Academic advising is limited in its ability to assist students in identifying academic pathways. Selecting a major and a university is a challenging process rife with anxiety. Students at high school are not sure how to match their interests with their working future or major. Therefore, high school students need guidance and support. Moreover, students need to filter, prioritize and efficiently get appropriate information from the web in order to solve the problem of information overload. This paper represents an approach for developing ontology-based recommender system improved with machine learning techniques to orient students in higher education. The proposed recommender system is an assessment tool for students' vocational strengths and weaknesses, interests and capabilities. The main objective of our ontology-based recommender system is to identify the student requirements, interests, preferences and capabilities to recommend the appropriate major and university for each one.
CITATION STYLE
Obeid, C., Lahoud, I., El Khoury, H., & Champin, P. A. (2018). Ontology-based Recommender System in Higher Education. In The Web Conference 2018 - Companion of the World Wide Web Conference, WWW 2018 (pp. 1031–1034). Association for Computing Machinery, Inc. https://doi.org/10.1145/3184558.3191533
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