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ABSTRACT LIBRARY

AI Analysis of Student Learning Patterns in Online Platforms and its Academic and Psychological Impact on Engineering Students

Publisher: IEEE

Authors: Kowshik Viajinepalli, SRM Institute of science and technology S Kanaga suba raja, SRM Institute of Science and Technology * K Jeevan kumar, SRM Institute of science and technology

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Abstract:

Artificial intelligence has revolutionized education. It is certainly changing the world for academic and professional spaces around the globe at a very high level. The dependence of students on AI tools for research, project work, and even test-taking has increased a lot. In one way, this saves time; however, it can hamper the acquisition of hands-on skill and independent critical thinking that employers nowadays seek from candidates. The bottom line is that there is a need to rethink how we use learning with AI. We should think of it as a means for skill development rather than using it as a shortcut. There seems to be a lot of tension regarding online learning in general and engineering students in particular. Although AI offers personalized responses and care via learning tendency analysis, students also live through psychological pressure at the same time that comes from the aspect of continuous observation with little human interaction. Attempts to better the teaching and learning outcomes should harmoniously run together with a thorough understanding of what a student experiences. While enhancing the paradigm through AI, enabling specialized assistance according to different learning needs should not limit the scope or well-being of a person. This makes students up-to-date with the needs of the future, resolves the skill gap, and focuses on long-term academic and personal growth

Keywords: AI Learning Analytics, Engineering Education, Student Engagement, Online Learning, Psychological Impact, Predictive Models, Student Well-being, Algorithmic Transparency

Published in: 2024 Asian Conference on Communication and Networks (ASIANComNet)

Date of Publication: --

DOI: -

Publisher: IEEE

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