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ACM Transactions on Computing Education

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Perceptual Comparison of Source-Code Plagiarism within Students from UK, China, and South Cyprus Higher Education Institutions

Mon, 05/22/2017 - 20:00
Georgina Cosma, Mike Joy, Jane Sinclair, Margarita Andreou, Dongyong Zhang, Beverley Cook, Russell Boyatt

Perspectives of students on what constitutes source-code plagiarism may differ based on their educational background. Surveys have been conducted with home students undertaking computing and joint computing subject degrees at higher education institutions throughout the UK, China, and South Cyprus, and a total of 984 responses have been statistically analysed to determine the common areas of understanding and misunderstanding among students on various topics related to source-code plagiarism. The study identifies those topics which are well understood, and those topics which are not properly understood across the different groups of students, and is the first study which specifically discusses Cypriot student perceptions on source-code plagiarism.

Teaching Programming in Secondary Education Through Embodied Computing Platforms: Robotics and Wearables

Mon, 05/22/2017 - 20:00
Alexandros Merkouris, Konstantinos Chorianopoulos, Achilles Kameas

Pedagogy has emphasized that physical representations and tangible interactive objects benefit learning especially for young students. There are many tangible hardware platforms for introducing computer programming to children, but there is limited comparative evaluation of them in the context of a formal classroom. In this work, we explore the benefits of learning to code for tangible computers, such as robots and wearable computers, in comparison to programming for the desktop computer. For this purpose, 36 students participated in a within-groups study that involved three types of target computer platform tangibility: (1) desktop, (2) wearable, and (3) robotic. We employed similar blocks-based visual programming environments, and we measured emotional engagement, attitudes, and computer programming performance.

Assessing Student Behavior in Computer Science Education with an fsQCA Approach: The Role of Gains and Barriers

Mon, 05/22/2017 - 20:00
Ilias O. Pappas, Michail N. Giannakos, Letizia Jaccheri, Demetrios G. Sampson

This study uses complexity theory to understand the causal patterns of factors that stimulate students’ intention to continue studies in computer science (CS). To this end, it identifies gains and barriers as essential factors in CS education, including motivation and learning performance, and proposes a conceptual model along with research propositions. To test its propositions, the study employs fuzzy-set qualitative comparative analysis on a data sample from 344 students. Findings indicate eight configurations of cognitive and noncognitive gains, barriers, motivation for studies, and learning performance that explain high intention to continue studies in CS.

Seeing Myself through Someone Else's Eyes: The Value of In-Classroom Coaching for Computer Science Teaching and Learning

Tue, 05/02/2017 - 20:00
Jane Margolis, Jean Ryoo, Joanna Goode

This article describes the impact of in-classroom coaching for computer science (CS) educators. Coaching is a way to support teachers in their classroom while teachers master new curricula or educational approaches and is not evaluative in purpose. Using qualitative methods to analyze computer science classroom observations, teacher surveys, teacher interviews, coaching logs, and coach interviews, this research answers the following question: How does in-classroom coaching support inquiry and equity-based teaching practices? This study of Exploring Computer Science classrooms illustrates the importance of having in-classroom coaches who can collaborate and reflect with teachers about current practices and who can help support new inquiry and equity-based instructional skills.

Novice Java Programming Mistakes: Large-Scale Data vs. Educator Beliefs

Tue, 05/02/2017 - 20:00
Neil C. C. Brown, Amjad Altadmri

Teaching is the process of conveying knowledge and skills to learners. It involves preventing misunderstandings or correcting misconceptions that learners have acquired. Thus, effective teaching relies on solid knowledge of the discipline, but also a good grasp of where learners are likely to trip up or misunderstand. In programming, there is much opportunity for misunderstanding, and the penalties are harsh: failing to produce the correct syntax for a program, for example, can completely prevent any progress in learning how to program. Because programming is inherently computer-based, we have an opportunity to automatically observe programming behaviour -- more closely even than an educator in the room at the time.