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Design an Adaptive E-learning Application Architecture based on IEEE LTSA reference model

Journal from gdlhub / 2016-11-11 07:44:32
By : Andharini Dwi Cahyani, Ari Basuki, Eka Mala Sari Rohman, Yeni Kustiyahningsih, Telkomnika
Created : 2015-03-01, with 1 files

Keyword : adaptive e-learning, IEEE LTSA, architectural model
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/112

Adaptivity in the field of e-learning and an innovative framework for personalised adaptive e-learning is often considered to be new or in an early development stage. In this paper, we propose an architecture for development of adaptive e-learning system. This architecture is based on the IEEE 1484 LTSA (Learning Technology System Architecture) reference model. The learner model is based on the learners’ preference and knowledge level. According to these profiles, the learners are served with learning material that best matches their educational needs. Furthermore, we also accomodate the learner feeback regarding to difficulty level of learning material. The design of our proposed models is prepared using UML notation. Our goal is to assist the instructional designers in developing adaptive e-learning system based on the IEEE LTSA models efficiently.

Description Alternative :

Adaptivity in the field of e-learning and an innovative framework for personalised adaptive e-learning is often considered to be new or in an early development stage. In this paper, we propose an architecture for development of adaptive e-learning system. This architecture is based on the IEEE 1484 LTSA (Learning Technology System Architecture) reference model. The learner model is based on the learners’ preference and knowledge level. According to these profiles, the learners are served with learning material that best matches their educational needs. Furthermore, we also accomodate the learner feeback regarding to difficulty level of learning material. The design of our proposed models is prepared using UML notation. Our goal is to assist the instructional designers in developing adaptive e-learning system based on the IEEE LTSA models efficiently.

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