A connectionist model of instructed learning
David C. Noelle, Garrison W. Cottrell · 1996
The focus of this research is on how people blend knowledge gained through explicit instruction with knowledge gained through experience. The product of this work will be a cognitively plausible computational learning model which integrates instructed learning with inductive generalization from examples. The suc-cess of this model will require the attainment of both a technical and a scientific goal. The technical goal is the design of a computational mechanism in which induction and instruction are smoothly integrated. The design of such a multistrat-egy learner might be implemented within a symbolic rule-based framework (Huffman, Miller, & Laird 1993), within a framework strong in inductive generalization, such as connectionism (Noelle & Cottrell 1995), or