Using Ontology for Personalised Course Recommendation Applications

Abstract

The primary data source for universities and courses for students is increasingly becoming the web, and with a vast amount of information about thousands of courses on different websites, it is quite a task to find one that matches a student's needs. That is why we are proposing the "Course Recommendation System", a system that suggests the course best suited for prospective students. As there has been a huge increase in course content on the Internet, finding the course you really need has become time-consuming, so we are proposing to use an ontology-based approach to semantic content recommendation. The aim is to enhance the efficiency and effectiveness of providing students with suitable recommendations. The recommender takes into consideration knowledge about the user (the student's profile) and course content, as well as knowledge about the domain that is being learned. Ontology is used to both models and represent such forms of knowledge. There are four steps to this: extracting information from multiple sources, applying ontologies by using Protégé tools, semantic relevance calculation and refining the recommendation. A personalised, complete and augmented course is then suggested for the student, based on these steps.

Ontology-Based Personalized Course Recommendation Framework

“…In this respect, Artificial Intelligence techniques could develop and improve the decision making and reasoning process of humans to minimize the amount of uncertainty there is in active learning to ensure a lifelong learning mechanism [21]. The challenge for recommender systems, therefore, is to better understand the student's interest and the purpose of the domain [1]. An association mining based recommender has been developed for recommending tasks that are related to learning, and are most suitable for learners based on the performance of the targeted student and other students who are similar to them [27].…”

“…Ontologies are used in the proposed approach to model knowledge regarding the course content (the course profile), knowledge about the user (the student profile) and domain knowledge (the taxonomy of the domain being learned). Within the domain of knowledge representation, the term ontology refers to both the formal and explicit descriptions of the domain concepts [1]. These are frequently conceived as a set of entities, relations, functions, instances and axioms [7].…”

“…Unstructured text documents include four processes: data pre-processing, concept clustering, context extraction and local ontology construction. For more information about local ontology construction from the unstructured text, see [1].…”

“…Finding information regarding higher education from a large number of websites is a challenging and time-consuming process. Helping students to make the correct choice from a myriad of available courses in order to meet their individual needs is a real challenge [1]. We have used the term ''course'' in this paper to refer to any program of study such as undergraduate, postgraduate and so forth.…”

“…Nowadays, students can rapidly find information relating to universities and the courses offered by them using online resources [6]. However, simply because more course information is now provided on university websites, this does not automatically mean that students possess the cognitive ability to evaluate them all [1]. Instead, they are confronted with a problem that is termed ''information overloading'' [7].…”