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224 Selected Studies on Software and Information Systems
◦ Inferred mode from the prerequisite relationships and
◦ Inferred model from part-of relationships, both based on independent Bayesian
networks.
– Instructional Planner – responsible for guidance during learning process (selecting
concept to be studied and the most adequate instructional resource).
– Connection Manager – manages the requests and responses between MEDEA’s services
(actually implemented as Web Services). The integration needs to deal with semantic
perspective of the communication problem. Relationships between MEDEA’s
domain models and its components must be established. Therefore, MEDEA implements
methods for automatic type conversion of different representations of student
knowledge (binary, discrete, real, etc.).
The student model includes the student model updating service, that updates the student model
whenever the student performs a pedagogical task (i.e., every time that an instructional resource
is executed). When Diagnostic Instructional Resource evaluates (accurately) student’s
knowledge about some domain topics, MEDEA adds this information to the verified knowledge
model. As Estimate Instructional Resources provide evaluation based on student observation,
the available information is used to update the estimated knowledge model. Non
intelligent Instructional Resources do not evaluate students in any way, so the student model
updating service just informs that the student has executed that task.
It is unclear why authors of MEDEA decided to use Ontology eXtensible Markup Language
(OXML) to represent domain model instead of widely used RDF/OWL approach.
Moreover, authors do not describe this language, so we have no idea how the domain model
is expressed. Current version of MEDEA forces authors to manually define mappings between
MEDEA domain model and domain model of a particular Instructional Resource. As
ontologies are used to represent the domain models, it is possible to apply semi-automated
ontology mapping approaches to support authors in the mapping task.
Personis
Personis [37] is another generic user modeling server. It is distinct from others by emphasizing
the scrutability of the user model [35].
Figure 8-4 depicts integration of Personis server with individual adaptive systems. Interesting
feature is a specific scrutability interface of each system as an addition to the common
one. This allows users to explore their models within a context of the particular application.
This could simplify user’s control of her model, which is used for personalization and thus
indirectly significantly improve user’s experience with the system.
Each application has its own view of the central user model, which decides which data
should be accessible to the application. The view is set by the user, allowing her to decide
upon availability of her (often) personal data to individual applications, thus preserving her
privacy.
User model is represented in triples component – evidence – source, where component
represents user’s attribute, evidence its value and source identifies an application, which
contributed this attribute to the user model.