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Shindler, Michael; Pinpin, Natalia; Markovic, Mia; Reiber, Frederick; Kim, Jee Hoon; Carlos, Giles Pierre Nunez; Dogucu, Mine; Hong, Mark; Luu, Michael; Anderson, Brian; Cote, Aaron; Ferland, Matthew; Jain, Palak; LaBonte, Tyler; Mathur, Leena; Moreno, Ryan; Sakuma, Ryan – Computer Science Education, 2022
Background and Context: We replicated and expanded on previous work about how well students learn dynamic programming, a difficult topic for students in algorithms class. Their study interviewed a number of students at one university in a single term. We recruited a larger sample size of students, over several terms, in both large public and…
Descriptors: Misconceptions, Programming, Computer Science Education, Replication (Evaluation)
Fegely, Alex; Tang, Hengtao – Educational Technology Research and Development, 2022
The purpose of this convergent mixed-methods study was to evaluate the effect of educational robotics on pre-service teachers' programming comprehension and motivation. Computer science is increasingly being integrated into K-8 curricula. However, a shortage of teachers trained to teach basic computer science concepts remains unresolved. This…
Descriptors: Programming, Robotics, Preservice Teachers, Comprehension
Carina Büscher – International Journal of Science and Mathematics Education, 2025
Computational thinking (CT) is becoming increasingly important as a learning content. Subject-integrated approaches aim to develop CT within other subjects like mathematics. The question is how exactly CT can be integrated and learned in mathematics classrooms. In a case study involving 12 sixth-grade learners, CT activities were explored that…
Descriptors: Mathematics Instruction, Thinking Skills, Teaching Methods, Computer Science Education
Meina Zhu; Min Young Doo; Sara Masoud; Yaoxian Huang – Education and Information Technologies, 2025
This study examines the influences of learners' motivation, self-monitoring, and self-management on learning satisfaction in online learning environments. The participants were 185 undergraduates and 99 graduate students majoring in computer science and engineering. The participants' motivation, self-monitoring, self-management, and learning…
Descriptors: Student Satisfaction, Differences, Undergraduate Students, Graduate Students
Yoonhee Shin; Jaewon Jung; Hyun Ji Lee – Metacognition and Learning, 2024
This study investigated the effects of concept-oriented faded in worked-out examples (WOE) and metacognitive scaffolding on learners' transfer performance and motivation in programming education. Two types of faded in WOE and metacognitive scaffolding were provided. A total of 140 participants were randomly assigned into one of four groups, with…
Descriptors: Metacognition, Concept Formation, Scaffolding (Teaching Technique), Learning Processes
Xiaojing Duan; Bo Pei; G. Alex Ambrose; Arnon Hershkovitz; Ying Cheng; Chaoli Wang – Education and Information Technologies, 2024
Providing educators with understandable, actionable, and trustworthy insights drawn from large-scope heterogeneous learning data is of paramount importance in achieving the full potential of artificial intelligence (AI) in educational settings. Explainable AI (XAI)--contrary to the traditional "black-box" approach--helps fulfilling this…
Descriptors: Academic Achievement, Artificial Intelligence, Prediction, Models
David P. Bunde; John F. Dooley – PRIMUS, 2024
We present a detailed description of a Cryptography and Computer Security course that has been offered at Knox College for the last 15 years. While the course is roughly divided into two sections, Cryptology and Computer Security, our emphasis here is on the Cryptology section. The course puts the cryptologic material into its historical context…
Descriptors: Technology, Coding, Computer Security, Mathematics Education
Sigal Levy; Yelena Stukalin; Nili Guttmann-Beck – Teaching Statistics: An International Journal for Teachers, 2024
Probability theory has extensive applications across various domains, such as statistics, computer science, and finance. In probability education, students are introduced to fundamental principles which may include mathematical topics such as combinatorics and symmetric sample spaces. Students pursuing degrees in computer science possess a robust…
Descriptors: Programming, Probability, Mathematics Skills, Computer Science Education
David S. Bowers; Mihaela Sabin – Education and Information Technologies, 2024
The skills and competencies of IT professionals are often described using employer-led skills frameworks. They express competencies as technical knowledge and skills combined with a range of personal qualities. Employers have indicated the importance of developing such qualities for new graduates. In response, recent ACM/IEEE curricular…
Descriptors: Information Technology, Bachelors Degrees, Computer Science Education, Career Readiness
Sonia Lorente; Mónica Arnal-Palacián; Maximiliano Paredes-Velasco – European Journal of Psychology of Education, 2024
The European Higher Education Area (EHEA) proposes to enhance active learning and student protagonism in order to improve academic performance. In this sense, different methodologies are emerging to create scenarios for self-regulation of their learning. In this study the cooperative, collaborative and interdisciplinary learning methodologies were…
Descriptors: Cooperative Learning, Interdisciplinary Approach, Computer Software, Universities
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
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
Chen Sun; Stephanie Yang; Betsy Becker – Journal of Educational Computing Research, 2024
Computational thinking (CT), an essential 21st century skill, incorporates key computer science concepts such as abstraction, algorithms, and debugging. Debugging is particularly underrepresented in the CT training literature. This multi-level meta-analysis focused on debugging as a core CT skill, and investigated the effects of various debugging…
Descriptors: Troubleshooting, Computation, Thinking Skills, Intervention
Mehmet Ceylan; Durmus Aslan – Education and Information Technologies, 2024
This study was conducted to investigate the effects of learning trajectories-based coding (LTs) and LTs-based program on preschoolers' length, area, volume, and angle measurement skills. A quasi-experimental research design was utilized with a quantitative approach. The study's participants were 47 children between the ages of 55-71 months who…
Descriptors: Learning Trajectories, Coding, Mathematics Skills, Measurement Techniques
Julia Rose Karpicz; Tomoko M. Nakajima; Justin A. Gutzwa – Journal of Women and Gender in Higher Education, 2024
In recent decades, initiatives to diversify post-secondary educational spaces have blossomed. Many of these "broadening participation" efforts are in STEM undergraduate departments that, historically and presently, predominantly serve white men. Using a raced-gendered theoretical lens, we conducted a narrative analysis of interviews with…
Descriptors: Gender Bias, Racism, Public Colleges, Computer Science Education