Abstract
The role AI plays in educational software design and construction is in constant evolution as underlying educational frameworks and paradigms change. Frequent criticisms have arisen with respect to the tutoring-focused, goal-based, knowledge domain transfer, of course material. It has been realized that the modelization of the learning process outweighs the characterization of domain knowledge (Akhras & Self, 1998; Espinosa & Ramos, 1998; Espinosa & Ramos 1999). However, purely instructivist [human, and recently machine] tutors, relying on knowledge transmission, are still mainstream in classrooms around the world (Latchman, Salzman & Gillet, 1999). Therefore, domain models and task models are being complemented with cognitive state models (Andriessen & Sandberg, 1999) and expert machines to handle these (Murray, 1999). According to these lines of thought, however, human cognition is only considered as part of ontology when it comes to learning environments where collaboration enters the scene. We maintain that fulfilling pedagogic goals in an Instructivist courseware always motivate the human being to make use of an autonomous cognitive history and data, both of which are interpreted in particular ways depending on a person’s singularity (Espinosa & Ramos, 1996c). However, such behavior cannot be specified as a consistent model, nor is fully formalizable, given its non-predictive, non-monotonic, non-precise, and holistic, nature. Furthermore, sometimes it is not even perceivable, or evident, to the instructor, the student, or the computer software.
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Ramos, F., Espinosa, E. (2002). A Constructivist Learning Studio Based on Cognitive Time Analysis. In: Chin, W., Patricelli, F., Milutinović, V. (eds) Electronic Business and Education. Multimedia Systems and Applications Series, vol 20. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-1497-8_3
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