System Intelligence in Constructivist Learning

The aim of this paper is to present a perspective on intelligent systems to support learning that is in line with constructivist views of learning. In order to develop such a perspective we have defined formal mechanisms to support knowledge representation, reasoning, and decision making in intelligent systems, that are attuned to the values of constructivist views of learning. These point to the importance of the context of learning, stress that learning involves active interaction, and emphasise the process rather than the product of learning. The theoretical models that constitute our approach enable intelligent learning environments to evaluate learning according to four properties of constructivist learning processes: cumulativeness, constructiveness, self-regulatedness, and reflectiveness, and to make decisions about the learning opportunities to be provided to the learners, taking into consideration the affordances of learning situations regarding these properties. The approach has been implemented in INCENSE, which is an intelligent learning environment in the domain of software engineering.

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