This document presents a theoretical approach and a methodology for analyzing data from students interacting with and learning from hypermedia systems. Interactions are mutually influenced by individual students' goals and strategies and the actions supported by the interface of the learning environment. The approach is illustrated by modelling data from an empirical study in which students browsed through a hypertext instructional environment to learn about programming concepts. By using the explanatory power of the computational model, interactions can be analyzed to determine patterns of use. Results obtained from this method of analysis yield specific feedback on system design and prescriptions for improving the design. More theoretically, they provide insights on the nature of human cognition and learning in the context of interactive educational technologies. There are a number of implications for design: (1) it is important to provide high-level navigational aids within hypermedia; (2) designers need to encourage the development of alternate browsing strategies; (3) instructional examples, which are highly valued by students, are important; (4) hypermedia interfaces should also function as memory aids, so as not to interfere with the learning process; and (5) singleton production rules and the uninterpretable cluster should be kept to a minimum. (Contains 15 references.) (AEF)