Laboratory work forms a critical part of the learning experience in computing courses -- it is through practical exercises that students develop their problem solving skills. As educators we would like to be able to keep abreast of how students are progressing. Unfortunately the traditional methods of assessment provide little insight into the problem solving behaviour that has resulted in a successful or unsuccessful submission.
One way to gain insight into the effectiveness of students? problem solving behaviour is to carry out longitudinal studies of their solution attempts -- that is, to look at how effective they are at improving their solutions over time. This paper investigates the use of automated syntactic analysis techniques as part of an e-learning system for categorising student errors and revealing students? problem solving profiles.
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