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Evaluation of college admissions: a decision tree guide to provide information for improvement

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  • Ying-Sing Liu

    (Chaoyang University of Technology)

  • Liza Lee

    (Chaoyang University of Technology)

Abstract

This study uses decision trees to analyze the admissions and enrollment of Taiwan’s 5-year junior colleges to explore the reasons that students might fail in an exam-free admissions process, propose methods for improvement, and view the implementation of the pedagogical theory of multiple intelligences. The college admissions system may produce confusion in Taiwan. Schools in metropolitan areas retain an advantage for screening talent across multiple abilities, and colleges in agricultural counties may unintentionally marginalize people, resulting in insufficient enrollment or an inverse selection of talent. It has been suggested that increasing the number of schools in metropolitan areas will reduce the rates of enrollment failure and improve the compulsory education environment that many are forced to attend.

Suggested Citation

  • Ying-Sing Liu & Liza Lee, 2022. "Evaluation of college admissions: a decision tree guide to provide information for improvement," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-12, December.
    • Handle: RePEc:pal:palcom:v:9:y:2022:i:1:d:10.1057_s41599-022-01413-z
    DOI: 10.1057/s41599-022-01413-z
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    References listed on IDEAS

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    1. Nelson Ositadimma Oranye, 2016. "The Validity of Standardized Interviews Used for University Admission Into Health Professional Programs," SAGE Open, , vol. 6(3), pages 21582440166, July.
    2. Seungwoo Han, 2022. "Identifying the roots of inequality of opportunity in South Korea by application of algorithmic approaches," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-10, December.
    3. W. O. Dale Amburgey & John Yi, 2011. "Using Business Intelligence in College Admissions: A Strategic Approach," International Journal of Business Intelligence Research (IJBIR), IGI Global, vol. 2(1), pages 1-15, January.
    4. Gengjun Yao & Jingwei Wang & Baoguo Cui & Yunlong Ma, 2022. "Quantifying effects of tasks on group performance in social learning," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-11, December.
    5. Xiangxiang Zeng & Sisi Yuan & You Li & Quan Zou, 2014. "Decision Tree Classification Model for Popularity Forecast of Chinese Colleges," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-7, April.
    6. Liza Lee & Ying-Sing Liu, 2021. "Use of Decision Trees to Evaluate the Impact of a Holistic Music Educational Approach on Children with Special Needs," Sustainability, MDPI, vol. 13(3), pages 1-6, January.
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