N, Mathimagal. and S, Jayalakshmi. (2021) Improvement of affected Intellectual behavior student's by social media using collaboration learning method. In: 2021 Second International Conference on Electronics and Sustainable Communication Systems (ICESC), Coimbatore, India.
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Abstract
Social Media (SM) is a web-based service that gives a unique option for creating public or private profile in a limited system. It helps to build community sense through networking, knowledge co-construction through cooperation, and room for individualization through individualization while learning has been differentiated to accumulate for diverse learning requirements. According to SM application, there are negative aspects which get related over increment of connectivity but there are several positive characteristics present in the SM that have positional for engaging students with an environment of quality learning. These applications of SM have created an online environment, the user present in the application has performed as creator instead of passive users whereas it allowed users to share and exchange their idea in terms of read and write. In the case of education, the advancement of SM is to recognize there collaboration and communication. Hence, this paper is performed based on the examining student intellectual behavior impact performance by SM in college present over Chennai and focused the affected students as Research Learner (RL) to build up their learning behavior using the same SM with the methodology of Collaborative Learning (CL). Moreover, the identification of analyzing the positive and negative aspects of students are done through Google form survey done to 837 students presented with questionnaires based on variable like SM improve academic performance, SM build good relationship, SM create introvert, SM cause health problem and time spending in SM are observed while using SM to the student of its institute. This research has revealed that use of SM sites have affected an academic performance for the students by engagement and collaborative learning through SM which can be predicted by exact dimension reduction using Sparse Principal Components Analysis (SPCA).
Item Type: | Conference or Workshop Item (Paper) |
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Subjects: | Computer Science > Computer Networks |
Divisions: | Computer Science |
Depositing User: | Mr IR Admin |
Date Deposited: | 18 Sep 2024 08:45 |
Last Modified: | 18 Sep 2024 08:45 |
URI: | https://ir.vistas.ac.in/id/eprint/6360 |