This research addresses ihc need for effective ways of teaching computer programming. It focuses on two aspects of instruction. First, the research investigates the use of analogy in teaching programming. It extends existing research by investigating what constitutes a good analogy. Second, the research investigates the effect of depth of encoding on programming performance. The factors analogy and encoding were manipulated in a 3 X 2 factorial design. Analogy was operalionalized by varying iJie clarity and systcmaticity/absu-actncss of the analogies used. Encoding was operationalized by varying the frequency with which deep encoding and elaboration of learned material were invoked by the presentation of questions on the learned material. The dependent variables were score obtained on program comprehension and program composition tasks and the time taken to perform the tasks. Research subjects were 15- to 17-year-olds without prior exposure to computer programming. Differences in mathematics ability and age were controlled. The results provide empirical support for a predictive theory of the relative goodness of competing analogies. They provide only marginal support for depth of encoding (as opcrationalizcd) in learning computer programming effectively. Post hoc data analysis suggests that good analogies assist the learning of semantics but not syntax. Furthermore, the effect of encoding was only apparent in learning syntax but not semantics.

We describe COGNITIO, a computational theory of learning and cognition, and provide evidence of its psychological validity by comparing the protocols of a student learning to program in Smalltalk against a COGNTTIO-based computer simulation of the same. COGNITIO is a production system cognitive architecture that accounts parsimoniously for human learning based on three learning mechanisms: schema formation, episodic memory, and knowledge compilation. The results of simulation support the validity of COGNITIO as a computational theory of learning and cognition. W e also draw some implications of COGNITIO for the teaching of complex problem solving skills.

Sense-making is an essential process in learning for understanding. W e describe a study of sense-making involving two pairs of students learning basic elements of the visual programming language Prograph. The study emphasizes the critical role of activity in mediating concept development and refinement Video protocols of learning behavior were recorded and analyzed. The analysis focuses on the situated nature of the meaning construction process. It reveals how exploration, explanation, and expectation play important roles in the sense-making process.