Author(s)

Huang Guiyuan ¹, Liu Hong ¹

Affiliation(s)

¹ Beibu Gulf University, Guangxi Qinzhou, 535011, China

Corresponding Author

Huang Guiyuan

ABSTRACT

In the epidemic situation of the corona virus disease, starting from the concept of deep learning, based on online learning experience, learning motivation and learning input and other variables, an influencing factor analysis framework, theoretical assumptions and corresponding measures of deep learning for college students were constructed. A one-stage survey was conducted on college students who conducted online learning at home during the epidemic to understand the situation of college students studying online at home and students' evaluation of online classrooms, and then a two-stage survey was conducted on students who will actively study online at the first stage Empirical analysis of influencing factors of college students' deep learning using structural equation model. The results prove that online learning experience, learning motivation and learning input all have a significant positive effect on deep learning. Therefore, colleges and universities need to continue to strengthen the construction of educational information infrastructure, integrate online education and teaching resources, improve teachers ’ability to apply information technology, set up rich teaching classrooms, increase teacher-student interaction, strengthen student participation in online classrooms, and strive to stimulate student learning Motivation, enhance students 'learning motivation, and cultivate students' deep learning ability.

KEYWORDS

Online deep learning, College students, Influencing factors, Epidemic period

CITE THIS PAPER

Huang Guiyuan, Liu Hong, Research on College Students' Online Deep Learning in the Epidemic Situation of Corona Virus Dissease. Adult and Higher Education (2022) Vol. 4: 78-88. DOI: http://dx.doi.org/10.23977/aduhe.2022.040514.

REFERENCES

[1] Mi Gaolei, Wu Jinwang. Design and Practice of Online Courses Based on Learning Experience--Take “Internet Finance” Public Courses as an Example [J]. Modern Educational Technology, 2017, 27(11): 92-98.
[2] Hu Yongbin, Huang Ronghuai. Learning experience in a smart learning environment: definition, elements and scale development [J]. Audio-visual Education Research, 2016, 37(12): 67-73.
[3] Udo G.J.,Bagchi K.K.,Kirs P.J., Using SERVQUAL to assess the quality of e-learning experience[J].Computers in Human Behavior,2011,27(3): 1272-1283
[4] Liu Zhongyu et al. Design of personalized learning model based on deep learning [J]. China Education Information, 2016, (08): 82-86.
[5] Chen Yi. Research on Deep Learning Based on Mobile Learning [J]. Journal of Jiangsu Radio and Television University, 2011, (01): 24-26.
[6] Li Yajiao et al. Comparative research on SNS platform in promoting deep learning [J]. Journal of Distance Education, 2012(05): 26-34.
[7] Fredricks JA, Blumenfeld PC, Paris AH. School engagement: Potential of the concept, state of the evidence [J]. Review of educational research, 2004, 74(1): 59-109
[8] Zhang Qi. Research on the correlation between college students' self-efficacy and deep learning in e-Learning environment [J]. Audio-visual Education Research, 2015, 04: 55-61
[9] Schaufeli WB, Martinez IM, Pinto AM, et al. Burnout and engagement in university across-national study [J]. Journal of cross-cultural psychology, 2002(5): 464-481.
[10] Hair, J. F., Black, W. C., Babin, B. J., and Anderson, R. E., Multivariate data analysis: A global perspective 7th ed. Prentice Hall, NJ, USA, 2010.
[11] Shih-chih Chen, Shih-Chi Liu. Understanding the Mediating Effects of Relationship Quality on Technology Acceptance: An Empirical Study of E-Appointment System [J].J Med Syst (2013)37: 9981
[12] Johanson J, Vahlne J E. The Internationalization process of the Firm-A Mdel of knowledge development and increasing foreign market commitments [J]. Journal of international business studies, 1977,8 (1): 23-32
[13] Wu Yajie. Factors that affect learners' online deep learning and their measurement research [J]. Audio-visual Education Research, 2017, (9): 57-63.
[14] Zhao Zongjin, Wang Xiaofang. Research on the deep learning level and related factors of college students based on the analysis of the survey of the academic conditions of Ocean University of China [J]. Educational Research and Experiment, 2013, (01): 73-77.
[15] Lv Linhai. The basic characteristics, influencing factors and promotion strategies of college students' deep learning [J]. China University Teaching, 2016, (11): 70-76.

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