Ontological student profile

Ameen, Ayesha; Khan, Khaleel Ur Rahman; Rani, B. Padmaja

doi:10.1145/2393216.2393294

Cited by 7 publications

(5 citation statements)

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“…The student profiles, relationships, conditions, and restrictions of the ontology can be reused as a basis for inferring additional student characteristics. Student profiles are provided explicitly by students and divided into three broad information categories: personal, academic, and general [37,38]. Sharma and Ahuja [39] presented an RS that recommended the most appropriate e-learning content for computer science students.…”

Section: B Ontology-based Recommender In Educationmentioning

confidence: 99%

SCA Advice System: Ontology Framework for a Computer Curricula Advice System Based on Student Behavior

Wongchomphu,

Beokhaimook

2023

JICCE

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This study proposed an SCA advice system. It is an ontology-based recommender that provides advice on appropriate computer curricula based on the behavior of high school students. The three computer curricula at Chiang Mai Rajabhat University include computer science (CS), information technology (IT), and web programming and security (WEB). This study aims to design the ontology framework for an SCA advice system. The system considers three core ontologies: student, computer-curriculum, and advice. After analyzing student behaviors, the behavior types of CS, IT, and WEB were determined to be SB-2, SB-1, and SB-5, respectively. All subjects in these three curricula were analyzed and grouped into seven groups. Their curricula were synthesized in terms of basic skills, basic knowledge, and characteristics. Finally, advice results can be obtained by consolidating the curriculum nature of the CS, IT, and WEB curricula.

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Section: B Ontology-based Recommender In Educationmentioning

confidence: 99%

SCA Advice System: Ontology Framework for a Computer Curricula Advice System Based on Student Behavior

Wongchomphu,

Beokhaimook

2023

JICCE

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“…The user/student ontology includes information about the student, such as personal information, academic information and general information. Refer to more details in [22], as shown in Fig. 2.…”

Section: Fig1 Course Ontologymentioning

confidence: 99%

Using Ontology for Personalised Course Recommendation Applications

Ibrahim¹,

Yang²,

Ndzi³

2017

Computational Science and Its Applications – ICCSA 2017

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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.

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“…Profile contains complete detail of student. The steps required to construct the profile are given in [2].…”

Section: Input Ontologiesmentioning

confidence: 99%

“…The second ontology used is Student profile ontology containing all type of information gathered from Student as in [2].There are many advantages of using ontological Student profile. Additional user characteristics can be inferred by using ontology relations, conditions, restrictions.…”

Section: Introductionmentioning

confidence: 99%

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Semi-Automatic Merging of Ontologies using Protégé

Ameen¹,

Khan²,

Rani³

2014

IJCA

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Ontologies play a crucial role in bringing the Semantic Web vision to its full potential. Ontologies are developed at different levels of abstraction and by different people for various purposes. Knowledge represented by the ontologies is scattered because of existence of many ontologies representing the same concepts, therefore it becomes difficult to analyse, study and use the knowledge spread across many ontologies if they are studied individually. Knowledge represented by ontologies can be combined into a single ontology which is shown in this paper. Ontologies can be merged to combine the knowledge from different ontologies. In this paper we have shown the merger of two ontologies first ontology is university second ontology is the Student profile ontology containing details of Student which were developed in educational domain. Ontologies were developed and merged using protégé 4.0 alpha tools.

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Ontological student profile

Cited by 7 publications

References 3 publications

SCA Advice System: Ontology Framework for a Computer Curricula Advice System Based on Student Behavior

SCA Advice System: Ontology Framework for a Computer Curricula Advice System Based on Student Behavior

Using Ontology for Personalised Course Recommendation Applications

Semi-Automatic Merging of Ontologies using Protégé

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