• Ms.M.Premalakshmi
• Dr.D.Kanthimathi

During the COVID-19 pandemic, online learning has become one of the important ways of higher education because it is not confined by time and place. How to ensure the effectiveness of online learning has become the focus of education research, and the role of the “online learning community” cannot be ignored. In the context of the Internet of Things (IoT), we try to build up a new online learning community model: First, we introduce the Kolb learning style theory to identify different online learning styles; Second, we use a clustering algorithm to identify the nature of different learning style groups; and Third, we introduce the group dynamics theory to design the dimensions of the questionnaire and combine the Analytic Hierarchy Process (AHP) method to identify the key influencing factors of the online learning community. We take business administration majors and students in universities as an example. The results show that as a machine learning method, the clustering algorithm method is superior to the random construction method in identifying different learning style groups, and our method can well judge the importance of each factor based on hierarchical analysis and clarify the different roles of factors in the process of knowledge transfer. This study can provide a useful reference for the sustainable development of online learning in higher education.

"Impact of Online E-learning During the Pandemic Period", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 12, page no.e662-e665, December-2023, Available :http://www.jetir.org/papers/JETIR2312481.pdf

"Impact of Online E-learning During the Pandemic Period", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 12, page no. ppe662-e665, December-2023, Available at : http://www.jetir.org/papers/JETIR2312481.pdf