Exploratory Factor Analysis (EFA) of Students’ Interest Based on Mathematics Content Domain

Abstract

Predicting students’ performance is essential in both educational and machine learning contexts. Prediction of students’ performance will facilitate in the development of relevant future study plans for students. In this paper, the objective of the study is to validate the main components of mathematical subject by using exploratory factor analysis (EFA). The study focus on mathematics subject since the subject is one of the mandatory or core subjects that is taken in the education public examination. A sample comprised 105 respondents selected from a certain school in Malaysia. The study validates the items of the questionnaire using IBM SPSS. The results show that the findings have managed to identify five factors with 80.402% of total variance using EFA.

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Author Information
Sharainie Sahrin, Universiti Malaysia Pahang, Malaysia
Noryanti Muhammad, Universiti Malaysia Pahang, Malaysia

• Category: Learning Experiences, Student Learning & Learner Diversity

Posted by James Alexander Gordon

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