Investigating Spatial Skills in Computing Education

There is an intriguing connection between spatial skills and CS: those with better spatial skills tend to do better in many CS related tasks. Since spatial skills are malleable, it is tempting to simply introduce spatial skills training courses to students who are struggling and expect positive outcomes. While improved outcomes are being observed, it would be preemptive to introduce such schemes widely without better understanding the relationship. We do not know why spatial skills are important in CS, so while one might take the gains observed at face value, we stand to lose valuable insights into not only the abstract cognition involved in spatial skills which appears to be of value across STEM, but also reflective and nuanced understanding of how people engage with CS education

Developing a Work-based Software Engineering Degree in Collaboration with Industry

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

The Effect of a Spatial Skills Training Course in Introductory Computing

Spatial skills have been associated with STEM success for decades. Research has shown that training spatial skills can have a positive impact on outcomes in STEM domains such as engineering, mathematics and physics; however -- despite some promising leads -- evidence for the same relationship with computing is limited. This research describes a spatial skills intervention delivered to around 60 students in introductory computing courses who tested with relatively low spatial skills, mirroring a well established intervention developed and used by Sorby in engineering for over 20 years. This study has shown correlation between spatial skills and computing assessment marks which was observed both before and after training took place, suggesting that as the students' spatial skills are improved via training, so too is their computing assessment. Students who took part in the intervention also showed a significant increase in class rankings over their peers. The authors consider this to be a good indication that spatial skills training for low spatial skills scorers starting a computing degree is of value

Relating Spatial Skills and Expression Evaluation

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

Improving Computational Thinking with Spatial Skills Development in Primary School

Spatial skills frequently correlate with many measures of computing success, and indeed with wider STEM achievement. Spatial skills training has also been shown to improve computing outcomes at multiple institutions of higher education with first-year university students. However, there is a good chance that even though we can improve the spatial skills of undergraduate students to help them succeed at computing, many students will have already opted-out of computing learning pathways in school due to poor spatial skills. Using a spatialised maths curriculum, we intend to improve the spatial skills of primary school children aged 8–9 and investigate the effect on their computational thinking. With this poster, we would like to share our work so that others can consider deploying similar programmes, and to hear feedback from the CS education community on what other aspects and factors we should consider

What Does Space Look Like in CS? Mapping out the Relationship between Spatial Skills and CS Aptitude

Spatial skills are cognitive skills relating to the mental consolidation of spatial structures and operations. Rotating shapes in one’s head, identifying patterns from obscured environments and parsing 3D structures from 2D representations are some tasks which require spatial skills. It is fairly easy to see how spatial skills – literally, skills to do with space – are associated with success in STEM domains: 3D modelling in engineering, understanding molecular structure in chemistry and conceptualising kinematics in physics. This connection is less clear for CS, where concepts of space are more abstract and can be thought unrelated to problems that programmers typically face [5]. And yet, spatial skills are correlated with CS success and training spatial skills improves CS outcomes. We are left asking: “What does space look like in CS?” Parkinson & Cutts associate spatial skills with visualisation and mental modelling skills [3], and Margulieux’s Spatial Encoding Strategy theory stipulates that developing spatial skills improves one’s capacity to encode mental representations of non-verbal information [2]. This permits processing of more non-verbal information rapidly through effective chunking, freeing up space in working memory (WM) for more complex operations and concurrent representations. That is, effective encoding strategies – related to spatial skills – allow more non-verbal information to be retained in WM and for multiple mental models to be held at once. But how does this look in CS specifically? In this abstract we highlight some existing research in our initial findings which point towards CS success depending – at least in part – on encoding strategies: These are just some examples of theories and strategies applied in CS which appear to depend on non-verbal encoding skills and therefore are related to spatial skills. We will present several connections by tying many perspectives of skills required for computing success back to non-verbal encoding skills, thus providing a model of the relationship between CS and spatial skills. Our goal with this poster is to solicit feedback on our model from the ICER community, from spatial skills factors all the way to application in CS. We want to hear perspectives on CS skills and attributes that we may have missed and determine if they relate to non-verbal encoding. Finally, we want to continue the discussion of spatial skills and abstract cognitive skills at ICER, a venue which has shown appreciation for these ideas in the past

Understanding Spatial Skills and Encoding Strategies in Student Problem Solving Activities

Background and Context. Margulieux’s Spatial Encoding Strategy theory (SpES) provides a possible reason for the relationship between spatial skills and success in STEM fields, including CS. While there is indirect evidence to suggest that the theory holds, there is little work which explicitly explores the core theory in practice. Furthermore, current work in spatial skills has largely focused on introductory courses, and it is unclear whether advanced students (and then experts) use spatial skills in computing. Objectives. We wish to determine whether we can see senior students in CS with high spatial skills utilising non-verbal encoding strategies when solving CS programming problems. Method. Transcripts from a think-aloud exercise with experienced students (final year of undergraduate), whose spatial skills were measured, were analysed to identify utterances which indicated spatial encoding strategies being employed, such as the construction and alteration of mental models on the fly, and to determine differences according to spatial skills level. Findings. Students with higher spatial skills were more likely to exhibit evidence of the construction of flexible, comprehensive mental models to solve the programming problems, demonstrating advanced encoding and chunking strategies. Students with lower spatial skills were more likely to struggle with the construction and alteration of mental models, indicating that they typically lack the capability to effectively chunk and save working memory space. Implications. This work confirms the predictions of SpES more precisely than prior work by showing that skilled problem solving involves the mental model creation and manipulation that underlies SpES. It demonstrates that students with better spatial skills are more likely to succeed in programming problem solving, even in the later stages of study, due to their ability to encode non-verbal information

Chairs' award: investigating the relationship between spatial skills and computer science

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

Devising Work-based Learning Curricula With Apprentice Research Software Engineers

Work-based learning (WBL) is a delivery model that attempts to address the isolation of theory and practice by integrating them into a single programme. The concern is that through lack of experience and understanding, both universities and industry may devise `Frankenstein' curricula, harming individuals rather than helping them. This poster introduces a small project to support curricula development by proposing universities act as both the learning provider and workplace for apprentice Research Software Engineers (RSEs)

Forming Community in Computing Science Education with Research in Practice Project Activities

The United Kingdom and Ireland Computing Education Research (UKICER) conference is emerging as a leading venue to disseminate research contributions to the community. However, it is important the venue continues to act as an entry point for individuals to participant in computing science education research. Consequently, the present proposal is to offer a new form of collaborative, community-forming activity at the UKICER conference called Research in Practice Project Activities (RIPPAs). The first RIPPA is focused on Spatial Skills and Computing Science and will be offered at UKICER 2021