Titlebook: Computational Intelligence for Technology Enhanced Learning; Fatos Xhafa,Santi Caballé,Angel Alejandro Juan Per Book 2010 Springer-Verlag

昆蟲(chóng)

Intelligent Techniques in Personalization of Learning in e-Learning Systems,It describes examples of their application to various e-learning platforms to create profiles of learners and to define learning path. The typical approach to obtain learner’s profile is the usage one of the clustering methods, such as: the simple k-means, Self Organizing Map, hierarchical clusterin

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Fuzzy ECA Rules for Pervasive Decision-Centric Personalised Mobile Learning,ormation system related to the domain of education. Personalization requires the identification and selection of individuals; this can be achieved using an individual’s profile (termed context). A context is inherently complex, its effective use representing a challenge that has to date not been ade

Narcissist

Developing an Adaptive Learning Based Tourism Information System Using Ant Colony Metaphor,been initiated by simple steps of bio-inspired algorithm to learn the collective pattern of tourist service environment. This chapter is devoted on a live project implementation and testing of a learning model prototype in tourist information system and service industry. The elaborated model is foll

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Intelligent and Interactive Web-Based Tutoring System in Engineering Education: Reviews, Perspectivave been developed and implemented. However, very few of them are pedagogically intelligent and interactive for learning purposes. The Web-based intelligent learning has become more effective in the past decade due to increasing use of the Internet in education. A literature search indicates that th

saphenous-vein

,Granular Mining of Student’s Learning Behavior in Learning Management System Using Rough Set Technins include the way the user navigate, the choice of the link provided in the system, the preferences of type of learning material, and the usage of the tool provided in the system. In this study, we propose mapping development of student characteristics into Integrated Felder Silverman (IFS) learnin

Gyrate

T-Learning 2.0: A Personalised Hybrid Approach Based on Ontologies and Folksonomies,chapter is exporting this technology to the field of learning through Interactive Digital TV (IDTV) (t-learning). In previous research, we have exposed our solution for creating learning experiences for t-learning, based on combining TV programmes and learning elements in order to lure viewers into

Obverse

Computational Intelligence Infrastructure in Support for Complex e-Learning Systems,phically be distributed, and who need to transparently share a huge variety of both software and hardware distributed learning resources. As a result, collaborative learning applications are to overcome important non-functional requirements arisen in distributed environments, such as scalability, fl