Information Technology Reference
In-Depth Information
One strategy toward personalized tutoring systems is AH, which adapts
both hypertext and multimedia to meet the individual student's needs. The
primary goal of this approach is to provide adaptive presentation and adap-
tive navigation support [9]. Adaptive presentation refers to changing the con-
tent of Web pages to cater to individual needs. Adaptive navigation support
refers to adding, hiding, or ordering the links presented on a Web page to
better suit the user's needs.
Another approach uses agent-based technology to provide Web-based per-
sonalization in e-learning systems. Currently, providing student-centered
learning contents and personalized guidance are the main research topics
in intelligent tutoring systems. Ozdemir and Ferda [42] use interface agents
to guide students through the course materials on the Web. Ankush et al.
[3] proposes a content-based retrieval system to provide educational videos
based on the individual student's needs.
The development of ITS, based on artificial intelligence and cognitive sci-
ence researches, has accumulated considerable results in the past 20 years. At
present, researchers attempt to deploy ITS onto the Web in view of the rapid
development of the Internet and the World Wide Web.
17.2.1 intelligent Tutoring System (iTS)
Most generic ITS architectures suggest building a good student model that
reflects the system's beliefs on the mastery level of learners in particular
concepts. Moreover, it is the driving force that enables the system to per-
form individualized tutoring to students [31]. To further extend the generic
architecture, various types of ITS have been developed based on different
domains, pedagogical strategies, and other affecting factors [37,46,56]. The
major researches and developments of ITS are summarized in the following
paragraphs.
Most researchers believe that the first ITS, SCHOLAR, was designed in the
early 1970s, to teach South American geography [17]. Early ITS systems empha-
sized duplicating the structure of student-human-tutor interactions. In such
systems, success has been limited because of the technological challenges of
making a computer system sufficiently intelligent to field various questions in
a pedagogically useful manner. The advent of the Web changed the pedagogi-
cal approaches to educational software, instead, it has less similarity to human
tutoring models. These approaches are more focused on simpler instructional
approaches and are easily computerized. Web-administered, multiple-choice
tutors have shown promise because of their ease of development [29]. Other ITS
systems create complex instructional strategies that require extensive expert
system representations customized to the knowledge domain; representative
models include geometry [1] and computer programming [38].
Other researchers have also attempted to create domain-independent stan-
dards for representing courseware. Information about the learning content,
