An Experimental Evaluation of Learning Based Platform to Analyze Mechanical Engineering Students Performance
The area of mechanical engineering requests a thorough comprehension of hypothetical ideas and functional applications. To meet this interest, there emerges a requirement for a learning platform customized explicitly for mechanical engineering students. The Learning Platform for Mechanical Engineering Students (LP-ME) is a powerful internet-based environment that coordinates different assets to take special care of the different necessities of students. It offers an organized educational program covering center points like thermodynamics, liquid mechanics, mechanics of materials, and machine plan, among others. Every subject is introduced through drawing in multimedia content, including intelligent reproductions, recordings, and movements, to work with better perception and maintenance. One of the vital elements of LP-ME is its versatile learning framework, which surveys the singular capability of students and gives customized recommendations to additional review. Through ordinary tests and assessments, students can keep tabs on their development and recognize regions for improvement. These intuitive encounters reinforce learning as well as develop critical thinking abilities fundamental for true engineering difficulties. Besides, LP-ME integrates industry-important substance and contextual analyses to overcome any barrier among the scholarly community and expert practice. Visitor addresses from industry specialists and potential open doors for entry level positions give students important bits of knowledge into latest things and advances in the field of mechanical engineering.
Authors
- S. Kanaga Suba Raja (ORCID: https://orcid.org/0009-0006-2291-7655)
- P. Kannan (ORCID: https://orcid.org/0009-0001-8892-6371)
- S Sowndhar
- Sasikumar PR
Publication Details
- Published
- 2024-12-12
- DOI
- https://doi.org/10.1109/icses63760.2024.10910834
- Primary Topic
- Online Learning and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 0.00