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Showing 1 to 15 of 79 results Save | Export
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Olgun Sadik; Anne Todd Ottenbreit-Leftwich – Computer Science Education, 2024
Background and Context: Based on issues arising around how to best prepare CS teachers and the constantly changing nature of the CS education content, curriculum, and instructional methods, it is crucial to examine the needs of secondary CS teachers. Objective: The primary purpose of this study was to identify secondary computer science (CS)…
Descriptors: Secondary School Teachers, Computer Science Education, Barriers, Needs
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Nijenhuis-Voogt, Jacqueline; Bayram-Jacobs, Durdane; Meijer, Paulien C.; Barendsen, Erik – Computer Science Education, 2023
Background and Context: Computing education is expanding, while the teaching of algorithms is less well studied. Objective: The aim of this study was to examine teachers' pedagogical content knowledge (PCK) for teaching algorithms. Method: We conducted semi-structured interviews with seven computer science (CS) teachers in upper secondary…
Descriptors: Algorithms, Secondary School Teachers, Pedagogical Content Knowledge, Computer Science Education
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Schulz, Sandra; Berndt, Sarah; Hawlitschek, Anja – Computer Science Education, 2023
Background and Context: Collaborative and cooperative learning is important to prepare students for their future work and to increase their learning performance in university courses. Several studies have shown promising results regarding team activities, such as pair programming. However, there is little information on how teamwork is currently…
Descriptors: Cooperative Learning, Computer Science Education, Higher Education, Foreign Countries
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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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Oscar Karnalim; Simon; William Chivers – Computer Science Education, 2024
Background and Context: To educate students about programming plagiarism and collusion, we introduced an approach that automatically reports how similar a submitted program is to others. However, as most students receive similar feedback, those who engage in plagiarism and collusion might feel inadequately warned. Objective: When students are…
Descriptors: Teaching Methods, Plagiarism, Computer Science Education, Programming
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K. Ann Renninger; Ruth C. Elias; Mariko J. Kamiya; Jennifer N. Paige; Raymond A. Youngblood – Computer Science Education, 2025
Background and Context: Integrating computer science (CS) and math in classrooms is an increasingly recognized way for schools to address national CS mandates. There is a need to understand how professional development (PD) can support teachers to integrate. Objective: We examined math teachers' interest, and confidence, in math, CS, and student…
Descriptors: Faculty Development, Teacher Workshops, Computer Science Education, Mathematics Instruction
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Indriasari, Theresia Devi; Denny, Paul; Lottridge, Danielle; Luxton-Reilly, Andrew – Computer Science Education, 2023
Background and Context: Peer code review activities provide well-documented benefits to students in programming courses. Students develop relevant skills through exposure to alternative coding solutions, producing and receiving feedback, and collaboration with peers. Despite these benefits, low student motivation has been identified as one of the…
Descriptors: Peer Evaluation, Student Motivation, Cooperative Learning, Programming
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Hawlitschek, Anja; Dietrich, André; Zug, Sebastian – Computer Science Education, 2023
Background and Context: During online learning, it is essential to provide instructional guidance to support learning. However, guidance can be given in different forms and quantities. Thus, one important challenge is to provide the right amount and type of instructional guidance. Objective: The aim of the study is to investigate types of guidance…
Descriptors: Computer Science Education, Electronic Learning, Distance Education, Teaching Methods
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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
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Amanda Peel; Sugat Dabholkar; Gabriella Anton; Mike Horn; Uri Wilensky – Computer Science Education, 2024
Background and Context: To better reflect the computational nature of STEM disciplines and deepen learning of science content computational thinking (CT) should be integrated in science curricula. Teachers have a critical role in supporting effective student learning with CT integrated curricula in classroom settings. Objective: Our team worked…
Descriptors: Biology, Computer Science Education, Science Instruction, Thinking Skills
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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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Gogolla, Martin; Stevens, Perdita – Computer Science Education, 2018
Teaching modeling in computer science is complicated. Many factors contribute, and are related in diverse ways. We regard some combinations as more successful than others, but we also value diversity, and we struggle to elucidate the relationships and our value structure. Similar remarks apply to the study of biological ecosystems. This…
Descriptors: Computer Science Education, Ecology, Teaching Methods, Logical Thinking
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Searle, Kristin A.; Tofel-Grehl, Colby; Fischback, Liam; Hansen, Tyler – Computer Science Education, 2023
Background and Context: There is a need for teachers who are prepared to teach integrated CS/CT throughout the K-12 curriculum. Drawing on three vignettes of teacher instructional practice, we build on a growing body of literature around how teachers integrate CS/CT into their classrooms after attending CS/CT focused professional development.…
Descriptors: Affordances, Barriers, Teaching Styles, Computer Science Education
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Mouza, Chrystalla; Sheridan, Scott; Lavigne, Nancy C.; Pollock, Lori – Computer Science Education, 2023
Background and Context: A key challenge in advancing computer science education in K-12 schools is teacher preparation and support. School-university partnerships and service-learning programs where undergraduates assist teachers represent one promising approach to supporting K-12 computer science teaching. Objectives: In this work, we examine the…
Descriptors: Undergraduate Students, Elementary Secondary Education, Computer Science Education, College School Cooperation
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Rich, Kathryn M.; Franklin, Diana; Strickland, Carla; Isaacs, Andy; Eatinger, Donna – Computer Science Education, 2022
Background and Context: We explored how learning trajectories (LTs) might be used to design variables instruction. Objective: We aimed to develop an LT for variables and use it to guide curriculum development for fourth graders working in Scratch in an integrated mathematics+CS curriculum. Method: We synthesized learning goals (LGs) and levels of…
Descriptors: Teaching Methods, Computer Science Education, Sequential Learning, Instructional Design
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