Classification of learning styles using behavioral features and twin support vector machine

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Nasiri Jalaledin; Mir AMIR MAHMOOD; Fatahi Somayeh

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Journal: Technology of Education Journal Year:2019 | Volume:13 | Issue:3 Page(s): 459-469

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Information Journal Paper

Title

Classification of learning styles using behavioral features and twin support vector machine

Author(s)

Nasiri Jalaledin | Mir AMIR MAHMOOD | Fatahi Somayeh | Issue Writer Certificate

Keywords

E-LearningQ1

Learning StyleQ2

Support Vector MachineQ1

MBTIQ1

Abstract

Students’ success is one of the prominent goals in the learning environments. In order to achieve this goal, paying attention to students’ Learning Style is essential. Being aware of students’ Learning Style helps to design an appropriate education method which improves student’ s performance in the learning environments. In this paper, the aim is to create a model for automatic prediction of Learning Styles. Therefore, two real datasets collected from an E-Learning environment which consists of 202 electrical and computer engineering students. Behavioral features were extracted from users’ interaction with E-Learning system and then Learning Styles were classified using twin Support Vector Machine. Twin Support Vector Machine is an extension of SVM which aims at generating two non-parallel hyperplanes. This classifier is not sensitive to imbalanced datasets and its training speed is fast. The results reveal that proposed method performs better than other used learning algorithms and it predicts Learning Styles with 95 percent accuracy.

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APA: Copy

Nasiri, Jalaledin, Mir, AMIR MAHMOOD, & Fatahi, Somayeh. (2019). Classification of learning styles using behavioral features and twin support vector machine. JOURNAL OF TECHNOLOGY OF EDUCATION (JOURNAL OF TECHNOLOGY AND EDUCATION), 13(3 ), 459-469. SID. https://sid.ir/paper/155368/en

Vancouver: Copy

Nasiri Jalaledin, Mir AMIR MAHMOOD, Fatahi Somayeh. Classification of learning styles using behavioral features and twin support vector machine. JOURNAL OF TECHNOLOGY OF EDUCATION (JOURNAL OF TECHNOLOGY AND EDUCATION)[Internet]. 2019;13(3 ):459-469. Available from: https://sid.ir/paper/155368/en

IEEE: Copy

Jalaledin Nasiri, AMIR MAHMOOD Mir, and Somayeh Fatahi, “Classification of learning styles using behavioral features and twin support vector machine,” JOURNAL OF TECHNOLOGY OF EDUCATION (JOURNAL OF TECHNOLOGY AND EDUCATION), vol. 13, no. 3 , pp. 459–469, 2019, [Online]. Available: https://sid.ir/paper/155368/en

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