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Kather, Philipp; Duran, Rodrigo; Vahrenhold, Jan – ACM Transactions on Computing Education, 2022
Previous studies on writing and understanding programs presented evidence that programmers beyond a novice stage utilize plans or plan-like structures. Other studies on code composition showed that learners have difficulties with writing, reading, and debugging code where interacting plans are merged into a short piece of code. In this article, we…
Descriptors: Eye Movements, Coding, Algorithms, Schemata (Cognition)
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Jinbo Tan; Lei Wu; Shanshan Ma – British Journal of Educational Technology, 2024
The purpose of this study was to investigate the collaborative dialogue patterns of pair programming and their impact on programming self-efficacy and coding performance for both slow- and fast-paced students. Forty-six postgraduate students participated in the study. The students were asked to solve programming problems in pairs; those pairs'…
Descriptors: Coding, Programming, Computer Science Education, Self Efficacy
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Mik Fanguy; Jamie Costley; Matthew Courtney; Kyungmee Lee – Interactive Learning Environments, 2024
The present study (n = 357) investigates the effects of collaborative note-taking behaviors on learning performance and note quality. To conceptualize collaborative note-taking, the present study introduces the collaborative encoding-storage paradigm, where collaborative writing behaviors are viewed as types of collaborative encoding and the…
Descriptors: Foreign Countries, Graduate Students, Graduate Study, Writing Skills
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Hoffman, Heather J.; Elmi, Angelo F. – Journal of Statistics and Data Science Education, 2021
Teaching students statistical programming languages while simultaneously teaching them how to debug erroneous code is challenging. The traditional programming course focuses on error-free learning in class while students' experiences outside of class typically involve error-full learning. While error-free teaching consists of focused lectures…
Descriptors: Statistics Education, Programming Languages, Troubleshooting, Coding
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Pishtari, Gerti; Prieto, Luis P.; Rodriguez-Triana, Maria Jesus; Martinez-Maldonado, Roberto – Journal of Learning Analytics, 2022
This research was triggered by the identified need in literature for large-scale studies about the kinds of designs that teachers create for mobile learning (m-learning). These studies require analyses of large datasets of learning designs. The common approach followed by researchers when analyzing designs has been to manually classify them…
Descriptors: Scaling, Classification, Context Effect, Telecommunications
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Simon D. Weaver; G. Alex Ambrose; Rebecca J. Whelan – Journal of Chemical Education, 2022
Students completing undergraduate majors in chemistry are not typically required to undergo formal training in computer programming or coding. As a result, many chemistry students are graduating without skills in understanding, writing, or manipulating computer code. This skills gap places students at a disadvantage, considering the widespread and…
Descriptors: Coding, Undergraduate Students, Majors (Students), Chemistry
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Susan B. Wainscott; Mohamed B. Trabia; David E. James – Advances in Engineering Education, 2023
How can we engage new engineering and computer science graduate students in meaningful conversations about research and publication ethics without establishing a common understanding of the issues and expectations? Most universities offer extensive responsible conduct of research (RCR) training programs, which are usually a semester-long. Absent a…
Descriptors: Ethics, Engineering Education, Computer Science Education, Graduate Students