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Subject: search.filters.subject.University Students

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    Personalized Adaptive System for Enhancing University Student Performance in Sri Lanka
    (Institute of Electrical and Electronics Engineers Inc., 2025) Dissanayake, N; Samarakoon, C; Wickramasinghe, D; Pathirana, M; Gamage N.D.U; Attanayaka, B
    The growing need for personalized learning strategies has driven the development of data-driven solutions to meet the diverse needs of Sri Lankan university students. A key challenge lies in identifying optimal learning paths that align with individual capabilities, learning styles, and engagement behaviors to improve academic performance. While previous research has explored generalized learning models, these often fail to adapt to the specific demands of individual learners. Traditional strategies lack personalization, resulting in inconsistent learning progress. To address this gap, the research introduces an assistive, data-driven approach that leverages Self-Organizing Maps (SOMs), Adaptive Learning (AL), Content-Based Filtering, Graph Neural Networks (GNNs), and Social Network Analysis (SNA) to create optimized, personalized learning strategies. Clustering algorithms and predictive analysis were used to segment learners and deliver tailored interventions based on their behavior. The proposed system integrates advanced machine learning techniques to enhance student engagement and improve overall academic outcomes through personalized pathways.
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    Escort - Natural Language Processing Based University Students Guidance System
    (IEEE, 2022-12-26) Srinivasan, D; Uthayakumar, A; Thiyagalingam, P; Ravindran, S; De Silva, H; Kasthururarthna, D
    Universities play a significant role in students’ lives and aim to provide the best education, knowledge, and experience. However, university students face many difficulties during their university life including language, communication issues, and the inability to get proper guidance for education and career improvement. This paper proposes an approach to overcome these issues. With the help of Natural Language Processing (NLP), in this paper, several solutions are recommended for the mentioned issues. First, a chatbot helps to communicate with the university administration, where students can ask relevant administrative-related questions. A recommendation system is developed to provide solutions for their psychological issues. Another recommendation system is built for career guidance which will help students to identify the future career of their interest, and the provided mentors will be able to guide them. Another recommendation system identifies the performance of students in each module according to their performance level. The system recommends learning materials to improve their level. With these components, ESCORT – A university students’ guidance system, will make students’ life easier and more efficient.