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Leah Bidlake; Eric Aubanel; Daniel Voyer – ACM Transactions on Computing Education, 2025
Research on mental model representations developed by programmers during parallel program comprehension is important for informing and advancing teaching methods including model-based learning and visualizations. The goals of the research presented here were to determine: how the mental models of programmers change and develop as they learn…
Descriptors: Schemata (Cognition), Programming, Computer Science Education, Coding
Muntasir Hoq; Ananya Rao; Reisha Jaishankar; Krish Piryani; Nithya Janapati; Jessica Vandenberg; Bradford Mott; Narges Norouzi; James Lester; Bita Akram – International Educational Data Mining Society, 2025
In Computer Science (CS) education, understanding factors contributing to students' programming difficulties is crucial for effective learning support. By identifying specific issues students face, educators can provide targeted assistance to help them overcome obstacles and improve learning outcomes. While identifying sources of struggle, such as…
Descriptors: Computer Science Education, Programming, Misconceptions, Error Patterns
Mehmet Basaran; Ömer Faruk Vural; Sermin Metin; Sabiha Tamur – International Journal of Early Childhood, 2025
This study investigates ChatGPT's perspectives on coding education for preschool children to provide a comprehensive understanding that is valuable for educators in early childhood education. An instrumental case study approach was employed, utilizing qualitative research design and case study methods. Data were gathered using a structured…
Descriptors: Preschool Education, Computer Science Education, Coding, Artificial Intelligence
Diana Franklin; Paul Denny; David A. Gonzalez-Maldonado; Minh Tran – Cambridge University Press & Assessment, 2025
Generative AI is a disruptive technology that has the potential to transform many aspects of how computer science is taught. Like previous innovations such as high-level programming languages and block-based programming languages, generative AI lowers the technical expertise necessary to create working programs, bringing the power of computation…
Descriptors: Artificial Intelligence, Technology Uses in Education, Computer Science Education, Expertise
Ishaya Gambo; Faith-Jane Abegunde; Omobola Gambo; Roseline Oluwaseun Ogundokun; Akinbowale Natheniel Babatunde; Cheng-Chi Lee – Education and Information Technologies, 2025
The current educational system relies heavily on manual grading, posing challenges such as delayed feedback and grading inaccuracies. Automated grading tools (AGTs) offer solutions but come with limitations. To address this, "GRAD-AI" is introduced, an advanced AGT that combines automation with teacher involvement for precise grading,…
Descriptors: Automation, Grading, Artificial Intelligence, Computer Assisted Testing
Cindy Royal – Journalism and Mass Communication Educator, 2025
Artificial intelligence (AI) has taken the forefront in discussions of the future of media and education. Although there are valid concerns, AI has the potential to be useful in learning new skills, particularly those related to computer programming. This case study depicts the ways AI was introduced to assist in teaching coding, specifically in a…
Descriptors: Artificial Intelligence, Coding, Programming, Computer Science Education
Zifeng Liu; Wanli Xing; Xinyue Jiao; Chenglu Li; Wangda Zhu – Education and Information Technologies, 2025
The ability of large language models (LLMs) to generate code has raised concerns in computer science education, as students may use tools like ChatGPT for programming assignments. While much research has focused on higher education, especially for languages like Java and Python, little attention has been given to K-12 settings, particularly for…
Descriptors: High School Students, Coding, Artificial Intelligence, Electronic Learning
W. Monty Jones; Katherine Hansen; Douglas Lusa Krug; Michael L. Schad; Nakisha Whittington; Xun Liu – Computer Science Education, 2025
Background and Context: Efforts to engage adult learners in computer science in the United States have been largely unsuccessful. While research examining the use of music for teaching computer programming with K-12 learners is emerging, little research with adult learners exists. Objective: This study evaluates the effect of computer coding…
Descriptors: Musical Composition, Computer Software, Adult Students, Student Attitudes
Dan Sun; Fan Xu – Journal of Educational Computing Research, 2025
Real-time collaborative programming (RCP), which allows multiple programmers to work concurrently on the same codebase with changes instantly visible to all participants, has garnered considerable popularity in higher education. Despite this trend, little work has rigorously examined how undergraduates engage in collaborative programming when…
Descriptors: Cooperative Learning, Programming, Computer Science Education, Undergraduate Students
Stella Xin Yin; Dion Hoe-Lian Goh; Choon Lang Quek; Zhengyuan Liu – Educational Technology & Society, 2025
With the growing popularity of computational thinking (CT) classes in K-12 schools, it is important to investigate public perceptions of these initiatives. Analyzing public discussions and opinions provides valuable insights that can inform future educational policies and reforms. In this paper, we collected questions and answers related to CT…
Descriptors: Computation, Thinking Skills, Elementary Secondary Education, Public Opinion
Mayowa Oyedoyin; Ismaila Temitayo Sanusi; Musa Adekunle Ayanwale – Computer Science Education, 2025
Background and Context: Recognizing that digital technologies can enable economic transformation in Africa, computing education has been considered a subject relevant for all within the compulsory level of education. The implementation of the subject in many schools is, however, characterized by a myriad of challenges, including pedagogical…
Descriptors: Elementary School Students, Student Attitudes, Internet, Coding
Mark Frydenberg; Anqi Xu; Jennifer Xu – Information Systems Education Journal, 2025
This study explores student perceptions of learning to code by evaluating AI-generated Python code. In an experimental exercise given to students in an introductory Python course at a business university, students wrote their own solutions to a Python program and then compared their solutions with AI-generated code. They evaluated both solutions…
Descriptors: Student Attitudes, Programming, Computer Software, Quality Assurance
Irene Govender; Reginald G. Govender; Desmond Wesley Govender – Educational Process: International Journal, 2025
Background/purpose: This research explores the use of robotics to facilitate the learning of computer programming among non-specialist pre-service teachers with no prior programming experience. With the increasing demand for 21st-century teaching competencies, it is essential to equip future educators with computational thinking (CT) skills, even…
Descriptors: Robotics, Coding, Preservice Teachers, Computer Science Education
Sümeyra Akkaya; Anil Erkan – International Journal of Contemporary Educational Research, 2025
Coding means writing down the steps to be followed in order to carry out any operation through computers, using commands step by step. In other words, it is the job of finding a solution to an existing problem by using the language that the computer understands. Thanks to coding education, students are provided with skills such as research,…
Descriptors: Stakeholders, Opinions, Coding, Computer Science Education
Jennifer Kidd; Kristie Gutierrez; Min Jung Lee; Danielle Rhemer; Pilar Pazos; Krishna Kaipa; Stacie Ringleb; Orlando Ayala – International Journal of Technology and Design Education, 2025
Due to mandates for the inclusion of engineering and computer science standards for K-6 schools nationwide, there is a need to understand how teacher educators can help develop preservice teachers' (PSTs') teaching self-efficacy in these areas. To provide experience teaching and learning engineering and coding, PSTs in an instructional technology…
Descriptors: Robotics, Coding, Computer Science Education, Engineering Education

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