo reviews employed text mining to analyze users' motivational and cognitive expressions, classifying feedback by thumbs-up count for agreement levels. The findings underscore a substantial difference in feedback among agreement groups, particularly in users’ cognitive expression. Reviews garnering more thumbs up proved more relevant for learning, emphasizing their importance in tailoring platforms for educational needs.
