Volume 8, Issue 6, November 2019, Pages: 359-366
Received: Nov. 2, 2019;
Published: Dec. 12, 2019
Views 424 Downloads 210
Enyan Wang, School of Economics and Management, Harbin Institute of Technology at Weihai, Weihai, China
Dequan Zheng, School of Economics and Management, Harbin Institute of Technology at Weihai, Weihai, China; School of Management, Harbin Institute of Technology, Harbin, China
Mobile-learning is not limited by time and place, it has a lot of advantages compared with traditional learning methods, so it has become a hot spot of education model reform. Teachers are also trying and researching on mobile-learning assisted instruction. However, the current research on mobile-learning mainly focuses on the students' users. In contrast, the behavior habits and use intentions of teachers' assisted instruction are very different, and teachers have a great impact on the use intentions of students' mobile-learning. In this study, through combing the theoretical literature of mobile-learning influencing factors, we use TAM model to build a mobile-learning influencing factor model, and put forward the corresponding research hypothesis. On the basis of this model, a questionnaire about the influencing factors of mobile-learning for university teachers is designed. The relevant data obtained from the questionnaire are analyzed by SPSS and Amos data analysis software. Through the analysis, it is concluded that perceived usefulness, perceived ease of use, resource optimization, future teaching tendency and social impact all have an impact on teachers' willingness to use mobile-learning, and relevant suggestions are putted forward.
Research on the Influence Factors of the University Teachers' Mobile-learning, Education Journal.
Vol. 8, No. 6,
2019, pp. 359-366.
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Zhou, Li. Blended mobile learning in theatre arts classrooms in higher education [J]. Innovations in Education and Teaching International, 2019, 56 (3), pp. 25-31.
Deniz Mertkan Gezgin. The Effect of Mobile Learning Approach on University Students' Academic Success for Database Management Systems Course [J]. International Journal of Distance Education Technologies (IJDET), 2019, 17 (1), pp. 21-32.
Liu Gang, Hu Shuixing, Gao Hui. Micro change of mobile learning and its countermeasures [J]. Modern Education Technology 2014, 24 (02), pp. 34-41.
Zhu Xuewei, Zhu Yu, Xu Xiaoli. Research and design of mobile learning platform supported by wechat [J]. Distance Education in China, 2014 (04), pp77-83.
Wang cixiao, Dong Qian, Wu Feng. Meta analysis of the impact of mobile learning on learning outcomes [J]. Distance Education Journal, 2018, 36 (02), pp 67-75.
Sun Chui, Ao Jianhua, Sheng Xue Feng. "Ubiquitous" teaching mode in Internet + environment [J]. computer education. 2019 (04), pp. 125-128+140.
Jing Hui, Zhang Yi, Zhou Gang. Mobile learning hybrid model research [J]. Journal of Jishou University (SOCIAL SCIENCES EDITION), 2018, 39 (S1), pp. 134-137.
Shakeel Iqbal, Dr. Zeeshan Ahmed Bhatti. An Investigation of UniversityStudent Readiness towards M-learning using Technology Acceptance Model [J]. International Review of Research in Open and Distributed Learning, 2015, 16 (4), pp. 454-466.
Hossein Mohammadi. Social and individual antecedents of m-learning adoptionin Iran [J]. Computers in Human Behavior, 2015, 3 (49), pp. 191–207.
Chung, H. H., Chen, S. C., & Kuo, M. H. A study of efl college stu-dents’acceptance of mobile learning. Procedia - Social and Behavioral Scien-ces, 2015, 176. pp. 333-339.
Zhang Xin, Li Qing. Business model analysis of mobile learning based on wechat [J]. Journal of Beijing University of Posts and Telecommunications (SOCIAL SCIENCES EDITION). 2018, 20 (05, pp. 99-108.
Zheng Lanqin, Cui Panpan, Li Xin. Can mobile learning promote learning performance? A meta-analysis based on 92 studies of International English journals in 2011-2017 [J]. Modern Distance Education Research, 2018 (06), pp. 45-54.
Ammar Khader Mohammad Almasri. A Hybrid Proposed Framework Based on QualityFactors (QF) and Technology Acceptance Model (TAM) for Mobile Learning Process: Higher Education Students in Jordanian Universities [J]. International Journalof Information, Business and Management, 2015, 7 (3), pp. 75-80.
TanW H, Sim J. Determinants of mobile learning adoption: an empirical analysis [J]. Journal of Computer Information Systems, 2012, pp. 82-91.