The epistemological divergence of Digital Humanities (DH) and Computer Science (CS) means that DH students are trying to understand and use computing in a way that is fundamentally different from its conceptualisation in CS. They represent a distinct group of computing learners whose needs and challenges remain under-explored. Additionally, little work has been dedicated to the difficulties faced by DH computing instructors, who do not have a unified curriculum on which to draw and often lack training in one of the knowledge traditions they are trying to teach. Through semi-structured interviews with 27 DH computing instructors and eight students, this paper aims to provide a snapshot of the current state of DH computing education and its key concerns and open questions. The qualitative analysis presented interrogates instructor training and outlooks on the field, shared learning outcomes and classroom practices, and student learning challenges. It further highlights and explores ongoing debates between seemingly contradictory instructional approaches. This work stands to act as an introductory roadmap for instructors new to teaching computing in a DH context and lay the foundations for the development of discipline-specific pedagogical resources. In light of its expanding scope and emergent concerns, we posit that our findings may also be relevant to the wider CS education community.

The software engineering graduate apprenticeship program at the School of Computing, University of Glasgow, has a significant emphasis on work-based learning (WBL), with approximately 80% of the students' time over four years spent in the workplace. This work-based aspect of the program plays a more prominent role in the final two years, by which time apprentices are undertaking increasingly larger roles in the workplace. In this report, we present how we addressed the challenge of structuring and assessing WBL in these senior years such that there is a balance between professional competency attainment and ranked academic achievement, while providing a fair and flexible structure. Based on a model of WBL presented by Raelin in 1997, we outline our rationale for dividing the assessments into workplace projects, workplace journal, and a portfolio of artefacts. The projects are categorised into different types both for flexibility and to encourage academia-industry collaboration, the workplace journal encourages higher forms of reflection, while the portfolio assessment encourages and assesses the attainment of professional competencies. We present our experience of implementing this structure, an analysis of student feedback, and the adjustments made in response. With an increasing focus on work-ready skills and competency-based education in software engineering education, we expect the theory-informed structure we developed, and our experience of running and adapting it, to serve as an exemplar for developing a WBL program at research-led institutions.

There is a growing body of literature on the relationship between spatial skills and computing success and evidence that developing spatial skills can improve computing outcomes, but almost all of this research has been conducted in higher education. To explore the link between spatial and computing skills in young people, we present the results of a spatial skills intervention deployed in maths lessons for 7--8-year-olds. Compared to a control group, pupils who received spatial instruction improved significantly more in tests of computational thinking despite not receiving deliberate computing instruction. We also explore some demographic factors relating to spatial skills and CT scores, finding previously observed demographic distinctions replicated in this population.

Over the past decades, computer science education (CSEd) research has studied the multitude of factors that may impact student success in introductory programming courses (CS0/CS1). The lack of foundational structure behind how these factors interrelate has made it difficult to gain a thorough understanding of this area of CSEd literature. Gaining a deeper understanding and applying structure to these factors would allow CSEd to adopt better teaching practices, study habits, learning environments, course materials, etc. and to better understand the student experience to better foster success among a broader population of students. Our systematic literature review used search criteria for factors that predicted student success in CS0/CS1, which yielded 311 research articles. We then mapped this body of work under the Biggs' 3P (Presage, Process, Product) educational model, which provides a comprehensive framework for how students engage with learning opportunities. We discovered that although many studies focused on the Presage and Product phases of the model, fewer studies mapped to the Process phase, which describes the students' active learning processes. Our study shows there is a potential gap in the literature and future studies should focus more specifically on how students choose to engage with learning opportunities and what factors may be hindering that engagement throughout a learning period.

Teachers face challenges in teaching new subjects at the early primary level. The difficulties vary from subject to subject. Teachers' first challenge in Computer Science (CS) and Computational Thinking teaching is their technological literacy and competency challenges. Lack of confidence, time, and willingness are significant reasons for the challenge. One of the studies on mathematics teaching shows that teachers need more knowledge tools and models to facilitate the analysis during the teaching process. Researchers assert that educational practice has focused more on technology than on new pedagogies needed to truly use technology in a transformative way. Frameworks are designed to meet high-level objectives set by the authorities. Teachers are provided with teaching materials for developing the course contents. The frameworks act as a connection between high-level objectives and low-level teaching materials. In this paper, we present the elaboration of a framework for teaching CS at the early stages of education. The framework consists of three components based on modelling real-world problems into a machine-world context and then realising the machine solution in the real world. Moreover, the problem-solving component of the framework emphasizes the iterative process of learning that strengthens the previous concepts and provides a logical con-nection between the previous and new concepts. The framework was evaluated in the context of Saudi Arabia, where the teachers were interviewed individually and then provided with a guide for teaching grade-4 learners. The guide was developed using the material provided by the Saudi Ministry of Education. The teachers taught using this guide over a sequence of lessons. At the end of this time, a second individual teacher interview was conducted to determine teacher experience. The results show that teaching using the framework is effective, and it is not only easier for teachers to understand the teaching method but also for learners to learn the content quickly.

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.

This working group concerns the adoption of computing education (CE) in undergraduate computer science (CS) programmes. Such adoption requires both arguments sufficient to persuade our departmental colleagues and our education committees, and also curricular outlines to assist our colleagues in delivery. The goal of the group is to develop examples of both arguments and curricular outlines, drawing on any prior experience available.

Argumentation, as the generation and evaluation of arguments, is critical in our ability to reason. Computing education research has long highlighted the relation between reasoning ability and programming skills but, to our knowledge, the relation between argumentative reasoning, and particularly collective argumentative reasoning, and programming have not yet been investigated. The aim of this paper, therefore, is twofold: first, to study empirically the nature of collective argumentative reasoning in programming during problem-solving and secondly, to identify the aspects of argumentation that facilitate or obstruct collective problem-solving. To achieve these aims, through an exploratory research design, our study identifies the argumentative moves and argumentative reasoning schemes employed by expert programmers, MSc students, and first-year undergraduate students (novices) during collective problem-solving by using a protocol analysis of concurrent verbalisations. The study illustrates how collective argumentative reasoning is reflected in the discourses of these groups during problem-solving, and most importantly how argumentative moves and argumentative reasoning schemes interact and impact problem-solving. The three groups exhibited substantial differences: novices engaged in collective monologue, the MSc students engaged in collective but egotistic argumentative dialogue and the experts in collective and altruistic argumentative dialogue. The paper concludes by proposing a turn in educational practices that place argumentative reasoning in the center of both classroom and peer to peer discourse in programming.

An increasing number of students arrive at university with programming experience and pre-formed mental models. These models are often incorrect, with students holding entrenched misconceptions. In this paper, we describe a study that investigated whether making explicit connections between our introductory Python programming and computing systems courses could expose mental models and help identify and fix misconceptions. We hypothesised that students would develop a correct mental model by creating a low level systems implementation of a high level program. While we identified misconceptions, these prevented the students from making explicit links and correcting their mental models. We detail these misconceptions, develop a set of hypotheses for why these were held, and suggest future studies.

Four years ago, the authors' institution conducted a spatial skills test with entry level computing students. At the time of writing, these students have just graduated and some agreed to have their academic record over the course of their programme examined. In particular, we wished to discover whether a spatial skills test taken in the students' first year of study was indicative of their final GPA, whether the correlation between grades and spatial ability in their first year rose or declined over the intervening years and to expose the courses in later years of study which most strongly correlated with spatial ability.

Concerns about participation in computer science at all levels of education continue to rise, despite the substantial efforts of research, policy, and world-wide education initiatives. In this paper, which is guided by a systematic literature review, we investigate the issue of inequalities in participation by bringing a theoretical lens from the sociology of education, and particularly, Bourdieu’s theory of social reproduction. By paying particular attention to Bourdieu’s theorising of capital, habitus, and field, we first establish an alignment between Bourdieu’s theory and what is known about inequalities in computer science (CS) participation; we demonstrate how the factors affecting participation constitute capital forms that individuals possess to leverage within the computer science field, while students’ views and dispositions towards computer science and scientists are rooted in their habitus which influences their successful assimilation in computer science fields. Subsequently, by projecting the issue of inequalities in CS participation to Bourdieu’s sociological theorisations, we explain that because most interventions do not consider the issue holistically and not in formal education settings, the reported benefits do not continue in the long-term which reproduces the problem. Most interventions have indeed contributed significantly to the issue, but they have either focused on developing some aspects of computer science capital or on designing activities that, although inclusive in terms of their content and context, attempt to re-construct students’ habitus to “fit” in the already “pathologized” computer science fields. Therefore, we argue that to contribute significantly to the equity and participation issue in computer science, research and interventions should focus on restructuring the computer science field and the rules of participation, as well as on building holistically students’ computer science capital and habitus within computer science fields.

Motivation More and more high schools are teaching programming, and in many cases, teachers teach multiple programming languages to the same group of students. Objectives The goal of this paper is to explore the views of high-school teachers on second and subsequent programming languages, including their motivation for teaching multiple languages, their struggles, and their use of transfer strategies when they teach their second or third programming language. Method The study consists of semi-structured interviews with 23 high-school teachers in two European countries. Results Our findings indicate that school pupils face the same issues as university students when moving from first to subsequent languages. Furthermore, the teachers’ attitudes towards second language learning are highly variable, both positive and negative, with some supportive teaching strategies used, but many less helpful ones in evidence too. Discussion Our findings suggest that the value of second language learning needs to be highlighted in teacher professional development materials more strongly and that teachers might need more support in implementing transfer strategies.

Students across disciplines are increasingly wrangling their data programmatically. Previous research indicates that graphical, instructor-provided subgoals could help novices solve data wrangling tasks, and that graphical thumbnails could make the syntax documentation more usable. Using a 2x2 design, we trialled different versions of a web application for teaching data wrangling, which contains both programmatic and non-programmatic exercises. Half of all participants received graphical subgoals to visualise data wrangling solutions instead of just textual subgoals, and half received graphical thumbnails. Performance and time on task are reported, but did not result in any significant effect. We discuss possible reasons why.

We needed to design a module covering both discrete maths and algorithms for a Work Based Learning (WBL) Software Engineering degree programme, where students spend half their time at their employers' workplace. This entails deciding the order of topics, and explaining that to students. Sequence in the course is only one kind of relationship between topics in the module; relevance to work is another. Such explaining is a neglected educational issue. This paper addresses how to convey these relationships to learners. Because of the WBL context, it is inevitable that questions about how pieces of academic learning relate to the work context (which these students are already experiencing) arise immediately and vividly for them. This is important because it affects learner motivation, sometimes greatly, and also whether they are likely to learn in a surface or a deep mode. A given learner's grasp of these relationships is both individual and changes over time. Because of this, the general pedagogical approach discussed here is “little and often”: raising it a number of times, with an emphasis not on one exhaustive and rigid view but on how different students often see it differently, and encouraging each to gradually develop their own view. The concept map diagram in this paper illustrates only one example of how the web of connections might be represented and conveyed during the course.

Prior research has shown that students face transition challenges between programming languages (PL) over the course of their education. We could not find research attempting to devise a model that describes the transition process and how students' learning of programming concepts is affected during the shift. In this paper, we propose a model to describe PL transfer for relative novices. In the model, during initial stages of learning a new language, students will engage in learning three categories of concepts, True Carryover Concepts, False Carryover Concepts, or Abstract True Carryover Concepts; during the transition, learners automatically effect a transfer of semantics between languages based on syntax matching. In order to find support for the model, we conducted two empirical studies. Study 1 investigated near-novice undergraduate students transitioning from procedural Python to object-oriented Java while Study 2 investigated near-novice postgraduate students doing a transfer from object-oriented Java to procedural Python. Results for both studies indicate that students had little or no difficulty with transitioning on TCC due to positive semantic transfer based on syntax similarities while they had the most difficulty transitioning on FCC due to negative semantic transfer. Students had little or no semantic transfer on ATCC due to differences in syntax between the languages. We suggest ways in which the model can inform pedagogy on how to ease the transition process.

Academics and employers can partner to deliver professional software engineering education via work-based learning (WBL) programmes. These programmes have the potential to engage and motivate under-represented groups, including those that would not normally engage in higher education. However, challenges still exist in supporting such individuals in participating in WBL programmes. Consequently, we discuss a project on broadening participation in WBL software engineering to support individuals from under-represented groups to participate in software engineering education.

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.

It is a natural part of a student's computing education to transfer from language to language, hence adopting to a new programming language (PL) quickly is a necessary skill. Prior work in computer science research mainly brings awareness of the success and difficulties that students face when learning new languages. In addition, work that directly relates to PL transfer mainly concerns experienced programmers problem solving in a new language, evidencing plan transfer. We could not find research attempting to devise a model of PL transfer based on code comprehension. We explore this phenomenon in the context of five university students transitioning from procedural Python to object-oriented Java, over a period of 10 weeks. We analyse the results through the lens of a model of second language acquisition using the notion of Semantic transfer and the Mindshift learning theory (MLT). The findings indicate that during the initial learning stages, learners relied mostly on their syntactic matching between Python and Java and subsequent semantic transfer which affected their learning positively on Carryover concepts and negatively on Changed concepts. Students could not transfer their semantic knowledge on concepts they perceived as Novel. An understanding of the transfer process learners go through during a shift can help inform our pedagogy on how to ease the transition process and achieve an effective learning process, and we provide pointers in this direction.

Cooperative programmes are principally partnerships between academia and industry to deliver education partly on campus and partly in the workplace. Mentors in the workplace are crucial in such cooperative programmes as they scaffold appropriate development activities for students. A workplace mentor in this situation is important not only for the development of detailed technical knowledge, but also in the development of software engineering skills that are almost never in fact taught in higher education, e.g. navigating large, neglected code bases. Consequently, workplace mentors are a key component of any high-quality education programme delivered in partnership with industry. However, higher education institutions and enterprises not only need to appreciate the importance of mentors in such schemes, but also ensure such staff are supported to use their experience to increase their skill as a mentor. Mentors need the space and support to reflect on their own practice, develop skills and attain new knowledge. In this sense, the challenge is not dissimilar to that faced by computing science school teachers that need to continually consider their own practice as well as have the time to consider emerging programming languages and frameworks. Many of the structures and existing research on how to support computing science school teachers could be adapted to support these workplace mentors, e.g. support groups.

Goal-directed problem-solving labs can lead a student to believe that the most important achievement in a first programming course is to get programs working. This is counter to research indicating that code comprehension is an important developmental step for novice programmers. We observed this in our own CS-0 introductory programming course, and furthermore, that students weren't making the connection between code comprehension in labs and a final examination that required solutions to pencil-and-paper comprehension and writing exercises, where sound understanding of programming concepts is essential. Realising these deficiencies late in our course, we put on three 3-hour optional revision evenings just days before the exam. Based on a mastery learning philosophy, students were expected to work through a bank of around 200 pencil-and-paper exercises. By comparison with a machine-based hackathon, we called this a Thinkathon. Students completed a pre and post questionnaire about their experience of the Thinkathon. While we find that Thinkathon attendance positively influences final grades, we believe our reflection on the overall experience is of greater value. We report that: respected methods for developing code comprehension may not be enough on their own; novices must exercise their developing skills away from machines; and there are social learning outcomes in programming courses, currently implicit, that we should make explicit.

This working group asserts that Program Comprehension (PC) plays a critical part in the writing process. For example, this abstract is written from a basic draft that we have edited and revised until it clearly presents our idea. Similarly, a program is written in an incremental manner, with each step being tested, debugged and extended until the program achieves its goal. Novice programmers should develop their program comprehension as they learn to code, so that they are able to read and reason about code while they are writing it. To foster such competencies our group has identified two main goals: (1) to collect and define learning activities that explicitly cover key components of program comprehension and (2) to define possible learning trajectories that will guide teachers using those learning activities in their CS0/CS1 or K-12 courses.

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).

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.

Drawing on the long debate about whether computer science (CS) and computational thinking skills are innate or learnable, this working group is based on the following hypothesis: The apparent innate ability of some CS learners who succeed in CS courses despite no prior exposure to computing is a manifestation of early childhood experiences and learning outside formal education.

Peer Instruction (PI) is a student-centric pedagogy in which students move from the role of passive listeners to active participants in the classroom. Over the past five years, there have been a number of research articles regarding the value of PI in computer science. The present work adds to this body of knowledge by examining outcomes from seven introductory programming instructors: three novices to PI and four with a range of PI experience. Through common measurements of student perceptions, we provide evidence that introductory computing instructors can successfully implement PI in their classrooms. We find encouraging minimum (74%) and average (92%) levels of success as measured through student valuation of PI for their learning. This work also documents and hypothesizes reasons for comparatively poor survey results in one course, highlighting the importance of the choice of grading policy (participation vs. correctness) for new PI adopters.

Recent work in computing has converged on a collection of complementary findings suggesting the value of the Peer Instruction (PI) pedagogy. Compared to lecture, PI has been shown to decrease fail rates, increase final exam grades, and increase engagement and enjoyment. In PI, students work together to exchange perspectives and use clickers to answer challenging conceptual questions in the presence of a knowledgeable instructor.

Recent work in computing has converged on a collection of complementary findings suggesting the value of the Peer Instruction (PI) pedagogy. Compared to lecture, PI has been shown to decrease fail rates, increase final exam grades, and increase engagement and enjoyment. In PI, students work together to exchange perspectives and use clickers to answer challenging conceptual questions in the presence of a knowledgeable instructor.

Although studies have shown Peer Instruction (PI) in computing courses to be beneficial for learning and retention, study of the student experience has been limited to attitudinal survey results. This study provides a preliminary evaluation of student experiences in a PI course -- specifically asking them to reflect on their role as a student in a PI lecture compared to a standard university lecture. Student responses to this question are first analyzed using Chi's Interactive-Constructive-Active-Passive framework which categorizes student activities by their value in a constructivist learning framework. This analysis finds that the majority of students reported activity in a PI lecture as "interactive" in contrast with "active" (e.g. taking notes) in a standard lecture. Additionally, a grounded theory open-coding analysis provides an initial examination of student perceptions of the PI lecture experience. Although students positively value learning-related aspects (feedback and increased understanding) a surprising breadth of value was noted around issues of affect and increased sense of community. In particular, these experiences invite discussion about PI and issues of STEM retention in post-secondary education.

We report on a post-hoc analysis of introductory programming lecture materials. The purpose of this analysis is to identify what knowledge and skills we are asking students to acquire, as situated in the activity, tools, and culture of what programmers do and how they think. The specific materials analyzed are the 133 Peer Instruction questions used in lecture to support cognitive apprenticeship -- honoring the situated nature of knowledge. We propose an Abstraction Transition Taxonomy for classifying the kinds of knowing and practices we engage students in as we seek to apprentice them into the programming world. We find students are asked to answer questions expressed using three levels of abstraction: English, CS Speak, and Code. Moreover, many questions involve asking students to transition between levels of abstraction within the context of a computational problem. Finally, by applying our taxonomy in classifying a range of introductory programming exams, we find that summative assessments (including our own) tend to emphasize a small range of the skills fostered in students during the formative/apprenticeship phase.

Constructivist learning theory suggests that learners must construct their own understandings, rather than have understanding passively dumped into their brains. These findings support the US National Research Council's recommendations for the adoption of active learning pedagogies in the classroom. However, the "classroom lecture" is only one of the resources students commonly have for learning in higher education. In this paper, we present exploratory homeworks -- a tool to support active learning for teaching programming languages. By leveraging the opportunity for the student to interact with the computer/compiler, we seek to provide a model for students of how to explore and understand programming language constructs and concepts. We report on the use of 15 exploratory homework assignments used in a CS0 course with 440 students in Winter 2011. We provide a model and advice for others wishing to develop exploratory homeworks for their programming courses and present quantitative and qualitative evidence regarding students' positive valuation of the homeworks.

Computing and computation are increasingly pervading our lives, careers, and societies - a change driving interest in computing education at the secondary level. But what should define a "general education" computing course at this level? That is, what would you want every person to know, assuming they never take another computing course? We identify possible outcomes for such a course through the experience of designing and implementing a general education university course utilizing best-practice pedagogies. Though we nominally taught programming, the design of the course led students to report gaining core, transferable skills and the confidence to employ them in their future. We discuss how various aspects of the course likely contributed to these gains. Finally, we encourage the community to embrace the challenge of teaching general education computing in contrast to and in conjunction with existing curricula designed primarily to interest students in the field.

We examine five outreach programmes that introduce school students to Computer Science. All downplay programming as a pre-requisite skill for engaging with Computer Science, yet they use a wide variety of formats for reaching students, including contests, shows, magazine articles, and resources for teachers. We classify these different approaches, identifying the different ways they have been adapted to their target audience, and drawing out the common elements to provide guidance for similar initiatives.

Peer Instruction (PI) has a significant following in physics, biology, and chemistry education. Although many CS educators are aware of PI as a pedagogy, the adoption rate in CS is low. This paper reports on four instructors with varying motivations and course contexts and the value they found in adopting PI. Although there are many documented benefits of PI for students (e.g. increased learning), here we describe the experience of the instructor by looking in detail at one particular question they posed in class. Through discussion of the instructors' experiences in their classrooms, we support educators in consideration of whether they would like to have similar classroom experiences. Our primary findings show instructors appreciate that PI assists students in addressing course concepts at a deep level, assists instructors in dynamically adapting their class to address student misunderstandings and, overall, that PI encourages students to be engaged in conversations which help build technical communication skills. We propose that using PI to engage students in these activities can effectively support training in analysis and teamwork skills.

Introductory programming classes are renowned for their high dropout rates. The authors propose that this is because students learn to adopt a fixed mindset towards programming. This paper reports on a study carried out with an introductory programming class, based on Dweck's mindset research. Combinations of three interventions were carried out: tutors taught mindset to students; growth mindset feedback messages were given to students on their work; and, when stuck, students were encouraged to use a crib sheet with pathways to solve problems. The study found that the mixture of teaching mindset and giving mindset messages on returned work resulted in a significant change in mindset and a corresponding significant change in test scores - improvements in test scores were found in a class test given immediately after the six-week intervention and at the end-of-year exam. The authors discuss the results and the strengths and weaknesses of the study.

Peer Instruction (PI) is a pedagogical technique to increase engagement in lectures. Students answer a multiple choice question (MCQ) typically using clickers (hand-held remote devices with a minimum of 5 option buttons), discuss the question with their peers, and then answer the question again. In physics, PI has years of evidence of increased conceptual learning, as measured by the Force Concept Inventory (FCI)[7]. In this experience report, we describe how PI was applied in CS1 and CS1.5 courses teaching Java. We identify specifics of the standard PI model which were adopted, adapted, or discarded for use in introductory computing, describe the process involved for the instructor, give examples of the types of questions asked of students, report on students' performance in answering these questions, reflect on the value for the instructor, and report the attitudes and opinions of the students. We conclude with observations, advice and suggested improvements.

We describe the experiences of three University projects that use a style of physical, non-computer based activity to enthuse and teach school students computer science concepts. We show that this kind of activity is effective as an outreach and teaching resource even when reused across different age/ability ranges, in lecture and workshop formats and for delivery by different people. We introduce the concept of a Reusable Outreach Object (ROO) that extends Reusable Learning Objects. and argue for a community effort in developing a repository of such objects.

School curricula contain little direct Computer Science (CS) content, and pupil surveys confirm that pupils have little idea what CS is. A range of initiatives have been introduced by universities to address this problem, and so attract more CS students. This paper presents the Computer Science Inside... project, one such initiative, the primary goals of which are to provide materials for use in secondary school classrooms, and to motivate and prepare the teachers to deliver them. The materials are principally workshops, to be conducted away from machinery and which bring out key CS concepts underpinning ubiquitous IT products such as the mobile phone or internet. All materials are available on the web, to encourage delivery widely by academics, students or teachers. Our evaluation has shown the approach to be broadly successful, and has also highlighted directions for future work.

Abstract Pointer traversals pose significant overhead to the execution of object‐oriented programs, since every access to an object's state requires a pointer dereference. Eliminating redundant pointer traversals reduces both instructions executed as well as redundant memory accesses to relieve pressure on the memory subsystem. We describe an approach to elimination of redundant access expressions that combines partial redundancy elimination (PRE) with type‐based alias analysis (TBAA). To explore the potential of this approach we have implemented an optimization framework for Java class files incorporating TBAA‐based PRE over pointer access expressions. The framework is implemented as a class‐file‐to‐class‐file transformer; optimized classes can then be run in any standard Java execution environment. Our experiments demonstrate improvements in the execution of optimized code for several Java benchmarks running in diverse execution environments: the standard interpreted JDK virtual machine, a virtual machine using ‘just‐in‐time’ compilation, and native binaries compiled off‐line (‘way‐ahead‐of‐time’). Overall, however, our experience is of mixed success with the optimizations, mainly because of the isolation between our optimizer and the underlying execution environments which prevents more effective cooperation between them. We isolate the impact of access path PRE using TBAA, and demonstrate that Java's requirement of precise exceptions can noticeably impact code‐motion optimizations like PRE. Copyright © 2001 John Wiley & Sons, Ltd.

We demonstrate the use of a hyper-programming system in building persistent applications. This allows program representations to contain type-safe links to persistent objects embedded directly within the source code. The benefits include improved efficiency and potential for static program checking, reduced programming effort and the ability to display meaningful source level representations for first class procedure values. Hyper-programming represents a completely new style of programming which is only possible in a persistent programming system.

Persistent programming systems are designed to provide technology for the construction and maintenance of large, long-lived object-based application systems. Many successful prototypes have been constructed and a large body of application building experience is emerging. Three common attributes of persistent systems are persistent linkage, strong typing, and the referential integrity of data. Persistent linkage allows persistent objects to be included in the binding process. Strong typing guarantees that objects are only manipulated in a manner consistent with their type system descriptions. Referential integrity ensures that once a link (reference) to an object is established, its identity is unique and it persists over time. As a consequence no object can be deleted while another refers to it. Here we examine some of the advantages of providing software engineering environments within a persistent object system with strong typing and referential integrity. It is shown how the integration of system specifications, programs, configuration management tools and documentation all within a single persistent environment leads to powerful new techniques. This new power is achieved by sharing structured persistent data across the hitherto enclosing boundaries of system components.