International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Machine-Learning Based Solution for Enhancing the Performance of Undergraduate Research Projects

W. K. C. ThiwankaDepartment of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, Sri LankaSubasinghe M. P.Department of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, Sri LankaDissanayake D. M. M. A.Department of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, Sri LankaWijewardane W. A. M. B.Department of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, Sri LankaH. M. Samadhi ChathurangaDepartment of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, Sri LankaWishalya TisseraDepartment of Information Technology, Faculty of Computing, Sri Lanka Institute of Information Technology, Sri Lanka

Vol 7 No 11 (2023): Volume 7, Issue 11, November 2023 | Pages: 461-468

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 17-11-2023

doi Logo doi.org/10.47001/IRJIET/2023.711062

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Abstract

Research projects are a critical point of a student’s life as they help to generate new knowledge and understanding in a particular field. University students struggle immensely when completing their research projects due to lack of knowledge about the research process. In order to assist students in this process, “LEARNBOOST’’ progressive web application provides dashboards with valuable and meaningful insights about the research projects, research areas, research groups, publications and competitions. These dashboards will help the students to get a clear understanding about the past research projects in a more effective manner. In addition, the system provides a research area prediction system that predicts the students research area of interest when they provide the research topic. These predictions are generated using Natural Language Processing (NLP) Transformers so that the students’ students research topics will be identified more accurately. Moreover, “LEARNBOOST” student performance enhancement system provides a recommendation system that identifies student research area of interests through text inputs and suggest leading research papers where students can contribute to the further development of new ideas, technologies, and innovations. And through an abstract summarization, students can easily get the abstract summarized into few sentences. We present the results of a pilot study in which the proposed system was used to support a group of students and demonstrate its effectiveness in improving student performance.

Keywords

Research analysis, research area prediction, information dashboards, research paper recommendation systems, abstract summarization, student performance enhancement, progressive web application, natural language processing, recommendation systems.


Citation of this Article

W. K. C. Thiwanka, Subasinghe M. P., Dissanayake D. M. M. A., Wijewardane W. A. M. B., H. M. Samadhi Chathuranga, Wishalya Tissera, “Machine-Learning Based Solution for Enhancing the Performance of Undergraduate Research Projects” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 7, Issue 11, pp 461-468, November 2023. Article DOI https://doi.org/10.47001/IRJIET/2023.711062

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