Modeling the learner's cognitive state transitions using fuzzy logic techniques for adaptive learning
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Keywords
Εξ αποστάσεως εκπαίδευση ; Ευφυές διδακτικό σύστημα ; Ασαφείς Γνωστικοί Χάρτες ; Fuzzy Cognitive Maps (FCMs) ; Intelligent tutoring systemsAbstract
In this Ph.D. thesis a novel approach of web-based education that performs
individualized instruction, adapting the delivery of the knowledge domain to
the individual learner’s learning needs and pace, is presented. It includes
fuzzy logic techniques to represent the learner’s knowledge and cognitive
state. The presented Intelligent Tutoring System includes a rule-based fuzzy
logic mechanism for providing personalized tutoring to each learner and an
innovative module, which is responsible for tracking cognitive state transitions
of learners with respect to their progress or non-progress.
The presented approach models either how learning progresses or how the
student’s knowledge can be decreased. In particular, it performs user
modeling by dynamically identifying and updating the student’s knowledge
level for all the concepts of the domain knowledge. Its operation is based on
Fuzzy Cognitive Maps (FCMs). They are used to represent the dependencies
among the domain concepts. The presented student model uses fuzzy sets to
represent the student’s knowledge level as a subset of the domain
knowledge. Thus, it combines fuzzy theory with the overlay model. Moreover,
it employs a novel inference mechanism that dynamically updates user
stereotypes using fuzzy sets. This mechanism is triggered after any change of
the student’s knowledge level of a domain concept. Then, it updates the
student’s knowledge level of the concepts, which are related with the concept
that the student has learnt or forgotten. The transition of a learner from one
stereotype to another reveals her/his learning state each time. In particular, it
reveals if a student learns or not, if s/he forgets and reasons these states.
The presented novel approach was fully implemented and evaluated.
Particularly, an original integrated environment for personalized e-training in
programming and the programming language C, which is called ELaC, was
developed. The specific knowledge domain was chosen due the fact that in
the domain of computer programming there are many different programming
languages and learners have a variety of different backgrounds and
characteristics. Therefore, it is suitable for the implementation and evaluation
of the thesis’ issue. ELaC incorporates the presented fuzzy student modeling
approach. Thereby, recognizes when a new domain concept is completely
unknown to the learner, or when it is partly known due to the learner having
previous related knowledge. Furthermore, it recognizes when a previously
known domain concept has been completely or partly forgotten by the learner.
This system was used by the students of a postgraduate program in the field
of Informatics in the University of Piraeus, Greece, in order to learn how to
program in the programming language C.
For the evaluation of the fuzzy student model approach, two well-known
and common-used evaluation methods were chosen: the Kirkpatrick’s model
and the layered evaluation method. The results of the evaluation were very
encouraging. They demonstrated that the system models the student’s
cognitive state and adapts dynamically to her/his individual needs by
scheduling the sequence of lessons instantly, allowing her/him to complete
the e-training course at her/his own pace and according to her/his ability.
It has to be noted that the presented novel combination of overlay model
and stereotypes with fuzzy sets is significant as the students’ level of
knowledge is represented in a more realistic way by automatically modeling
the learning or forgetting process of a student with respect to the FCMs. The
application of this approach is not limited to adaptive instruction, but it can
also be used in other systems with changeable user states, such as e-shops,
where consumers’ preferences change over the time and affect one another.
Therefore, the particular approach constitutes a novel generic fuzzy tool,
which offers dynamic adaptation to users’ needs and preferences of adaptive
systems.
Department
Σχολή Τεχνολογιών Πληροφορικής και Επικοινωνιών. Τμήμα ΠληροφορικήςNumber of pages
250Language
EnglishCollections
Except where otherwise noted, this item's license is described as
Attribution-NonCommercial-NoDerivatives 4.0 Διεθνές
Attribution-NonCommercial-NoDerivatives 4.0 Διεθνές