The relationship between spatial skills training and computer science learning is unclear. Reported experiments provide tantalising, though not convincing, evidence that training a programming student's spatial skills may accelerate the development of their programming skills. Given the well-documented challenge of learning to program, such acceleration would be welcomed. Despite the experimental results, no attempt has been made to develop a model of how a linkage between spatial skills and computer science ability might operate, hampering the development of a sound research programme to investigate the issue further. This paper surveys the literature on spatial skills and investigates the various underlying cognitive skills involved. It poses a theoretical model for the relationship between computer science ability and spatial skills, exploring ways in which the cognitive processes involved in each overlap, and hence may influence one another. An experiment shows that spatial skills typically increase as the level of academic achievement in computer science increases. Overall, this work provides a substantial foundation for, and encouragement to develop, a major research programme investigating precisely how spatial skills training influences computer science learning, and hence whether computer science education could be significantly improved.

Vast numbers of publications in computing education begin with the premise that programming is hard to learn and hard to teach. Many papers note that failure rates in computing courses, and particularly in introductory programming courses, are higher than their institutions would like. Two distinct research projects in 2007 and 2014 concluded that average success rates in introductory programming courses worldwide were in the region of 67%, and a recent replication of the first project found an average pass rate of about 72%. The authors of those studies concluded that there was little evidence that failure rates in introductory programming were concerningly high. However, there is no absolute scale by which pass or failure rates are measured, so whether a failure rate is concerningly high will depend on what that rate is compared against. As computing is typically considered to be a STEM subject, this paper considers how pass rates for introductory programming courses compare with those for other introductory STEM courses. A comparison of this sort could prove useful in demonstrating whether the pass rates are comparatively low, and if so, how widespread such findings are. This paper is the report of an ITiCSE working group that gathered information on pass rates from several institutions to determine whether prior results can be confirmed, and conducted a detailed comparison of pass rates in introductory programming courses with pass rates in introductory courses in other STEM disciplines.

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Work-based learning has been in practice in Software Engineering for some time, but only in recent years has it been introduced as a pathway to an honours-level undergraduate degree across the UK. Through the lens of one such scheme, the Graduate Apprenticeship programme in Scotland, we have investigated what challenges work-based learning degree programmes are likely to face and took this question to 26 industry partners. Also, since we are aware of a persistent skills gap between Software Engineering graduates and entry-level industry roles, we investigated the skills that Software Development teams are looking for in Scotland. This paper details our findings concerning perceived challenges to industry, the skills and knowledge to be imparted at university and the workplace learning opportunities which can be exploited by companies. CCS CONCEPTS• Social and professional topics → Industry statistics.

Work connecting spatial skills to computing has used course grades or marks, or general programming tests as the measure of computing ability. In order to map the relationship between spatial skills and computing more precisely, this paper picks out a particular subset of possible programming concepts and skills, that of expression evaluation. The paper describes the development of an expression evaluation test, which aims to identify participants' ability to perform evaluations of expressions across a range of complexity. The results indicate participants' expression evaluation ability was significantly correlated with a spatial skills test (r=0.48), even more so when only considering those with less prior programming experience (r=0.58). Thus, we have determined that spatial skills are of value in expression evaluation exercises, particularly for beginners. CCS CONCEPTS• Social and professional topics → Computing education.