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Ontology Based Adaptive, Semantic E-Learning Framework (OASEF)

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Information Science and Applications (ICISA) 2016

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 376))

Abstract

E-Learning, having a pivotal role in educating diverse communities of knowledge has not prevailed much in addressing individualized needs (i.e. Personalization) of learner while designing didactic contents, and their respective deliverance to the learners in adaptive manner. Moreover, there is sheer need of porting current e-learning systems to ontology backed web3.0 for incorporating context aware provision of learning material with a goal to improve learner’s performance. We have developed an adaptive e-learning framework, named OASEF, comprising of backbone ontologies such as domain ontology, learner ontology, content ontology and assessment ontology (to model exercises, quizzes and exams).Concepts of learner ontology are exploited as guideline to offer semantic contents to certain category of learner from content ontology keeping in view his ability, knowledge, prior performance and results in current assessments. Effectiveness of ontological model is evaluated through metrics of correctness, consistency and completeness. Initial experiential evaluation of proposed framework has shown a remarkable improvement in learner’s performance due to its adaptive and dynamic nature. Moreover, comparative analysis of our framework with prevalent systems especially [9] stipulates our system as more comprehensive, diverse and versatile.

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Correspondence to Sohail Sarwar .

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Sarwar, S., Ul Qayyum, Z., Safyan, M., Munir, R.F. (2016). Ontology Based Adaptive, Semantic E-Learning Framework (OASEF). In: Kim, K., Joukov, N. (eds) Information Science and Applications (ICISA) 2016. Lecture Notes in Electrical Engineering, vol 376. Springer, Singapore. https://doi.org/10.1007/978-981-10-0557-2_114

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  • DOI: https://doi.org/10.1007/978-981-10-0557-2_114

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0556-5

  • Online ISBN: 978-981-10-0557-2

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