Introduction
Adaptive hypermedia (AH) is one of the promising application areas for user
modeling and user-adapted interaction techniques [1]. AH systems can be useful
in any situation when the system is expected to be used by people with
different goals and knowledge and where the hyperspace is reasonably big. Users
with different goals and knowledge may be interested in different pieces of
information presented on a hypermedia page and may use different links for
navigation. AH tries to overcome this problem by using knowledge about a
particular user, represented in the user model, to adapt the information and
links being presented to the given user. That is essentially important for
educational hypermedia systems, where the same user can have different
knowledge on the same topic (and thus needs different information on this
topic) on different stages of learning. Adaptation can also protect the user
from being lost in hyperspace. Knowing user goals and knowledge, AH systems can
support users in their navigation by limiting browsing space, suggesting most
relevant links to follow, or providing adaptive comments to visible links.
We are using AH in educational context as a component of intelligent tutoring
system (ITS). The student model of ITS (which is used traditionally for
individualizing instruction) is applied in our systems as a user model for AH
component. We have implemented several different adaptation techniques for
adaptive educational hypermedia [2]. Of particular interest for us is the
technique of adaptive visual annotation of hypermedia links. Here we explain
briefly this technique and report preliminary experimental results of its
evaluation. The results show that adaptive visual annotation is helpful and can
reduce user floundering in hyperspace.
ADAPTATION IN HYPERMEDIA
What can be adapted in AH are the content of a hypermedia page and the links
from a page (including index pages and maps) to related pages. We distinguish
these two techniques of adaptation and call the first technique adaptive
presentation (or content-level adaptation) and the second technique
adaptive navigation support (or link-level adaptation). Adaptive
presentation is the most popular and the most studied way of hypermedia
adaptation [3-5]. With adaptive presentation the content of a hypermedia page
is generated or assembled from pieces according to the user's class and
knowledge state. Generally, qualified users receive more detailed and deep
information, while novices receive more additional explanation. By adaptive
navigation support we mean all the ways to play with visible links that can
support hyperspace navigation.
Previous works [3,6] suggest adaptive ordering technique for adaptive
navigation support. This technique applies user model and some user-valuable
criteria to adapt the order of presentation for all possible links. It gives
the user a hint which of these links to follow (the more close to the top, the
more relevant the link is). We think that adaptive ordering technique provides
a good way to support user navigation in the pages with dozens of possible
links, but has less sense in educational context when the number of links is
smaller. Some research also shows that the stable order of options in menus is
important for novices. We apply another technique for adaptive navigation
support in educational hypermedia: visual adaptive annotation of links
(augmenting links with dynamic comments in any form) according user's goal and
knowledge state [2,7]. We expect that adaptive annotation can give the users
some additional information about accessible nodes and thus reduce their
floundering in the hyperspace. In particular, we hope that it reduces the
number of "orientation" visits when the user visits related nodes just for
several seconds to see what is around him.
At present there are very few studies investigating the effectiveness of AH.
The experiments, reported in [5] shows that adaptive presentation increases
user performance. The work [6] reports positive experimental results of
adaptive ordering technique. By now there was no experiments with adaptive
annotation technique, though some related research shows that even non-adaptive
annotation, which tells the user more about the nodes designated by annotated
links, can increase student's performance [8]. It was the goal of our recent
experiment to check the effectiveness of adaptive annotation in educational
context.
THE EXPERIMENT
We use for the experiment an ITS ISIS-Tutor [7]. Hypermedia component of
ISIS-Tutor is an interface with a network of concept descriptions, examples and
problems. ISIS-Tutor uses colors and special marks to annotate the set of links
leading from the current node to related nodes (and from index page to all
nodes) according to the current user knowledge and educational goals. The
latter means, that the links to concepts that are the goal of the current
lesson are marked with a sign "-". The system uses the student model to
distinguish four knowledge states for each concept represented by a hypermedia
page: not-ready-to-be-learned (i.e., has unlearned prerequisites),
ready-to-be-learned, in-work (learning started), and
learned (user has solved the required number of problems for the
concept). Thus, at any moment the hyperspace is divided implicitly into four
zones with different educational status. The idea is that marking these zones
visually would help the student in hyperspace navigation. In the current
version of ISIS-Tutor links to not-ready-to-be-learned concepts were not
specially colored, ready-to-be-learned were colored red, both in-work and
learned were colored green, and learned concepts was additionally marked with
sign "+". Links to problems were annotated by the same way.
Twenty-six subjects (first year computer science students of the Moscow State
University) took part in the experiment. They were briefly introduced to
ISIS-Tutor and then had up to 45 minutes to work with the system. The same
educational goal (ten concepts and ten test problems) was set to all the
students. To finish the course, each user had to solve all ten problems. The
subjects were divided randomly into three groups. Group A worked with
hypermedia without any adaptation. Group B worked with adaptive hypermedia as
described above. Group C worked with restrictive version of the same adaptive
hypermedia: the links to all not-ready-to-be-learned concepts and problems and
to all concepts and problems outside the learning goals were excluded from
index and all other menus. The idea of this restriction is to reduce the
cognitive load of the student by excluding "not useful" information. All
actions of the students working with the system are recorded and then analyzed
to compare various aspects of user performance.
Table 1. Results of the experiment
The results of the experiment are shown in the table above (all data are
average numbers for each group). As we can see, the overall number of
navigation steps, the number of repetitions of previously studied concepts, the
number of transitions from concept to concept and from index to concept are
seriously less for AH. Moreover, this difference is usually bigger for
non-restrictive hypermedia.
DISCUSSION
The results of our experiment show that adaptive visual annotation of
hypermedia links in educational context can really reduce user's floundering in
the hyperspace and make the learning with hypermedia more goal-oriented. With
adaptive annotation the user can achieve the same result using smaller number
of navigation steps and visits to hypernodes. It is interesting to compare our
results with the results presented in [5]. This work reports that adaptive
presentation in hypermedia can reduce the time for learning the material and
improve the comprehension of it, but can not reduce the number of nodes visited
in the process of learning. In the same time, adaptive annotation of links can
hardly improve the quality of learning, but can reduce the number of visited
nodes thus further reducing the learning time. These techniques look
complimentary and can be used together for further improvement of the
effectiveness of learning with hypermedia.
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