Identifying and Guiding Students’ Behavioural Patterns in the Perspective of Online Civic Education Based on Big Data

[1]Jing, G. (2023). Research on the Innovation of Network Ideological and Political Education in Colleges and Universities in the Era of Big Data. Contemporary Education and Teaching Research, 4(8), 394-399.Search in Google Scholar

[2]Guo, Y. (2021). Research on the Path of Network Ideological and Political Education in Colleges and Universities from the Perspective of “Three Complete Education”. Scientific and Social Research, 3(4), 40-45Search in Google Scholar

[3]Deatherage, S., Servaty-Seib, H. L., & Aksoz, I. (2014). Stress, coping, and internet use of college students. Journal of American College Health, 62(1), 40-46.Search in Google Scholar

[4]Kittinger, R., Correia, C. J., & Irons, J. G. (2012). Relationship between Facebook use and problematic Internet use among college students. Cyberpsychology, Behavior, and Social Networking, 15(6), 324-327.Search in Google Scholar

[5]Chen, S. K. (2012). Internet use and psychological well-being among college students: A latent profile approach. Computers in Human Behavior, 28(6), 2219-2226.Search in Google Scholar

[6]Faghani, N., Akbari, M., Hasani, J., & Marino, C. (2020). An emotional and cognitive model of problematic Internet use among college students: The full mediating role of cognitive factors. Addictive behaviors, 105, 106252.Search in Google Scholar

[7]Chu, W. (2023). Research on the innovative path of college students’ network ideological and political education. education, 6(18), 18-23.Search in Google Scholar

[8]Lin, L., & Hai, S. (2016). Research on the multi-dimension ideological and political education of college students based on computer platform. RISTI (Revista Iberica de Sistemas e Tecnologias de Informacao), (E7), 244-252.Search in Google Scholar

[9]Zhang, Y. (2021, January). Research on the effectiveness of ideological and political education in colleges and universities based on mobile internet. In 2021 2nd International Conference on Education, Knowledge and Information Management (ICEKIM) (pp. 121-125). IEEE.Search in Google Scholar

[10]He, L. (2015, October). The New Trends and Strategies of College Ideological and Political Education in Internet Age. In International Conference on Education, Management and Information Technology (pp. 456-460). Atlantis Press.Search in Google Scholar

[11]Zhang, C. (2022). Research on the effectiveness of new media platforms in improving college students’ online ideological and political education. Forest Chemicals Review, 1135-1146.Search in Google Scholar

[12]Wucheng, Y., Ling, C., Qingdao, S., & Fan, L. (2016, September). Exploration of new methods of ideological and political education for college students: Integration of new media and construction of micro-environment. In The Fifth International Conference on E-Learning and E-Technologies in Education (ICEEE2016) (p. 77).Search in Google Scholar

[13]Chen, H. (2021, September). Research on the mode of Ideological and political education in Colleges and Universities Based on “Internet+”. In 2021 4th International Conference on Information Systems and Computer Aided Education (pp. 2709-2711).Search in Google Scholar

[14]Ren, W. (2021, January). Research on Ideological and Political Education of College Students From the Perspective of College Network Public Opinion. In 6th Annual International Conference on Social Science and Contemporary Humanity Development (SSCHD 2020) (pp. 15-19). Atlantis Press.Search in Google Scholar

[15]Shi, Q. (2021, May). Construction of Core Ideas of Ideological and Political Education for College Students Based on Modern Open and Distance Education. In 2021 2nd International Conference on Computers, Information Processing and Advanced Education (pp. 1375-1378).Search in Google Scholar

[16]Wang, X., Zhang, L., & Zhang, Y. (2021). A Review of Research on Online Ideological and Political Education of College Students in the Past Ten Years-Qualitative Analysis Based on Grounded Theory. International Journal of Education and Management, 6(1).Search in Google Scholar

[17]Anand, N., Thomas, C., Jain, P. A., Bhat, A., Thomas, C., Prathyusha, P. V., ... & Cherian, A. V. (2018). Internet use behaviors, internet addiction and psychological distress among medical college students: A multi centre study from South India. Asian journal of psychiatry, 37, 71-77.Search in Google Scholar

[18]Rinker, D. V., Krieger, H., & Neighbors, C. (2016). Social network factors and addictive behaviors among college students. Current addiction reports, 3, 356-367.Search in Google Scholar

[19]Kesheng, L., Yikun, N., Zihan, L., & Bin, D. (2020, May). Data mining and feature analysis of college students’ campus network behavior. In 2020 5th IEEE International Conference on Big Data Analytics (ICBDA) (pp. 231-237). IEEE.Search in Google Scholar

[20]Patterson, M. S., Gagnon, L. R., Vukelich, A., Brown, S. E., Nelon, J. L., & Prochnow, T. (2021). Social networks, group exercise, and anxiety among college students. Journal of American College Health, 69(4), 361-369.Search in Google Scholar

[21]Wang Tengfei,Xiao Baorong & Ma Weixiao. (2022). Student Behavior Data Analysis Based on Association Rule Mining. International Journal of Computational Intelligence Systems(1).Search in Google Scholar

[22]Veenu Rani & Munish Kumar. (2024). Transfer learning for human gait recognition using VGG19: CASIA-A dataset. Multimedia Tools and Applications(prepublish),1-15.Search in Google Scholar

[23]Sheng Bo,Chen Linfeng,Cheng Jian,Zhang Yanxin,Hua Zikai & Tao Jing. (2024). A markless 3D human motion data acquisition method based on the binocular stereo vision and lightweight open pose algorithm. Measurement113908-.Search in Google Scholar

[24]Huan He,Lei Wang,Enze Zhou,Ruizeng Wei & Shuqin Liu. (2024). Domain Adaptation Infrared Forest Fire Detection Method Based on YOLOv5 Framework. International Journal on Artificial Intelligence Tools(prepublish).Search in Google Scholar

[25]Moussa Belletreche,Nadjem Bailek,Mostafa Abotaleb,Kada Bouchouicha,Bilel Zerouali,Mawloud Guermoui... & El Sayed M. El kenawy. (2024). Hybrid attention-based deep neural networks for short-term wind power forecasting using meteorological data in desert regions. Scientific Reports(1),21842-21842.Search in Google Scholar