E-Learning Systems: Intelligent Techniques for by Aleksandra Klašnja-Milićević, Boban Vesin, Mirjana Ivanović,

By Aleksandra Klašnja-Milićević, Boban Vesin, Mirjana Ivanović, Zoran Budimac, Lakhmi C. Jain

This monograph offers a accomplished examine overview of clever concepts for customization of e-learning platforms. exact emphasis is given to clever tutoring platforms as a selected category of e-learning platforms, which help and enhance the training and instructing of domain-specific knowledge.

A new method of practice potent personalization in line with Semantic net applied sciences completed in a tutoring process is gifted. This technique includes a recommender procedure according to collaborative tagging concepts that adapts to the pursuits and point of scholars' wisdom. those concepts are very important contributions of this monograph.

Theoretical versions and strategies are illustrated on a true personalized tutoring method for educating Java programming language.

The monograph is directed to, scholars and researchers drawn to the e-learning and personalization techniques.

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Extra resources for E-Learning Systems: Intelligent Techniques for Personalization

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2016). An automatic and dynamic approach for personalized recommendation of learning objects considering students learning styles: An experimental analysis. In Informatics in education (Vol. 15, pp. 45–62). Vilnius University. , & Freeley, M. E. (1984). Practical applications of the research: Responding to students’ learning styles–step one. Illinois State Research and Development Journal, 21(1), 1–21. , & Silverman, L. (1988). Learning and teaching styles in engineering education. Engineering Education, 78, 674–681.

Regueras, L. , Verdú, M. , Leal, J. , de Castro, J. , & Queirós, R. (2012). A distributed system for learning programming online. Computers & Education, 58(1), 1–10. , & Ivanović, M. (2004). Modern educational tools. In Proceedings of PRIM2004, 16th Conference on Applied Mathematics, Budva, Montenegro (pp. 293–302). , & Putnik, Z. (2012). 0 technologies. Educational Technology Research and Development. 1007/s11423-011-9228-z Part II E-Learning Systems Personalization Chapter 2 Personalization and Adaptation in E-Learning Systems Abstract Personalization is a feature that occurs separately within each system that supports some kind of users’ interactions with the system.

Namely, since the early 60s to these days researchers have built over 70 different learning style models accompanied by the instruments for their assessment. They mostly differ in a way in which they distinguish the leading factors of the learning process. All learning style models can be classified into five learning style families (Coffield et al. 2004; Dorça et al. 2016; Halawa et al. 2015), according to the cognition of the learning style concept: • Learning styles and preferences are constitutionally based, including four modalities: visual, auditory, kinaesthetic and tactile; • Learning styles reflect features of the cognitive structure, including patterns of ability; • Learning styles are one component of personality type; • Learning styles are flexibly stable learning preferences; • Move on from learning styles to learning approaches, strategies, orientations and conceptions.

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