The Comparison of Explanatory Factor Analysis and Clustering Analysis Which are Used for Determining Scale Factor Structure, and The Comparison Of Discriminant And Logistic Regression Analysis Techniques Which are Used for Data Classification

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Thesis Type: Postgraduate

Institution Of The Thesis: Gazi University, Eğitim Bilimleri Enstitüsü, Eğitim Bilimleri Enstitüsü, Turkey

Approval Date: 2016

Thesis Language: Turkish

Student: ZAFER ERTÜRK

Supervisor: MEHTAP ÇAKAN

Open Archive Collection: AVESIS Open Access Collection

Abstract:

The purpose of the study is compare the techniques of factor analysis, clustering analysis, discriminant analysis and logistic regression analysis in terms of the determination of factors affecting academic motivation of the university students and the classification of the students by their motivational level. The population of the study is Gazi University Gazi Education Faculty students who studied in 2014-2015 educational year and the sample of the study consists of 671 students (562 male and 109 female) who were selected by using convenient sampling. In order to determine academic motivational level of the university students, motivation sub-scale in Motivated Strategies for Learning Questionnaire, which was developed by Pintrich, Smith, Garcia and McKeachie (1991) was used. Personal information form that was created by the researcher was used for collecting data on students' socio-demographic information. SPSS 21 package program and LISREL 8.8 package program were used for analyzing data. In the analysis conducted by using SPSS 21, both explanatory factor analysis and clustering analysis produced same results on explaining factor structure of the scale. In terms of the classification of the students' motivational level, discriminant analysis and the logistic regression analysis performed 93,9% and %91,2% accurate classification performance, respectively.