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Meghan M. Parkinson; Seppe Hermans; David Gijbels; Daniel L. Dinsmore – Computer Science Education, 2024
Background and Context: More data are needed about how young learners identify and fix errors while programming in pairs. Objective: The study will identify discernible patterns in the intersection between debugging processes and the type of regulation used during debugging while children engage in coding to drive further theory and model…
Descriptors: Computer Science Education, Troubleshooting, Cooperative Learning, Coding
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Zachary M. Savelson; Kasia Muldner – Computer Science Education, 2024
Background and Context: Productive failure (PF) is a learning paradigm that flips the order of instruction: students work on a problem, then receive a lesson. PF increases learning, but less is known about student emotions and collaboration during PF, particularly in a computer science context. Objective: To provide insight on students' emotions…
Descriptors: Student Attitudes, Psychological Patterns, Fear, Failure
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von Hausswolff, Kristina – Computer Science Education, 2022
Background and Context: Research in programming education seems to show that hands-on writing at the keyboard is beneficial for learning, but we lack an explanation of why that is and an underlying theory to anchor that explanation. Objective: The first objective is to lay out a theoretical foundation for understanding the learning situation when…
Descriptors: Programming, Computer Science Education, Novices, Student Experience
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Coto, Mayela; Mora, Sonia; Grass, Beatriz; Murillo-Morera, Juan – Computer Science Education, 2022
Background and context: Emotions are ubiquitous in academic settings and affect learning strategies, motivation to persevere, and academic outcomes, however they have not figured prominently in research on learning to program at the university level. Objective: To summarize the current knowledge available on the effect of emotions on students…
Descriptors: Programming, Computer Science Education, Psychological Patterns, Emotional Response
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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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Ben-David Kolikant, Yifat; ma'ayan, Ze'ev – Computer Science Education, 2018
Higher-education students now have more alternatives for searching for information than previous generations had. The Internet is a vast ocean of information sources, albeit with diverse reliability and quality. In Web 2.0 platforms, any participant can be a content creator. This reality is challenging for both the instructors and the students. We…
Descriptors: Computer Science Education, Higher Education, Internet, Web 2.0 Technologies