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Gayithri Jayathirtha; Deborah Fields; Yasmin Kafai – Computer Science Education, 2024
Background and Context: Debugging is a challenging yet understudied practice within recent collaborative K-12 physical computing contexts. We examined think-aloud interviews and reflections of seven high school student pairs who debugged researcher-designed buggy electronic textile projects. Objective: We asked: (1) What strategies did student…
Descriptors: High School Students, Problem Solving, Cooperation, Small Group Instruction
Renske Weeda; Sjaak Smetsers; Erik Barendsen – Computer Science Education, 2024
Background and Context: Multiple studies report that experienced instructors lack consensus on the difficulty of programming tasks for novices. However, adequately gauging task difficulty is needed for alignment: to select and structure tasks in order to assess what students can and cannot do. Objective: The aim of this study was to examine…
Descriptors: Novices, Coding, Programming, Computer Science Education
Pelánek, Radek; Effenberger, Tomáš – Computer Science Education, 2022
Background and Context: Block-based programming is a popular approach to teaching introductory programming. Block-based programming often works in the context of microworlds, where students solve specific puzzles. It is used, for example, within the Hour of Code event, which targets millions of students. Objective: To identify design guidelines…
Descriptors: Programming, Computer Science Education, Puzzles, Problem Solving
Poole, Frederick J.; Clarke-Midura, Jody; Rasmussen, Melissa; Shehzad, Umar; Lee, Victor R. – Computer Science Education, 2022
There is a growing perception that computational thinking can be developed in unplugged environments. A recent trend among these unplugged approaches is the use of tabletop games. While there are many commercial tabletop games on the market that are promoted as teaching computer science and/or computational skills, little is known about how these…
Descriptors: Teaching Methods, Games, Computation, Thinking Skills
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
Akkaya, Ali; Akpinar, Yavuz – Computer Science Education, 2022
Background and Context: Though still a nascent area of research, serious games have been presented as means of engaging students in computer programming and computational thinking due to their immersive and interactive nature. Existing research is limited in its ability to provide systems based on sound instructional design models, and only a few…
Descriptors: Experiential Learning, Educational Games, Instructional Design, Programming
Kale, Ugur; Yuan, Jiangmei; Roy, Abhik – Computer Science Education, 2023
Background and Context: Various coding initiatives and materials exist such as those on Code.org site to promote students' computational thinking (CT). However, little is known as to: (a) whether such materials, in fact, promote CT and (b) how CT skills are related to each other. Objective: As a preliminary step to identify CT skills addressed in…
Descriptors: Thinking Skills, Computer Science Education, Programming, Problem Solving
Espinal, Alejandro; Vieira, Camilo; Guerrero-Bequis, Valeria – Computer Science Education, 2023
Background and context: Transfer is a process where students apply their learning to different contexts. This process includes using their knowledge to solve problems with similar complexity, and in new contexts. In the context of programming, transfer also includes being able to understand and use different programming languages. Objective: This…
Descriptors: Block Scheduling, Computer Science Education, Programming Languages, Coding
Finke, Sabrina; Kemény, Ferenc; Sommer, Markus; Krnjic, Vesna; Arendasy, Martin; Slany, Wolfgang; Landerl, Karin – Computer Science Education, 2022
Background: Key to optimizing Computational Thinking (CT) instruction is a precise understanding of the underlying cognitive skills. Román-González et al. (2017) reported unique contributions of spatial abilities and reasoning, whereas arithmetic was not significantly related to CT. Disentangling the influence of spatial and numerical skills on CT…
Descriptors: Spatial Ability, Cognitive Ability, Abstract Reasoning, Arithmetic

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