Personalized Learning in an Intelligent Educational System

Terzieva, Valentina; Ivanova, Tatyana; Todorova, Katia

doi:10.1007/978-3-031-17601-2_2

Cited by 4 publications

(2 citation statements)

References 22 publications

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“…Terzieva et al 2023 introduced a Knowledge Model for Intelligent Education Systems (IES), enabling dynamic personalization of learning paths. This model encompasses ontological information on prerequisites, learners, learning objectives, teaching strategies, courses, educational resources, and assessment of learners' knowledge [30].…”

Section: B Personalized Learning Pathsmentioning

confidence: 99%

Ontology-Driven Approach for Competency-Oriented and Student-Centered Engineering Education

Evain,

Exposito,

Gueye

et al. 2024

2024 IEEE Global Engineering Education Conference (EDUCON)

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Section: B Personalized Learning Pathsmentioning

confidence: 99%

Ontology-Driven Approach for Competency-Oriented and Student-Centered Engineering Education

Evain,

Exposito,

Gueye

et al. 2024

2024 IEEE Global Engineering Education Conference (EDUCON)

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“…Students are critical in the educational process; here, they are represented as unique individuals in the proposed ontology, with attributes that capture their name, identifier, and acquired competencies [16]. In addition, relationships are established between students and the learning objectives they have achieved.…”

Section: Fundamental Concepts For Ontology Developmentmentioning

confidence: 99%

Enhancing Learning Personalization in Educational Environments through Ontology-Based Knowledge Representation

Villegas-Ch,

García-Ortiz

2023

Computers

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In the digital age, the personalization of learning has become a critical priority in education. This article delves into the cutting-edge of educational innovation by exploring the essential role of ontology-based knowledge representation in transforming the educational experience. This research stands out for its significant and distinctive contribution to improving the personalization of learning. For this, concrete examples of use cases are presented in various academic fields, from formal education to corporate training and online learning. It is identified how ontologies capture and organize knowledge semantically, allowing the intelligent adaptation of content, the inference of activity and resource recommendations, and the creation of highly personalized learning paths. In this context, the novelty lies in the innovative approach to designing educational ontologies, which exhaustively considers different use cases and academic scenarios. Additionally, we delve deeper into the design decisions that support the effectiveness and usefulness of these ontologies for effective learning personalization. Through practical examples, it is illustrated how the implementation of ontologies transforms education, offering richer educational experiences adapted to students’ individual needs. This research represents a valuable contribution to personalized education and knowledge management in contemporary educational environments. The novelty of this work lies in its ability to redefine and improve the personalization of learning in a constantly evolving digital world.

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Application of ICT in Interactive Learning Environments for Emergency Response Training

Chikurteva,

Chikurtev,

Bogdanova

et al. 2024

Lecture Notes in Networks and Systems

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Personalized Learning in an Intelligent Educational System

Cited by 4 publications

References 22 publications

Ontology-Driven Approach for Competency-Oriented and Student-Centered Engineering Education

Ontology-Driven Approach for Competency-Oriented and Student-Centered Engineering Education

Enhancing Learning Personalization in Educational Environments through Ontology-Based Knowledge Representation

Application of ICT in Interactive Learning Environments for Emergency Response Training

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