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Start date: 1995
This research project aims to produce a computational model of how students learn to program in LISP. Programming is a complex skill, and research into program synthesis has shown that it cannot be done without knowledge. Whist this research aims to be able to synthesise computer programs, the focus of the work is to model how students learn to program, and thus have a handle on being able to identify the knowledge used in designing programs. Thus in contrast to much research into program synthesis, the approach here is within Cognitive Science, and attempts to develop a computer program capable of learning to program in LISP in a similar way to people, but restricting the designs to functional programming.
LISP is an ideal language for modelling the task of learning to program for four important reasons:
1. Much programming exploits knowledge of other domains such as mathematics, but elementary LISP programming does not.
2. LISP is the ideal language for synthesising programs, since LISP functions are easily created and modified at run time.
3. It is straightforward to design programs to reason about functionally designed LISP programs.
4. The research builds on the established expertise of Furse and Sewell in their work on parallel processing where similar techniques have been employed.
Kevin Sewell is registered for a part-time PhD at the University of Glamorgan to conduct this research.
Page by Kevin H. Sewell
Last updated 24/October/95