Understanding of Digital Learning Sources with the Heutagogy Approach using the K-Means and Naive Bayes Methods

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Henry Praherdhiono, Eka Pramono Adi, Riri Nada Devita

2018 2018 4th International Conference on Education and Technology, ICET 2018 Conference paper Cited by 5

Abstract

The heutagogical approach is a learning approach that is consistent with the characteristics of independent students. This approach makes students become more active and independent in choosing, developing, and utilizing learning resources that are needed in the learning process. At the State University of Malang the heutagogical approach was carried out with digital learning sources in the form of the LSM SIPEJAR website and MOOC. On the website students can create and develop materials independently. The level of student understanding resulting from the learning process through the website will be evaluated using the k-means and naive bayes methods. Based on the results of clustering based on questionnaire data that has been distributed, obtained 3 classes in the form of students' level of understanding, namely Very Understanding, Understanding, and Understanding. This shows that the heutagogy approach in learning at Malang State University can improve students' understanding of the material being studied. While the results of the classification using Naive Bayes produce very good accuracy of 97.82%. © 2018 IEEE.

Affiliations

Department of Educational Technology, Universitas Negeri Malang, Malang, Indonesia