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Hao, Qiang; Smith, David H., IV; Ding, Lu; Ko, Amy; Ottaway, Camille; Wilson, Jack; Arakawa, Kai H.; Turcan, Alistair; Poehlman, Timothy; Greer, Tyler – Computer Science Education, 2022
Background and Context: automated feedback for programming assignments has great potential in promoting just-in-time learning, but there has been little work investigating the design of feedback in this context. Objective: to investigate the impacts of different designs of automated feedback on student learning at a fine-grained level, and how…
Descriptors: Computer Science Education, Feedback (Response), Teaching Methods, Comparative Analysis
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Hundhausen, C. D.; Conrad, P. T.; Carter, A. S.; Adesope, O. – Computer Science Education, 2022
Background and Context: Assessing team members' indivdiual contributions to software development projects poses a key problem for computing instructors. While instructors typically rely on subjective assessments, objective assessments could provide a more robust picture. To explore this possibility, In a 2020 paper, Buffardi presented a…
Descriptors: Computer Software, Computer Science Education, Correlation, Engineering Education
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Zakaria, Zarifa; Vandenberg, Jessica; Tsan, Jennifer; Boulden, Danielle Cadieux; Lynch, Collin F.; Boyer, Kristy Elizabeth; Wiebe, Eric N. – Computer Science Education, 2022
Background and Context: Researchers and practitioners have begun to incorporate collaboration in programming because of its reported instructional and professional benefits. However, younger students need guidance on how to collaborate in environments that require substantial interpersonal interaction and negotiation. Previous research indicates…
Descriptors: Feedback (Response), Intervention, Comparative Analysis, Programming
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Prado, Yenda; Jacob, Sharin; Warschauer, Mark – Computer Science Education, 2022
Background and Context: Computational Thinking (CT) is a skill all students should learn. This requires using inclusive approaches to teach CT to a wide spectrum of students. However, strategies for teaching CT to students with exceptionalities are not well studied. Objective: This study draws on lessons learned in two fourth-grade classrooms --…
Descriptors: Thinking Skills, Computer Science Education, Special Education, Teaching Methods
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McCord, Rachel; Jeldes, Isaac – Computer Science Education, 2019
Background and Context: Flipped classrooms are becoming more widely adopted across engineering higher education contexts. In degree programs where enrollment is increasing and undergraduate curricula are packed with content, pedagogies that allow more time for actively participate in classroom activities are being highly sought after to aid in…
Descriptors: Computer Software, Computer Science Education, Blended Learning, Intervention
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Sanchez, Pablo; Zorrilla, Marta; Duque, Rafael; Nieto-Reyes, Alicia – Computer Science Education, 2011
Models in Software Engineering are considered as abstract representations of software systems. Models highlight relevant details for a certain purpose, whereas irrelevant ones are hidden. Models are supposed to make system comprehension easier by reducing complexity. Therefore, models should play a key role in education, since they would ease the…
Descriptors: Computer Science Education, Computer Software, Programming, Programming Languages
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Lewis, Colleen M. – Computer Science Education, 2011
This study investigates differences between collaboration methods in two summer enrichment classes for students entering the sixth grade. In one treatment, students used pair programming. In the other treatment, students engaged in frequent collaboration, but worked on their own computer. Students in the two treatments did not differ significantly…
Descriptors: Elementary School Students, Student Attitudes, Educational Research, Tests
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Eckerdal, Anna; McCartney, Robert; Mostrom, Jan Erik; Ratcliffe, Mark; Zander, Carol – Computer Science Education, 2006
This paper examines the problem of studying and comparing student software designs. We propose semantic categorization as a way to organize widely varying data items. We describe how this was used to organize a particular multi-national, multi-institutional dataset, and present the results of this analysis: most students are unable to effectively…
Descriptors: Semantics, Computer Software, Classification, Computer System Design
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Lancaster, Thomas; Culwin, Fintan – Computer Science Education, 2004
Automated techniques for finding plagiarism in student source code submissions have been in use for over 20 years and there are many available engines and services. This paper reviews the literature on the major modern detection engines, providing a comparison of them based upon the metrics and techniques they deploy. Generally the most common and…
Descriptors: Foreign Countries, Plagiarism, College Students, Student Evaluation