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Showing 226 to 240 of 2,031 results Save | Export
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Chiao Ling Huang; Lianzi Fu; Shih-Chieh Hung; Shu Ching Yang – Journal of Computer Assisted Learning, 2025
Background: Many studies have highlighted the positive effects of visual programming instruction (VPI) on students' learning experiences, programming self-efficacy and flow experience. However, there is a notable gap in the research on how these factors specifically impact programming achievement and learning intentions. Our study addresses this…
Descriptors: Attention, Self Efficacy, Visual Aids, Instructional Effectiveness
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Victor-Alexandru Padurean; Tung Phung; Nachiket Kotalwar; Michael Liut; Juho Leinonen; Paul Denny; Adish Singla – International Educational Data Mining Society, 2025
The growing need for automated and personalized feedback in programming education has led to recent interest in leveraging generative AI for feedback generation. However, current approaches tend to rely on prompt engineering techniques in which predefined prompts guide the AI to generate feedback. This can result in rigid and constrained responses…
Descriptors: Automation, Student Writing Models, Feedback (Response), Programming
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Wang, Jianlan; Zhang, Yuanlin; Jones, Arthur; Eckel, Rory; Hawkins, Joshua; Musslewhite, Darrel – Journal of Computers in Mathematics and Science Teaching, 2022
Despite the importance of computer science education and computational thinking, there have been limited examples of computer science education at K-12 classrooms that authentically represents the work of computer scientists, especially programming. One reason is the lack of a measurable definition of computational thinking and a programming…
Descriptors: Teaching Methods, Computer Science Education, Programming, Thinking Skills
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Podworny, Susanne; Hüsing, Sven; Schulte, Carsten – Statistics Education Research Journal, 2022
Data science surrounds us in contexts as diverse as climate change, air pollution, route-finding, genomics, market manipulation, and movie recommendations. To open the "data-science-black-box" for lower secondary school students, we developed a data science teaching unit focusing on the analysis of environmental data, which we embedded…
Descriptors: Statistics Education, Programming, Programming Languages, Data Analysis
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Zhang, Yingbin; Paquette, Luc; Pinto, Juan D.; Liu, Qianhui; Fan, Aysa Xuemo – Education and Information Technologies, 2023
It is widely recognized that debugging is challenging for novice programmers and, as such, computing educators and researchers have called for explicit debugging instruction. Debugging requires various knowledge and skills, and different students may show different strengths and weaknesses. An understanding of such individual differences is…
Descriptors: Undergraduate Students, Programming, Novices, Troubleshooting
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Djelil, Fahima; Sanchez, Eric – Education and Information Technologies, 2023
Game based-learning have been widely promoted to overcome the difficulties encountered by beginners to learn programming. However, there are many issues to address for the implementation of game-based learning. Indeed, game-based learning is not limited to adding game elements such as rewards to a learning situation, but it rather consists of…
Descriptors: Game Based Learning, Educational Games, Design, Programming
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Cheers, Hayden; Lin, Yuqing; Yan, Weigen – Informatics in Education, 2023
Source code plagiarism is a common occurrence in undergraduate computer science education. Many source code plagiarism detection tools have been proposed to address this problem. However, most of these tools only measure the similarity between assignment submissions, and do not actually identify which are suspicious of plagiarism. This work…
Descriptors: Plagiarism, Assignments, Computer Software, Computer Science Education
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York, Julie – Childhood Education, 2023
The STEM acronym (science, technology, engineering, and mathematics) has evolved into STEAM, to reflect the increasingly held view that art and creativity are essential components of math/science teaching and learning. Sadly, too few students are choosing to take computer science classes. When presented as a technical science, many students,…
Descriptors: Programming, STEM Education, Art Education, Early Childhood Education
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Rõõm, Marili; Luik, Piret; Lepp, Marina – Education and Information Technologies, 2023
Learners' success in Massive Open Online Courses (MOOCs) and the factors influencing it have previously been examined mainly upon completion of the course. This approach does not reveal whether learners are fulfilling their initial intentions regarding MOOCs and which factors affect it and thus the individual success of the learners. This…
Descriptors: Academic Achievement, MOOCs, Programming, Computer Science Education
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Sbaraglia, Marco; Lodi, Michael; Martini, Simone – Informatics in Education, 2021
Introductory programming courses (CS1) are difficult for novices. Inspired by "Problem solving followed by instruction" and "Productive Failure" approaches, we define an original "necessity-driven" learning design. Students are put in an apparently well-known situation, but this time they miss an essential ingredient…
Descriptors: Programming, Introductory Courses, Computer Science Education, Programming Languages
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Goudouris, Cesar; de Abreu Mol, Antônio Carlos; Legey, Ana Paula; de Carvalho, Paulo Victor Rodrigues; Freire, Joana Loureiro; Martins, Bianca Maria Rego; Jatobá, Alessandro – Education and Information Technologies, 2020
Teaching computer programming to children and adolescents has become popular in recent years. This popularity has resulted in increased research into techniques for teaching introductory programming using visual languages, especially block-based languages. This study aims to explore new possibilities for teaching programming by adopting a hybrid…
Descriptors: High School Students, Computer Science Education, Programming, Teaching Methods
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Muhammed Murat Gümüs; Volkan Kukul; Özgen Korkmaz – Informatics in Education, 2024
This study aims to explain the relationships between secondary school students' digital literacy, computer programming self-efficacy and computational thinking self-efficacy. The study group consists of 204 secondary school students. A relational survey model was used in the research method and three different data collection tools were used to…
Descriptors: Correlation, Middle School Students, Thinking Skills, Digital Literacy
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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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Valerie Critten; Hannah Hagon; Melike Aslan Unlu – International Journal of Computer Science Education in Schools, 2024
In light of current developments, there is an increasing effort to integrate computing-oriented activities into the education of children as young as two years old. Although the computing strand is not officially addressed in the Early Years Foundation Stage Statutory Framework (DfES, 2024), a small number of early years teachers in England…
Descriptors: Foreign Countries, Early Childhood Education, Computation, Problem Solving
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Loïs Vanhée; Karin Danielsson; Lena Enqvist; Kalle Grill; Melania Borit – European Journal of Education, 2024
Whereas hackathons are widespread within and outside academia and have been argued to be a valid pedagogical method for teaching interdisciplinarity, no detailed frameworks or methods are available for conceptualizing and organizing educational hackathons, i.e., hackathons dedicated to best achieving pedagogic objectives. This paper is dedicated…
Descriptors: Interdisciplinary Approach, Learning Activities, Programming, Computer Security
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