An Intelligent and Adaptive Hypermedia System Based on Thinking Style (IAHS-TS)

An Intelligent and Adaptive Hypermedia System Based on Thinking Style (IAHS-TS)

Mahnane M. L. Lamia (LRS Laboratory, University of Badji Mokhtar Annaba, Algeria) and Hafidi Mohamed (LRS Laboratory,University of Badji Mokhtar Annaba, Algeria)
Copyright: © 2016 |Pages: 20
DOI: 10.4018/978-1-4666-9932-8.ch007
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Abstract

In this paper, an adaptive and intelligent hypermedia system, AIHS was designed, developed and implemented. This e-learning system was intended for bachelor degree program that is offered in all Algerian public universities, where the studied subjects are: “ORL”, “Dermatology”, “Ophthalmology” and “Language”. Content which was transformed into learning objects in four different ways in accordance with Herrmann Brain Dominance Instrument (HBDI). the developed prototype will assist a learner in accessing and using learning resources which are adapted according to his/her personal characteristics (in this case his/her thinking style and level of knowledge). It will facilitate the learning content teacher in the creation of appropriate learning objects and applying them to suitable pedagogical strategies.
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Introduction

Today, learning environments vary and evolve in parallel with rapid development of informatics technology. In this sense, e-learning environments have become common in recent years.

Traditional e-learning environments present pre-determinated content in the same sequence to all learners. Therefore, they became the focus of many criticisms due to their structure. These criticisms and new approaches led to the birth of a new concept which is Intelligent and Adaptive Hypermedia System (IAHS).

IAHSs were developed as an alternative to traditional e-learning environments that are developed according to ‘‘one-size-fits-all’’ approach (Brusilovsky, 1996; Brusilovsky, 2001; Brusilovsky et al., 2003). IAHSs are systems where Adaptive Hypermedia System (AHS) and Intelligent Tutoring System (ITS) architectures are conceived together.

Though AHSs and ITSs are often used together, they do not mean the same concept literally (Brusilovsky et al., 2003). AHSs are environments where individual differences of learners are entirely taken into account offering different content and browsing support to each individual. As for ITSs, they are computer systems which are designed using artificial intelligence methods and which know what to teach, how to teach and whom to teach (Brusilovsky et al., 2003; Murray, 1999). ITSs are considered as education systems in which artificial intelligence methods are employed. They are also considered as systems offering intelligent problem solution supports and acting as intelligent solution analysts (Brusilovsky et al., 2003; Keles et al., 2009; Munoz-Merino et al., 2012).

Design of IAHSs is one of the important research topics for researchers’ education and computer sciences. Key concept in these systems is being known which characteristic of the learner will be computerized and how to use this information. Tendency of researchers regarding this topic is taking thinking styles, which is considered as the preference of taking, using and saving the information, into account (Kainnen, 2009). According to researchers, e-learning environments developed taking into account thinking styles are more efficient than traditional e-learning environments. Besides, according to many previous studies, e-learning environments employing a specific thinking style are more efficient for learners with higher level of satisfaction and reduced period of time for learning (Bajraktarevic et al., 2003; Chua et al., 2011; Manochehr, 2006; Mustafa et al., 2011; Papanikolaou et al., 2003; Popescu, 2010; Sangineto et al., 2008; Triantafillou et al., 2003; Wang, 2008; Wang et al., 2010). From this aspect, thinking styles can be taken as basis for constructing user model in design of AHSs (Brown et al., 2005; Karampiperis et al., 2005; Liegle et al., 2006).

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