Proceedings of the Annual Meeting of the Cognitive Science Society

While recent studies have demonstrated various ways that transfer might be achieved in a domain, the measures used to assess transfer rarely stray from lime and error data. This paper examines transfer in the complex skill of computer programming in order to explore more flexible and sensitive methods of assessing transfer. In the experiment, subjects wrote both a P A S C A L and a LISP version of two programming problems. Although a simple accuracy measure provides evidence for knowledge transfer between the two programming languages, measures based on analyses of the task domain (i.e., partialcredit accuracy, strategy use) provide much stronger evidence. Curiously, these measures target different subjects as exhibiting transfer, suggesting that more than one type of knowledge may be available for transfer.