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Discovering the Micro-Clusters From a Group of DHH Learners: An Approach Using Machine Learning Techniques

Discovering the Micro-Clusters From a Group of DHH Learners: An Approach Using Machine Learning Techniques

Anisha Poly, P. K. Nizar Banu
Copyright: © 2024 |Pages: 17
ISBN13: 9798369308684|ISBN13 Softcover: 9798369348161|EISBN13: 9798369308691
DOI: 10.4018/979-8-3693-0868-4.ch010
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MLA

Poly, Anisha, and P. K. Nizar Banu. "Discovering the Micro-Clusters From a Group of DHH Learners: An Approach Using Machine Learning Techniques." Transforming Education for Personalized Learning, edited by Afzal Sayed Munna, et al., IGI Global, 2024, pp. 159-175. https://doi.org/10.4018/979-8-3693-0868-4.ch010

APA

Poly, A. & Banu, P. K. (2024). Discovering the Micro-Clusters From a Group of DHH Learners: An Approach Using Machine Learning Techniques. In A. Munna, H. Alharahsheh, A. Ferrazza, & A. Pius (Eds.), Transforming Education for Personalized Learning (pp. 159-175). IGI Global. https://doi.org/10.4018/979-8-3693-0868-4.ch010

Chicago

Poly, Anisha, and P. K. Nizar Banu. "Discovering the Micro-Clusters From a Group of DHH Learners: An Approach Using Machine Learning Techniques." In Transforming Education for Personalized Learning, edited by Afzal Sayed Munna, et al., 159-175. Hershey, PA: IGI Global, 2024. https://doi.org/10.4018/979-8-3693-0868-4.ch010

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Abstract

The e-learning environment is essentially helpful for improving the autonomous learning skills of the DHH learners. Facing numerous resources online, DHH learners need support to choose the right learning materials. This can be done by recommending suitable learning objects to similar types of learners. Hence, this research attempts to explore the possibilities of forming micro clusters from the group of DHH learners to improve the recommendation. As a result of k-means, three different micro clusters are formed. So, from the initial analysis, it is identified that the formation of micro clusters is possible, and features such as communication and learning ways play an important role in forming the well-defined micro clusters. This will definitely help the teachers in traditional classrooms and recommendation engines in e-learning to explore the micro clusters of learners with same learning patterns and communication preferences to appropriately stream the right pedagogical methods.

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