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This year, an ITiCSE record of 243 papers were submitted, of which 66 were accepted, giving an acceptance rate of 27%. Of these papers, just over half had an author from the United States or Canada, while European authors were represented in about 40% of the papers. We also accepted papers with authors from Central and South America, China, Japan, Australia, and the Middle East, giving us a truly international avour of current Computer Science Education research and practice. In addition to the Paper, Poster and Panel submissions, and Tips, Techniques and Courseware presentations, we have ten Working Groups investigating these topics: the pacing of introductory CS courses; fostering program comprehension for novice programmers; exploring pass rates in computing and other STEM subjects; sustainability issues in CS; diversity in the cybersecurity eld; data science education; benchmarking K-12 CS education in schools; developing a model curriculum for cloud computing; and designing better compiler error messages. The reports from these groups will be published in a companion volume to the nal proceedings, but we look forward to the working groups presenting preliminary findings during the conference.
This is an authoritative introduction to Computing Education research written by over 50 leading researchers from academia and the industry.
This book constitutes the refereed proceedings of the 45th Annual Conference of the Southern African Computer Lecturers' Association on ICT Education, SACLA 2016, held in Cullinan, South Africa, in July 2016. The three revised full papers and 13 work-in-progress papers presented together with two invited keynote papers were carefully reviewed and selected from 30 submissions. The papers are organized in topical sections on assessment methods, instruction methods, new curricula, social skills, and various experiences.
Drawing together the most up-to-date research from experts all across the world, the second edition of Computer Science Education offers the most up-to-date coverage available on this developing subject, ideal for building confidence of new pre-service and in-service educators teaching a new discipline. It provides an international overview of key concepts, pedagogical approaches and assessment practices. Highlights of the second edition include: - New sections on machine learning and data-driven (epistemic) programming - A new focus on equity and inclusion in computer science education - Chapters updated throughout, including a revised chapter on relating ethical and societal aspects to knowledge-rich aspects of computer science education - A new set of chapters on the learning of programming, including design, pedagogy and misconceptions - A chapter on the way we use language in the computer science classroom. The book is structured to support the reader with chapter outlines, synopses and key points. Explanations of key concepts, real-life examples and reflective points keep the theory grounded in classroom practice. The book is accompanied by a companion website, including online summaries for each chapter, 3-minute video summaries by each author and an archived chapter on taxonomies and competencies from the first edition.
Data science is a new field that touches on almost every domain of our lives, and thus it is taught in a variety of environments. Accordingly, the book is suitable for teachers and lecturers in all educational frameworks: K-12, academia and industry. This book aims at closing a significant gap in the literature on the pedagogy of data science. While there are many articles and white papers dealing with the curriculum of data science (i.e., what to teach?), the pedagogical aspect of the field (i.e., how to teach?) is almost neglected. At the same time, the importance of the pedagogical aspects of data science increases as more and more programs are currently open to a variety of people. This book provides a variety of pedagogical discussions and specific teaching methods and frameworks, as well as includes exercises, and guidelines related to many data science concepts (e.g., data thinking and the data science workflow), main machine learning algorithms and concepts (e.g., KNN, SVM, Neural Networks, performance metrics, confusion matrix, and biases) and data science professional topics (e.g., ethics, skills and research approach). Professor Orit Hazzan is a faculty member at the Technion’s Department of Education in Science and Technology since October 2000. Her research focuses on computer science, software engineering and data science education. Within this framework, she studies the cognitive and social processes on the individual, the team and the organization levels, in all kinds of organizations. Dr. Koby Mike is a Ph.D. graduate from the Technion's Department of Education in Science and Technology under the supervision of Professor Orit Hazzan. He continued his post-doc research on data science education at the Bar-Ilan University, and obtained a B.Sc. and an M.Sc. in Electrical Engineering from Tel Aviv University.
Open-source electronics are becoming very popular, and are integrated with our daily educational and developmental activities. At present, the use open-source electronics for teaching science, technology, engineering, and mathematics (STEM) has become a global trend. Off-the-shelf embedded electronics such as Arduino- and Raspberry-compatible modules have been widely used for various applications, from do-it-yourself (DIY) to industrial projects. In addition to the growth of open-source software platforms, open-source electronics play an important role in narrowing the gap between prototyping and product development. Indeed, the technological and social impacts of open-source electronics in teaching, research, and innovation have been widely recognized.
This book presents a collection of meta-studies, reviews, and scientometric analyses that together reveal a fresh picture about the past, present, and future of computing education research (CER) as a field of science. The book begins with three chapters that discuss and summarise meta-research about the foundations of CER, its disciplinary identity, and use of research methodologies and theories. Based on this, the book proceeds with several scientometric analyses, which explore authors and their collaboration networks, dissemination practices, international collaboration, and shifts in research focus over the years. Analyses of dissemination are deepened in two chapters that focus on some of the most influential publication venues of CER. The book also contains a series of country-, or region-level analyses, including chapters that focus on the evolution of CER in the Baltic Region, Finland, Australasia, Israel, and in the UK & Ireland. Two chapters present case studies of influential CER initiatives in Sweden and Namibia. This book also includes chapters that focus on CER conducted at school level, and cover crucially important issues such as technology ethics, algorithmic bias, and their implications for CER.In all, this book contributes to building an understanding of the past, present and future of CER. This book also contributes new practical guidelines, highlights topical areas of research, shows who to connect with, where to publish, and gives ideas of innovative research niches. The book takes a unique methodological approach by presenting a combination of meta-studies, scientometric analyses of publication metadata, and large-scale studies about the evolution of CER in different geographical regions. This book is intended for educational practitioners, researchers, students, and anyone interested in CER. This book was written in collaboration with some of the leading experts of the field.
This Handbook describes the extent and shape of computing education research today. Over fifty leading researchers from academia and industry (including Google and Microsoft) have contributed chapters that together define and expand the evidence base. The foundational chapters set the field in context, articulate expertise from key disciplines, and form a practical guide for new researchers. They address what can be learned empirically, methodologically and theoretically from each area. The topic chapters explore issues that are of current interest, why they matter, and what is already known. They include discussion of motivational context, implications for practice, and open questions which might suggest future research. The authors provide an authoritative introduction to the field which is essential reading for policy makers, as well as both new and established researchers.