PRINCIPAL COMPONENT ANALYSIS AND A MULTILINGUAL CONSTRUCT TO DETERMINE THE UNDERGRADUATE MAJOR SELECTION FACTORS

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dc.contributor.authorAssanbayeva G.
dc.contributor.authorKadyrov Sh.
dc.date.accessioned2024-02-05T09:23:26Z
dc.date.available2024-02-05T09:23:26Z
dc.date.issued2020
dc.description.abstractAbstract. In this article, we review mathematics behind well-known Principal Component Analysis from Linear Algebra implemented in various applied fields. As an application, we develop a construct to measure factors that affect college students in their major selection. This is a multilingual construct given in three languages, namely Kazakh, Russian, and English. To this end, we prepare a survey consisting of 27 Likert scale items in three languages and it is conducted among 314 undergraduate students in Kazakhstan. For dimensionality reduction, Principal Component Analysis is carried in python programming language which resulted in 9 major scales with only 22 elements. The overall reliability of the test is calculated to be 0,856. The nine scales are the effect of Uniform National Testing, state grant affect, personal interest affect, skills affect, occupation salary affect, teacher affect, external affect, university cost affect, parent’s affect.
dc.identifier.citationG. Assanbayeva , Sh. Kadyrov / PRINCIPAL COMPONENT ANALYSIS AND A MULTILINGUAL CONSTRUCT TO DETERMINE THE UNDERGRADUATE MAJOR SELECTION FACTORS / СДУ хабаршысы - 2020
dc.identifier.issn2709-2631
dc.identifier.urihttps://repository.sdu.edu.kz/handle/123456789/1181
dc.language.isoen
dc.publisherСДУ хабаршысы - 2020
dc.subjectPrincipal Component Analysis
dc.subjectFactor Analysis
dc.subjectVarimax rotation
dc.subjectReliability
dc.subjectMajor selection
dc.subjectConstruct
dc.subjectСДУ хабаршысы - 2020
dc.subject№1
dc.titlePRINCIPAL COMPONENT ANALYSIS AND A MULTILINGUAL CONSTRUCT TO DETERMINE THE UNDERGRADUATE MAJOR SELECTION FACTORS
dc.typeArticle

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