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

Authors

  • Sunze Yu Universiti Malaysia
  • Jie Zhang Beifang Minzu University

DOI:

https://doi.org/10.18662/rrem/13.1/358

Keywords:

Covid-19, mobile learning, mix-method, path analysis, China

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.

References

Abdulrahman, R. A., Eardley, W. A., & Soliman, A. (2017). The Uses of Mobile Learning Citizen Engagement and the Fostering of Smart Cities. In L. G. Chova, A. L. Martinez, & I. C. Torres (Eds.), Inted2017: 11th International Technology, Education and Development Conference (pp. 2973-2978). https://doi.org/10.21125/inted.2017.0787

Briz-Ponce, L., Pereira, A., Carvalho, L., Juanes-Méndez, J. A., & García-Peñalvo, F. J. (2017). Learning with mobile technologies–Students’ behavior. Computers in Human Behavior, 72, 612-620. https://doi.org/10.1016/j.chb.2016.05.027

Bryman, A. (2006). Integrating quantitative and qualitative research: how is it done? Qualitative research, 6(1), 97-113. https://doi.org/10.1177/1468794106058877

Chavoshi, A., & Hamidi, H. (2019). Social, individual, technological and pedagogical factors influencing mobile learning acceptance in higher education: A case from Iran. Telematics and Informatics, 38, 133-165. https://doi.org/ 10.1016/j.tele.2018.09.007

Cochrane, T., & Narayan, V. (2016). Design considerations for mobile learning. In C. M. Reigeluth, B. J. Beatty, R. D. Myers (Eds.), Instructional-Design Theories and Models, Volume IV: The Learner-Centered Paradigm of Education (1st Ed., Chapter 14, p. 385). Routledge.

Cohen, A., & Ezra, O. (2018). Development of a contextualised MALL research framework based on L2 Chinese empirical study. Computer Assisted Language Learning, 31(7), 764-789. https://doi.org/10.1080/09588221.2018.1449756

Creswell, J. W. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications. http://www.drbrambedkarcollege.ac.in/sites/default/files/research-design-ceil.pdf

Education, N. R. D. O. (2020). Notice from the Department of Education of the Autonomous Region on strengthening the prevention and control of the new crown pneumonia epidemic and continuing to postpone the start of the spring 2020 school year in schools, colleges and kindergartens across the region. Ningxia Regional Department of Education. http://jyt.nx.gov.cn/sviewp/6B82E06B-8185-4240-AC5E-86326C98DF79

Flynn, L. R., & Goldsmith, R. E. (2013). Case studies for ethics in academic research in the social sciences. Sage.

Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382–388. https://doi.org/ 10.1177/002224378101800313

Fury, C. A., & Harrison, P. L. (2011). Impact of flood events on dolphin occupancy patterns. Marine Mammal Science, 27(3), E185-E205. https://doi.org/ 10.1111/j.1748-7692.2010.00447.x

García-Santillán, A., Venegas-Martinez, F., & Escalera, M. E. (2013). Attitude toward Statistic in College Students (An Empirical Study in Public University). Journal of Statistical and Econometric Methods, 2(1), 43-60. http://www.scienpress.com/Upload/JSEM/Vol%202_1_4.pdf

Glaser Barney, G., & Strauss Anselm, L. (1967). The discovery of grounded theory: strategies for qualitative research. New York, Adline de Gruyter, 17(4), 364. https://journals.lww.com/nursingresearchonline/Citation/1968/07000/The_Discovery_of_Grounded_Theory__Strategies_for.14.aspx.

Halcomb, E. J., & Hickman, L. (2015). Mixed methods research. Nursing Standard, 29(32), 41-47. https://doi.org/ 10.7748/ns.29.32.41.e8858

Ivankova, N. V. (2014). Mixed methods applications in action research. Sage.

Kalina, C., & Powell, K. (2009). Cognitive and social constructivism: Developing tools for an effective classroom. Education, 130(2), 241-250. https://www.semanticscholar.org/paper/Cognitive-and-Social-Constructivism%3A-Developing-for-Powell-Kalina/a716ae15717001889732f937a37f7292faf1d107?p2df

Krause, K., Bochner, S., & Duchesne, S. (2006). Educational Psychology for Learning and Teaching. Cengage Learning Australia.

Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and psychological measurement, 30(3), 607-610. https://doi.org/ 10.1177/001316447003000308

Labaree, R. (2013). Organizing your social sciences research paper. USC Library. https://libguides.usc.edu/writingguide

Lancet. (2020). No more normal. Lancet, 396(10245), 143. https://doi.org/10.1016/S0140-6736(20)31591-9

Onwuegbuzie, A. J., & Combs, J. P. (2011). Data analysis in mixed research: A primer. International Journal of Education, 3(1), 1. https://doi.org/10.5296/ije.v3i1.618

Reynolds, B. L., & Anderson, T. A. (2015). Extra-dimensional in-class communications: Action research exploring text chat support of face-to-face writing. Computers and Composition, 35, 52-64. https://doi.org/ 10.1016/j.compcom.2014.12.002

Salkind. (2003). Exploring Research. Pearson Education International Upper Saddle River. http://fbs.dinus.edu/repository/docs/ajar/Neil_J._Salkind_2012_-_Exploring_Research_.pdf

Schreiber, J. B., Nora, A., Stage, F. K., Barlow, E. A., & King, J. (2006). Reporting structural equation modeling and confirmatory factor analysis results: A review. The Journal of educational research, 99(6), 323-338. https://doi.org/ 10.3200/JOER.99.6.323-338

Shadiev, R., Hwang, W. -Y., & Huang, Y. -M. (2017). Review of research on mobile language learning in authentic environments. Computer Assisted Language Learning, 30(3-4), 284-303. https://doi.org/10.1080/09588221.2017.1308383

Sharma, B. (2016). A focus on reliability in developmental research through Cronbach’s Alpha among medical, dental and paramedical professionals. Asian Pacific Journal of Health Sciences, 3(4), 271-278. https://doi.org/10.21276/apjhs.2016.3.4.43

Steffe, L. P., & Gale, J. E. (1995). Constructivism in education. Lawrence Erlbaum Hillsdale. http://emis.matem.unam.mx/journals/ZDM/zdm982r2.pdf

Tashakkori, A., & Creswell, J. W. (2008). Mixed methodology across disciplines. Journal of Mixed Methods Research, 2(1), 3-6. https://doi.org/10.1177/1558689807309913

WHO. (2020). Statement on the second meeting of the International Health Regulations (2005) Emergency Committee regarding the outbreak of novel coronavirus (2019-nCoV). WHO. https://www.who.int/news/item/30-01-2020-statement-on-the-second-meeting-of-the-international-health-regulations-(2005)-emergency-committee-regarding-the-outbreak-of-novel-coronavirus-(2019-ncov)

Wu, T. -T. (2014). The use of a mobile assistant learning system for health education based on project-based learning. CIN: Computers, Informatics, Nursing, 32(10), 497-503. https://doi.org/10.1097/CIN.0000000000000089

Zhonggen, Y., Ying, Z., Zhichun, Y., & Wentao, C. (2019). Student satisfaction, learning outcomes, and cognitive loads with a mobile learning platform. Computer Assisted Language Learning, 32(4), 323-341. https://doi.org/ 10.1080/09588221.2018.1517093

Downloads

Published

2021-03-16

How to Cite

Yu, S., & Zhang, J. (2021). Technical and Individual Factors Influencing Mobile Learning in China’s Higher Education during the Outbreak of Covid-19. Revista Romaneasca Pentru Educatie Multidimensionala, 13(1), 41-53. https://doi.org/10.18662/rrem/13.1/358