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A case-based reasoning and ontology-based hybrid recommender system for student orientation in higher education.

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Title: A case-based reasoning and ontology-based hybrid recommender system for student orientation in higher education.
Authors: Lahoud, Christine (AUTHOR), Moussa, Sherin (AUTHOR), Obeid, Charbel (AUTHOR), Khoury, Hicham El (AUTHOR)
Source: Educational Technology Research & Development. Aug2025, Vol. 73 Issue 4, p2495-2522. 28p.
Subjects: College student orientation, Higher education, Data analysis, Recommender systems, Ontology, Vocational guidance, Case-based reasoning, Lebanese
Geographic Terms: Beirut (Lebanon)
Abstract: The orientation programs in most of the schools do not mitigate the diverse necessities of students. In addition, the instability of the labor market and the complexity of life have a great impact on young people's career choices. Faced with these concerns, high school students get confused when choosing a college major. Furthermore, the explosion of data on the Internet has caused most of the Internet users to make possible unsuitable decisions when browsing the Web, due to their inability to handle such large amounts of data. In this paper, the Case-based reasoning, and Ontology-based Hybrid Recommender System (COHRS) is proposed to assist high school students deciding the appropriate university/college, university major and career domain that best fit their preferences. COHRS uniquely combines case-based reasoning, collaborative filtering, knowledge base and ontology to explore the top N recommendations based on their fields of interest. The system has been evaluated on Lebanese students through a real-life dataset collected from different Lebanese cities. The first tests carried out on 60 high school students in Beirut city showed an average satisfaction level of 91.7% of the recommended results from the proposed system and 93.3% of them found the system very useful. The proposed system achieved an average accuracy level of 98% and 95% to retrieve the most similar cases and to extract appropriate recommendations respectively, which provides a very insightful capability to guide high school students in their future directions. [ABSTRACT FROM AUTHOR]
Copyright of Educational Technology Research & Development is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: A case-based reasoning and ontology-based hybrid recommender system for student orientation in higher education.
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  Data: <searchLink fieldCode="DE" term="%22College+student+orientation%22">College student orientation</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+education%22">Higher education</searchLink><br /><searchLink fieldCode="DE" term="%22Data+analysis%22">Data analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Recommender+systems%22">Recommender systems</searchLink><br /><searchLink fieldCode="DE" term="%22Ontology%22">Ontology</searchLink><br /><searchLink fieldCode="DE" term="%22Vocational+guidance%22">Vocational guidance</searchLink><br /><searchLink fieldCode="DE" term="%22Case-based+reasoning%22">Case-based reasoning</searchLink><br /><searchLink fieldCode="DE" term="%22Lebanese%22">Lebanese</searchLink>
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  Data: The orientation programs in most of the schools do not mitigate the diverse necessities of students. In addition, the instability of the labor market and the complexity of life have a great impact on young people's career choices. Faced with these concerns, high school students get confused when choosing a college major. Furthermore, the explosion of data on the Internet has caused most of the Internet users to make possible unsuitable decisions when browsing the Web, due to their inability to handle such large amounts of data. In this paper, the Case-based reasoning, and Ontology-based Hybrid Recommender System (COHRS) is proposed to assist high school students deciding the appropriate university/college, university major and career domain that best fit their preferences. COHRS uniquely combines case-based reasoning, collaborative filtering, knowledge base and ontology to explore the top N recommendations based on their fields of interest. The system has been evaluated on Lebanese students through a real-life dataset collected from different Lebanese cities. The first tests carried out on 60 high school students in Beirut city showed an average satisfaction level of 91.7% of the recommended results from the proposed system and 93.3% of them found the system very useful. The proposed system achieved an average accuracy level of 98% and 95% to retrieve the most similar cases and to extract appropriate recommendations respectively, which provides a very insightful capability to guide high school students in their future directions. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Educational Technology Research & Development is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Aug2025
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