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A Study on the Classification of Hybrid Courses in Higher Vocational Colleges Based on Latent Class Analysis

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  • Xiaohong Yang

    (Northwest Normal University, China)

  • Chengdong Zheng

    (Northwest Normal University, China & Qingdao Vocational and Technical College of Hotel Management, China)

  • Jingwen Wang

    (Northwest Normal University, China)

  • Shujuan Yin

    (Northwest Normal University, China)

Abstract

This study examines latent classes of higher vocational hybrid courses and their influencing factors using bidirectional online behavioral data from 592 courses through latent class analysis (LCA) and multinomial logistic regression. Results identify five categories: comprehensive active (21.6%), teacher-dominated (18.9%), assignment-driven (28.9%), test-driven (9.6%), and peripheral participation (20.9%). Online activity frequency negatively predicts Assignment-Driven and Peripheral Participation types; total student access negatively predicts the Test-Driven type, whereas average learning duration positively predicts it. These findings provide data-driven criteria for optimizing hybrid course design and strategies for improving vocational education quality.

Suggested Citation

  • Xiaohong Yang & Chengdong Zheng & Jingwen Wang & Shujuan Yin, 2026. "A Study on the Classification of Hybrid Courses in Higher Vocational Colleges Based on Latent Class Analysis," International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), IGI Global Scientific Publishing, vol. 21(1), pages 1-22, January.
    • Handle: RePEc:igg:jwltt0:v:21:y:2026:i:1:p:1-22
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