Predicting the success of students participating in introductory programming courses has been an active research area for more than 25 years. Until recently, no variables or tests have had any significant predictive power. However, Dehnadi and Bornat claim to have found a simple test for programming aptitude to cleanly separate programming sheep from non-programming goats. We briefly present their theory and test instrument. We have repeated their test in our local context in order to verify and perhaps generalise their findings, but we could not show that the test predicts students ’ success in our introductory programming course. Based on this failure of the test instrument, we discuss various explanations for our differing results and suggest a research method from which it may be possible to generalise local results in this area. Furthermore, we discuss and criticize Dehnadi and Bornat’s programming aptitude test and devise alternative test instruments.

Computing educators may hope that postsecondary courses both convey content and also give students a new perspective on computing. In the study described in this paper, a sample of students about to graduate with their postsecondary degrees wrote about their relationship with computing and what influenced that relationship. Computing majors wrote expressively about the excitement and breadth of the discipline. Other majors were positive about computing, but the essays indicate that postsecondary education (including introductory computer science courses) did not have a large effect on their attitudes about computing.

Abstract: Assuming that understanding object-oriented programming requires the understanding of object-interaction, this article outlines the development of a theoretical model that provides a framework to assess a hierarchy of competences related to object-interaction. A newly developed test allows for an in-depth analysis of this hierarchy, including its relationship with other (e.g. more ‘traditional’) factors that impact students ’ understanding of objectoriented programming. Based on a study at two learning institutions, we conclude that the proposed model is an effective tool for describing different competence levels. The analysis of how different factors influence students’ object-interaction skills shows a correlation between object-interaction and imperative programming, as well as self-efficacy; the correlation between object-interaction and math, however, was weak. We found that the degree of visibility of object-interaction in the program text is the most critical factor for understanding object-interaction. The analysis is followed by a discussion of the implications of the findings for teaching.