• Engeneering and Natural science Department:Mathematics

    • PRINCIPAL COMPONENT ANALYSIS AND A MULTILINGUALCONSTRUCT TO DETERMINE THE UNDERGRADUATE MAJORSELECTION FACTORS

    Authors

    • Gulzhaukhar Assanbayeva Author

    DOI:

    https://doi.org/10.47344/0qw8wb89

    Keywords:

    Principal Component Analysis, Factor Analysis, Varimax rotation, Reliability, Major selection, Construct

    Abstract

    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.

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    Published

    2020-06-17

    Issue

    Vol. 52 No. 1 (2020): SDU Bulletin: Natural and Technical Sciences

    Section

    Computer Science

    How to Cite

    Assanbayeva, G. (2020). PRINCIPAL COMPONENT ANALYSIS AND A MULTILINGUALCONSTRUCT TO DETERMINE THE UNDERGRADUATE MAJORSELECTION FACTORS. Journal of Emerging Technologies and Computing, 52(1). https://doi.org/10.47344/0qw8wb89