Cluster Change Analysis to Assess the Effectiveness of Speaking Skill Techniques using Machine Learning

Nunik Herani Wulandari(1), Vega Purwayoga(2*),

(1) Universitas Siliwangi
(2) Universitas Siliwangi
(*) Corresponding Author

Abstract


This study aims to compare effective teaching methods for speaking using machine learning. The classes used in this study consisted of three classes: conventional, vlog project, and picture series. The data used were students' pre-test and post-test scores. The machine learning algorithm used is K-Means. K-Means clusters the pre-test and post-test data. The results of K-Means clustering on the pre-test and post-test identified the differences in student groups between the pre-test and post-test. Students who experienced the most cluster movement were those in the vlog project class, the conventional class, and the picture series class.


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DOI: https://doi.org/10.24071/ijasst.v7i1.9667

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