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Technical and Individual Factors Influencing Mobile Learning in China’s Higher Education during the Outbreak of Covid-19

Author

Listed:
  • Sunze Yu

    (Universiti Malaysia)

  • Jie Zhang

    (Beifang Minzu University)

Abstract

The COVID-19 pandemic has swept the world like a tornado, caught unprepared of the Chinese higher education system to adapt to widespread unexpected disruption. It forced university students transfer to mobile learning during epidemic disease period, but students' learning efficiency had become a concern for teachers who were used to face-to-face pedagogy. This study applied mixed methods. Qualitative phase interviewed 12 freshmen with e-mail, then constructed a model by thematic analysis that ultimately affects mobile learning efficiency. Quantitative phase survived 367 freshmen by questionnaire and test previous model. The result of path analysis in quantitative phase indicated that individual factors and technological factors positively affect mobile learning acceptance, mobile learning acceptance positively affect mobile learning efficiency. The contributions of this study have strong implications for universities whom conducting mobile learning in other regions, that were still in the midst of the epidemic.

Suggested Citation

  • Sunze Yu & Jie Zhang, 2021. "Technical and Individual Factors Influencing Mobile Learning in China’s Higher Education during the Outbreak of Covid-19," Revista romaneasca pentru educatie multidimensionala - Journal for Multidimensional Education, Editura Lumen, Department of Economics, vol. 13(1), pages 41-53, March.
  • Handle: RePEc:lum:rev1rl:v:13:y:2021:i:1:p:41-53
    DOI: https://doi.org/10.18662/rrem/13.1/358
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    References listed on IDEAS

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    1. Arturo García-Santillán & Francisco Venegas-Martinez & Milka Elena Escalera Chávez & Arturo Córdova-Rangel, 2013. "Attitude toward Statistic in College Students (An Empirical Study in Public University)," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 2(1), pages 1-4.
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      More about this item

      Keywords

      Covid-19; mobile learning; mix-method; path analysis; China;
      All these keywords.

      JEL classification:

      • I2 - Health, Education, and Welfare - - Education

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