User Modelling and Hypertext Adaptation in the Tutoring System
Anatom-Tutor
I. Beaumont
Fraunhofer Inst., St. Ingbert, Germany.
e-mail address: beaumont@ibmt.fhg.de
This article describes ANATOM-TUTOR, an intelligent anatomy tutoring
system for use at university level. After a general introduction to
the system, we briefly look at the system's question mode, in which
explanations and questions are generated in a simulated examination
situation, taking into consideration the individual user's level of
knowledge, then take a closer look at adaptivity in the system's
hypertext component, which also involves taking into account the
user's level of knowledge.
General
ANATOM-TUTOR is, as the name suggests, a system for teaching anatomy.
At present we deal with several aspects of brain anatomy, including
the visual system, the pupillary light reflex system and the
accommodation reflex system, each looked at from both morphological
and functional perspectives. An intelligent knowledge base,
accessible via menus and mouse-sensitive diagrams, is used for that
part of the material which forms the framework of our domain.
Detailed information, knowledge of how the information is used, and
other material not suitable for representation in the knowledge base
formalism is treated in a hypertext module. Much of this information
is available (in rule form) to a didactic module which is thus able
to present explanations and illustrate the use of the material. The
didactic module adapts its presentation to the user's level of
knowledge by consulting a rule-based user modelling component, which
uses weighted rules and stereotypes to infer a default closure of the
observed data complet ANATOM-TUTOR has three operating modes. In the
browsing mode, menus and mouse-sensitive diagrams are employed for
accessing the domain knowledge base. The user model is neither
consulted nor modified in this mode. The question mode, which makes
extensive use of the user model, is a simulated examination situation
offering individually tailored responses to student misconceptions.
In the hypermode, which also makes use of the user model, a hypertext
based information system is used for the structured presentation of
domain knowledge, together with illustrations of its use, in a manner
suited to the users' level of knowledge. This is built along the
lines of existing "stretchtext" systems such as MetaDoc from Boyle
and Encarnacion [Boyle 91]. In the browsing mode, the user learns in
a self-directed, explorative manner. In the hypermode, he is guided
through the material in a personalised way, the important points are
emphasized, and the uses of the material illustrated. The question
mode can be used for exami It has been pointed out by several authors
that Intelligent Tutoring Systems (ITSs) and educational hypertext
systems are currently seen as two distinct approaches to using
computers in education (e.g. [Brusilovsky et al, 94]). It would seem
that this view has often tacitly implied the incompatibility of the
two approaches. ANATOM-TUTOR shows that this is not the case, and
that indeed the two approaches can be combined to the advantage of
both. It is a system in which a hypertext component has been combined
with an ITS, both modules referring to a common user modelling
component for information about the learner. Its hypertext system is
unique in that it has been equipped to offer custom-tailored
explanations and auxiliary questions on encountering user
misconceptions, a capability which relies on the properties of the
ITS. Looking at things from a pedagogical point of view, ANATOM-TUTOR
is, as far as the author is aware, the first comparable case of
self-directed and guided approaches to instruction being
simultaneously covered in one system.
The Question Mode
The question mode (a simulated examination situation) is important in
that it provides the main vehicle for receiving information about the
user. In any adaptive system, adaptation has to be carried out with
respect to some (implicit or explicit) model of the user. This model
has to be built and maintained, and the more complex the model, the
more work has to go into filling it with information. In pure
hypertext systems this is a problem, since information flows mainly
in one direction - to the user. Many systems feature an enrollment
procedure in which inventory is taken of the user's knowledge of the
concepts covered in the material, but this can be extremely time
consuming if a detailed model is required, and does not take into
account the knowledge that the user gains by using the system.
Updating the model on the basis of information asked for by the user
is of limited usefulness. In ANATOM-TUTOR, the modelling problem is
tackled as follows. The user first goes through an enrollment
procedure. The aim here is to gather certain key information about
the user, to which stereotype knowledge can then be applied. This is
statistically gathered information about which items of knowledge are
generally dependent on which other items. (For example in a
programming application, one might find that users of a certain level
who know the nroff command would also know the ls, mail, sed, etc.,
commands with some specifiable degree of certainty.) Using the user's
knowledge of the key items, a default picture of the rest of his
knowledge of the domain can be deduced. The actual questions provide
a means of obtaining explicit information about the user's knowledge.
If the user answers a question wrongly, but the user model contains
the correct answer, his knowledge of the premises and domain laws
necessary for deducing the information can be checked. This means
that wrong answers result in relevant ad
The Hypertext Component
We will assume that the reader is familiar with the terms hypertext
and hypermedia and will not give any basic definitions or
descriptions here. Instead, we describe how the user model is used
for tailoring text and specifying links, and how user's interaction
with the system affects the user model. The idea behind
ANATOM-TUTOR's hypertext component is to provide the learner with the
full functionality of traditional hypertext with the additional
advantage that the text has been adapted to the learner's individual
needs, and that the user is not confused by having too many active
links (lost in hyperspace). (This means, of course, that a detailed
user model is required.) Adaptation in hypertext systems can take
place at two levels: at the link level, and at the text level.
Adaptation at the link level involves imposing some sort of structure
on the nodes (or rather, on the concepts in them) and activating or
deactivating links from these depending on the user's knowledge. In
ANATOM-TUTOR, a hypertext lesson consists basically of pre-defined
sequence of nodes. Depending on the global classification of the
user, the actual nodes to be presented and the anchors to be
activated are determined and the resulting setting remains unchanged
during the course of the lesson. Adaptation at the text level can
invol
In an information system such as hypertext, the main feedback which
the system gets is the request for more information, which is usually
done by clicking menu buttons or active fields in the body of the
text. Boyle and Encarnacion, [Boyle 91], recognise that the mouse
click allows only a "narrow bandwidth of information" but make the
most of it by enabling the user to remove superfluous information
(i.e. information which the user does not understand or which is too
basic) from the screen, thus providing another feedback dimension.
(We believe that in a realistic situation a user will just gloss over
what he cannot use, as he would do when reading a book, and not try
to use paragraph deletion as a signaling device.) If the user asks
for an explanation of an item of information which was assumed known,
MetaDoc removes the item from the user model and gives the requested
explanation (presumably then re-adding the item to the user model).
Paris [Paris 89] avoids the problem, and assumes the existence of a
per While there may be a question of the desirability and user
acceptance of putting test questions in an on-line documentation
system, ANATOM-TUTOR is a tutoring program and we can use test
questions to increase the bandwidth of information available from the
user without leaving the teaching paradigm. Adding questions relating
to the material is obviously superior to trying to accurately update
the model solely from the user's requests for more or less material,
and is in keeping with Self's [Self 88] advice on bypassing the
intractability problem of student modelling - "avoid guessing - get
the student to tell you what you need to know". The questions were
designed with the task analysis approach to curriculum design in mind
and are for confirming that the instructional objectives in the
lessons have been attained. Not only do we get instant reliable
feedback on the user's understanding, immediate active recollection
is a recognised method of embedding information in the memory. When
questions are posed by t
Implementational Details
ANATOM-TUTOR's user interface and hypertext component are programmed
using XVT. The domain knowledge base, user modelling component, and
didactic component are programmed in Common Lisp, the latter two
components also using the Lisp based production system Ops5.
ANATOM-TUTOR currently runs on Sun Workstations, and we are looking
at the possibility of implementing a PC version.
References
[Beaumont, 94] Beaumont, I.: 1994, "User Modelling in the
Interactive Anatomy Tutoring System ANATOM-TUTOR" in the journal User
Modeling And User-Adapted Interaction
[Boyle, 91] Boyle, C., and A. Encarnacion: 1991, 'A User Model
Based Hypertext Documentation System'. In: Proceedings of the IJCAI
Workshop W.4. (The system is also described in: C. Boyle and A. O.
Encarnacion: 1993, 'Meta-Doc: An Adaptive Hypertext Reading System'.
In: User Modeling and User-Adapted Interaction.)
[Brusilovsky et al, 94] Brusilovsky, P., L. Pesin, and M Zyryanov:
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[Paris, 89] Paris, C.: 1989, 'The Use of Explicit User Models in a
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[Rich 89] Rich, E.: 1989, 'Stereotypes and User Modeling'. In: A.
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[Self, 88] Self, J.: 1988, 'Bypassing the Intractable Problem of
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