Assessing How Pre-requisite Skills Affect Learning of Advanced Concepts

Students often struggle with advanced computing courses, and comparatively few studies have looked into the reasons for this. It seems that learners do not master the most basic concepts, or forget them between courses. If so, remedial practice could improve learning, but instructors rightly will not use scarce time for this without strong evidence. Based on personal observation, program tracing seems to be an important pre-requisite skill, but there is yet little research that provides evidence for this observation. To investigate this, our group will create theory-based assessments on how tracing knowledge affects learning of advanced topics, such as data structures, algorithms, and concurrency. This working group will identify relevant concepts in advanced courses, then conceptually analyze their pre-requisites and where an imagined student with some tracing difficulties would encounter barriers. The group will use this theory to create instructor-usable assessments for advanced topics that also identify issues caused by poor pre-requisite knowledge. These assessments may then be used at the start and end of advanced courses to evaluate to what extent students\u2019 difficulties with the advanced course originate from poor pre-requisite knowledge

Modeling Women's Elective Choices in Computing

Evidence-based strategies suggest ways to reduce the gender gap in computing. For example, elective classes are valuable in enabling students to choose in which directions to expand their computing knowledge in areas aligned with their interests. The availability of electives of interest may also make computing programs of study more meaningful to women. However, research on which elective computing topics are more appealing to women is often class or institution specific. In this study, we investigate differences in enrollment within undergraduate-level elective classes in computing to study differences between women and men. The study combined data from nine institutions from both Western Europe and North America and included 272 different classes with 49,710 student enrollments. These classes were encoded using ACM curriculum guidelines and combined with the enrollment data to build a hierarchical statistical model of factors affecting student choice. Our model shows which elective topics are less popular with all students (including fundamentals of programming languages and parallel and distributed computing), and which elective topics are more popular with women students (including mathematical and statistical foundations, human computer interaction and society, ethics, and professionalism). Understanding which classes appeal to different students can help departments gain insight of student choices and develop programs accordingly. Additionally, these choices can also help departments explore whether some students are less likely to choose certain classes than others, indicating potential barriers to participation in computing

From a National Meeting to an International Conference: A Scientometric Case Study of a Finnish Computing Education Conference

Computerisation and digitalisation are shaping the world in fundamental and unpredictable ways, which highlights the importance of computing education research (CER). As part of understanding the roots of CER, it is crucial to investigate the evolution of CER as a research discipline. In this paper we present a case study of a Finnish CER conference called Koli Calling, which was launched in 2001, and which has become a central publication venue of CER. We use data from 2001 to 2020, and investigate the evolution of Koli Calling’s scholarly communities and zoom in on it’s publication habits and internalisation process. We explore the narrative of the development and scholarly agenda behind changes in the conference submission categories from the perspective of some of the conference chairs over the years. We then take a qualitative perspective, analysing the conference publications based on a comprehensive bibliometric analysis. The outcomes include classification of important research clusters of authors in the community of conference contributors. Interestingly, we find traces of important events in the historical development of CER. In particular, we find clusters emerging from specific research capacity building initiatives and we can trace how these connect research spanning the world CER community from Finland to Sweden and then further to the USA, Australia and New Zealand. This paper makes a strategic contribution to the evolution of CER as a research discipline, from the perspective of one central event and publication venue, providing a broad perspective on the role of the conference in connecting research clusters and establishing an international research community. This work contributes insights to researchers in one specific CER community and how they shape the future of computing education.</p

Modelling competencies for computing education beyond 2020: a research based approach to defining competencies in the computing disciplines.

How might the content and outcomes of tertiary education programmes be described and analysed in order to understand how they are structured and function? To address this question we develop a framework for modelling graduate competencies linked to tertiary degree programmes in the computing disciplines. While the focus of our work is computing the framework is applicable to education more broadly. The work presented here draws upon the pioneering curricular document for information technology (IT2017), curricular competency frameworks, other related documents such as the software engineering competency model (SWECOM), the Skills Framework for the Information Age (SFIA), current research in competency models, and elicitation workshop results from recent computing conferences. The aim is to inform the ongoing Computing Curricula (CC2020) project, an endeavour supported by the Association for Computing Machinery (ACM) and the IEEE Computer Society. We develop the Competency Learning Framework (CoLeaF), providing an internationally relevant tool for describing competencies. We argue that this competency based approach is well suited for constructing learning environments and assists degree programme architects in dealing with the challenge of developing, describing and including competencies relevant to computer and IT professionals. In this paper we demonstrate how the CoLeaF competency framework can be applied in practice, and though a series of case studies demonstrate its effectiveness and analytical power as a tool for describing and comparing degree programmes in the international higher education landscape

High-school students' mastery of basic flow-control constructs through the lens of reversibility

High-school students specialising in computing fields need to develop the abstraction skills required to understand and create programs. Novices' difficulties at high-school level, ranging from mastery of the "notional machine"to recognition of a program's purpose, have not been investigated as extensively as at tertiary level. This work explores high-school students' code comprehension by asking to reason about reversing conditional and iteration constructs. A sample of 205 K11 - 13 students from different institutions were asked to engage in a set of "reversibility tasklets". For each code fragment, they need to identify if its computation is reversible and either provide the code to reverse or an example of a value that cannot be reversed. For 4 such items, after extracting the recurrent patterns in students' answers, we have carried out an analysis within the framework of the SOLO taxonomy. Overall, 74% of answers correctly identified if the code was reversible but only 42% could provide the full explanation/code. The rate of relational answers varies from 51% down to 21%, the poorest performance arising for a small array-processing loop (and although 65% of the subjects had correctly identified the loop as reversible). The instruction level did not have a strong impact on performance, indicating such tasks are suitable for K11, when the basic flow-control constructs are usually introduced. In particular, the reversibility concept could be a useful pedagogical instrument both to assess and to help develop students' program comprehension

Emergence of computing education as a research discipline

This thesis investigates the changing nature and status of computing education research (CER) over a number of years, specifically addressing the question of whether computing education can legitimately be considered a research discipline. The principal approach to addressing this question is an examination of the published literature in computing education conferences and journals. A classification system was devised for this literature, one goal of the system being to clearly identify some publications as research – once a suitable definition of research was established. When the system is applied to a corpus of publications, it becomes possible to determine the proportion of those publications that are classified as research, and thence to detect trends over time and similarities and differences between publication venues. The classification system has been applied to all of the papers over several years in a number of major computing education conferences and journals. Much of the classification was done by the author alone, and the remainder by a team that he formed in order to assess the inter-rater reliability of the classification system. This classification work led to two subsequent projects, led by Associate Professor Judy Sheard and Professor Lauri Malmi, that devised and applied further classification systems to examine the research approaches and methods used in the work reported in computing education publications. Classification of nearly 2000 publications over ranges of 3-10 years uncovers both strong similarities and distinct differences between publication venues. It also establishes clear evidence of a substantial growth in the proportion of research papers over the years in question. These findings are considered in the light of published perspectives on what constitutes a discipline of research, and lead to a confident assertion that computing education can now rightly be considered a discipline of research

Role Modeling as a Computing Educator in Higher Education: A Focus on Care, Emotions and Professional Competencies

This paper provides insights into role modeling by educators in computing that is beyond the technical, theoretical and rational perspectives which have historically been described as dominant in computing. Surveying 199 educators in higher education, we have built on frameworks of role modeling, care, emotions, and professional competencies as a lens to see different ways of engaging in computing. Our quantitative and qualitative findings show how educators model ways of caring (for oneself, other humans and living species, technology, and the planet), emotions, professional competencies and other types of role modeling. Examples of contexts within computing and reasons why an educator can(not) model these aspects bring new light to research on care and emotions being shown in computing. This work contributes to a better understanding of computing educators as potential role models, particularly in terms of displaying emotions and various types of care. Our work can support ways of developing the professional competences of computing educators and the teaching culture of computing departments. Our findings may inspire other educators to think about their own display of emotions and care, and what this transmits to their students. Thus, the work also contributes to the discussion of ways to increase diversity among students and equitable access to computing education

What Do We Think We Think We Are Doing?: Metacognition and Self-Regulation in Programming

Metacognition and self-regulation are popular areas of interest in programming education, and they have been extensively researched outside of computing. While computing education researchers should draw upon this prior work, programming education is unique enough that we should explore the extent to which prior work applies to our context. The goal of this systematic review is to support research on metacognition and self-regulation in programming education by synthesizing relevant theories, measurements, and prior work on these topics. By reviewing papers that mention metacognition or self-regulation in the context of programming, we aim to provide a benchmark of our current progress towards understanding these topics and recommendations for future research. In our results, we discuss eight common theories that are widely used outside of computing education research, half of which are commonly used in computing education research. We also highlight 11 theories on related constructs (e.g., self-efficacy) that have been used successfully to understand programming education. Towards measuring metacognition and self-regulation in learners, we discuss seven instruments and protocols that have been used and highlight their strengths and weaknesses. To benchmark the current state of research, we examined papers that primarily studied metacognition and self-regulation in programming education and synthesize the reported interventions used and results from that research. While the primary intended contribution of this paper is to support research, readers will also learn about developing and supporting metacognition and self-regulation of students in programming courses

Relation of Individual Time Management Practices and Time Management of Teams

Full research paper-Team configuration, work practices, and communication have a considerable impact on the outcomes of student software projects. This study observes 150 college students who first individually solve exercises and then carry out a class project in teams of three. All projects had the same requirements. We analyzed how students' behavior on individual pre-project exercises predict team project outcomes, investigated how students' time management practices affected other team members, and analyzed how students divided their work among peers. Our results indicate that teams consisting of only low-performing students were the most dysfunctional in terms of workload balance, whereas teams with both low-and high-performing students performed almost as well as teams consisting of only high-performing students. This suggests that teams should combine students of varying skill levels rather than allowing teams with only low performers or letting students to form teams without constraints. We also observed that individual students' poor time management practices impair their teammates' time management. This underlines the importance of encouraging good time management practices. Most teams reported that they divided tasks in a way that is beneficial for the acquisition of technical skills rather than collaboration and communication skills. Only a few teams assigned tasks so that students would have worked only on tasks they already knew and thus felt most comfortable to work with.Team configuration, work practices, and communication have a considerable impact on the outcomes of student software projects. This study observes 150 college students who first individually solve exercises and then carry out a class project in teams of three. All projects had the same requirements. We analyzed how students' behavior on individual pre-project exercises predict team project outcomes, investigated how students' time management practices affected other team members, and analyzed how students divided their work among peers. Our results indicate that teams consisting of only low-performing students were the most dysfunctional in terms of workload balance, whereas teams with both low-and high-performing students performed almost as well as teams consisting of only high-performing students. This suggests that teams should combine students of varying skill levels rather than allowing teams with only low performers or letting students to form teams without constraints. We also observed that individual students' poor time management practices impair their teammates' time management. This underlines the importance of encouraging good time management practices. Most teams reported that they divided tasks in a way that is beneficial for the acquisition of technical skills rather than collaboration and communication skills. Only a few teams assigned tasks so that students would have worked only on tasks they already knew and thus felt most comfortable to work with.Peer reviewe