Hybrid Rasch Model Detection Variables for Dropout Analysis
27 Pages Posted: 4 Aug 2022 Publication Status: Preprint
Abstract
Dropout students is a severe problem in Higher Education (HE) in many countries. Student dropout has a tremendous negative impact, not only on individuals but also on university and socioeconomic. Consequently, preventing the educational dropout process is a considerable challenge for HE's institutions. Therefore, knowing factors that influence student dropout is an essential first step in preventing students from dropping out. This study using a mixed sequential exploratory method. There are three steps in this research including: (1) Seeking information directly from dropout students using questionnaires and indirect interviews; (2) Validation, there are two validations: validation by public opinion and stakeholders using questionnaire. Validity and reliability questionnaire using the Rasch Model; (3) Classifications of Variables, to classify these variables into dimensions factors using Categorical Principal Component Analysis (CATPCA). The findings reveal that personal economic factors, academic performance, academic satisfaction, and family economics are the most influential. The results of this paper are significant for universities in Indonesia, especially Central Java, to overcome the problem of dropping out of school so that they are more precise in making decisions. In addition, the results of this study are also helpful for further research as a basis for predicting students dropping out of the university.
Keywords: Dropout Students, Higher education, Rasch Model, CATPCA
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