Robert G. Farrell

Learning to program in LISP

We have gathered protocols of subjects in their first 30 hours of learning LISP. The processes by which subjects write LISP functions to meet problem specifications has been modeled in a simulation program called GRAPES (Goal Restricted Production System). The GRAPES system embodies the goal-restricted architecture for production systems as specified in the ACT* theory ( Anderson, 1983a , Anderson, 1983b, August ). We compare our simulation to human protocols on a number of problems. GRAPES simulates the top-down, depth-first flow of control exhibited by subjects and produces code very similar to subject code. Special attention is given to modeling student solutions by analogy, how students learn from doing, and how failures of working memory affect the course of problem-solving. Of major concern is the process by which GRAPES compiles operators in solving one problem to facilitate the solution of later problems.

Learning to Program in LISP1

We have gathered protocols of subjects in their first 30 hours of learning LISP. The processes by which subjects write LISP functions to meet problem specifications has been modeled in a simulation program called GRAPES (Goal Restricted Production System). The GRAPES system embodies the goal-restricted architecture for production systems as specified in the ACT* theory (Anderson, 1983). We compare our simulation to human protocols on a number of problems. GRAPES simulates the top-down, depth-first flow of control exhibited by subjects and produces code very similar to subject code. Special attention is given to modeling student solutions by analogy, how students learn from doing, and how failures of working memory affect the course of problem-solving. Of major concern is the process by which GRAPES compiles operators in solving one problem to facilitate the solution of later problems.