Abstract
In the present work, the semantics of the Extended Genetic Graph (EGG) is defined in order to eliminate limitations inherent in these graphs in the modelling of an ideal Student Model. The semantics of extended genetic graphs can be defined at two representational levels: conceptual and transactional. First, the student's knowledge as represented by EGG nodes is specified explicitly at the conceptual level using the conceptual graphs (CGs) as a representation. Secondly, the criteria for the definition and use of learning processes such asanalogy, generalization, refinement, component, anddeviation/correction are specified at the transactional level. These criteria are then associated with the conditions of existence of different EGG links as they are implicitly assumed in the semantics of these graphs. Once the conditions of their creation are known, the semantics of EGG links can be represented explicitly by the use of CGs and Predicate Transition Networks (PrTNs). These representations are then used for detecting different types of EGG links.
Conceptual graphs combined with PrTNs are able to describe the semantic structures equivalent to those contained implicitly in EGGs. However, the semantics of the combined graph which is based on the results of cognitive psychology, natural language processing, as well as logic, are richer than the semantics of the EGG. Furthermore, the operations provided by the conceptual graph theory combined with the constraint specifications as expressed by PrTNs allow the modification of the learner graph. Thus, our proposed representational framework provides the basis for the construction of a deep dynamical student model. An example from the Boolean Algebra domain demonstrates its feasibility.
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Niem, L., Fugére, B.J., Rondeau, P. et al. Defining the semantics of extended genetic graphs. User Model User-Adap Inter 3, 107–153 (1993). https://doi.org/10.1007/BF01099727
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DOI: https://doi.org/10.1007/BF01099727