Pass Rates in Introductory Programming and in other STEM Disciplines

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 world-wide 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. The group found that pass rates in introductory programming courses appear to average about 75%; that there is some evidence that they sit at the low end of the range of pass rates in introductory STEM courses; and that pass rates both in introductory programming and in other introductory STEM courses appear to have remained fairly stable over the past five years. All of these findings must be regarded with some caution, for reasons that are explained in the paper. Despite the lack of evidence that pass rates are substantially lower than in other STEM courses, there is still scope to improve the pass rates of introductory programming courses, and future research should continue to investigate ways of improving student learning in introductory programming courses.Peer reviewe

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

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

Introducing Educational Technologies to Teachers: Experience Report

The dramatic rise in use of digital media has changed the way learning is taking place and has led to new ways to teach with digital technologies. In this article, we describe the experiences of teaching a course that introduces educational technologies to teachers in Macau. The course design is based on connectivism, a learning theory for the digital age that emphasizes interaction with digital media and active engagement in sharing digital artefacts. The learning outcomes are constructively aligned with learning and teaching activities and assessments. We share the insights we gained of the learning needs and the disparity in the technological skills and competencies of the students. The course design is evaluated in terms of the students\u27 learning outcomes and progress through the stages of learning with technology. We present evidence from journal writings that show metacognition, active reflection and critical evaluation, and we identify anxiety and increased confidence with digital tools, as well as concerns about group work. This article contributes to the discussion on teachers learning to teach with technologies

A glimpse into the cultural situatedness of computer science : Some insights from a pilot study

To what extent is students' understanding of computer science culturally situated? This, possibly philosophical question, has come to the surface at Uppsala University, Uppsala, Sweden, where many Chinese students study computer science together with the local students. We did an exploratory study using email interviews to see if our intuitions could be relied on. We collected data from Chinese students studying in master programs and analysed the data using a phenomenographic perspective. A complex intertwined relationship between the content of their learning (the WHAT) the ways in which they went about studying (the HOW), the aims of their studies (the WHY), and the competencies developed from the intercultural context they studied in (the WHERE) was observed. In this paper we offer some insights from the results of the pilot study and discuss how they have shaped our on-going study in the field

How do master level students in Computer Science perceive plagiarism?

Plagiarism is a serious problem in computer science.This paper reports the analyses of data about plagiarism that wasgathered from master level students in computing. We haveidentified how students perceive plagiarism, how they choose torespond when faced by a scenario involving plagiarism, and whatdrives them to take a particular stance or adopt an action. Thedata-driven analyses show complex understanding of plagiarismand a range of motives that could lead students to plagiarize. Wehave found discrepancies between how students understandplagiarism and how they argue they would act when facing adilemma involving plagiarism. The implications of theseperceptions and motives for computer science educators arediscussed. A number of questions for discussion and furtherinvestigation are raised

Illustration of paradigm pluralism in computing education research

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