Elie Milgrom

Constructivist learning: operational criteria for cognitive flexibility

Constructivism is a learning theory which states that people learn best when they actively construct their own knowledge. Many different perspectives exist on constructivist pedagogical principles and on how to apply them to instructional design. It is thus not only difficult to evaluate the conformity of existing learning systems with constructivist principles, it is also quite hard to ensure that a new learning system being designed ultimately facilitates and stimulates constructivist learning. Our research aims to help designing truly constructivist learning systems. For that purpose, we must clarify what constructivism entails in an operational manner: we need criteria enabling one to determine which aspects of a learning system actually embody constructivist principles. Cognitive flexibility is a pedagogical principle that is often mentioned among the basic characteristics of constructivism. This paper proposes operational criteria for cognitive flexibility and presents both justifications and examples of their use. These criteria should be applicable to many instructional situations.

Optimization at a High Level of Abstraction

This paper presents an optimization to an insertion algorithm for nearly complete binary search trees. The original algorithm was published recently by T.E. Gerasch in the Communications of the ACM ([Ger88]). Its insertion time is logarithmic in the best case, and linear in the worst case. With the optimization proposed here, some insertions that would require linear time with Geraschs algorithm are handled in logarithmic time. The proposed optimization does not modify the worst case nor the best case behaviour of the algorithm.