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

dc.contributor.authorAssanbayeva G.
dc.contributor.authorKadyrov Sh.
dc.date.accessioned2025-08-04T08:16:43Z
dc.date.available2025-08-04T08:16:43Z
dc.date.issued2020
dc.description.abstractIn 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.citationAssanbayeva G , Kadyrov Sh. / PRINCIPAL COMPONENT ANALYSIS AND A MULTILINGUAL CONSTRUCT TO DETERMINE THE UNDERGRADUATE MAJOR SELECTION FACTORS / SDU Bulletin: Natural and Technical Sciences / 2020
dc.identifier.issn2709-2631
dc.identifier.urihttps://repository.sdu.edu.kz/handle/123456789/1850
dc.language.isoen
dc.publisherSDU Bulletin: Natural and Technical Sciences
dc.subjectPrincipal Component Analysis
dc.subjectFactor Analysis
dc.subjectVarimax rotation
dc.titlePRINCIPAL COMPONENT ANALYSIS AND A MULTILINGUAL CONSTRUCT TO DETERMINE THE UNDERGRADUATE MAJOR SELECTION FACTORS
dc.typeArticle

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