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Showing 1 to 15 of 22 results Save | Export
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Ünal Çakiroglu; Seval Bilgi – Interactive Learning Environments, 2024
The aim of this explanatory study is to identify the causes of intrinsic cognitive load in programming process. For this purpose, a method based on two dimensions; programming knowledge types (syntactic, semantic, and strategic) and programming constructs was proposed. The proposed method was tested with high school students enrolled in Computer…
Descriptors: Cognitive Processes, Difficulty Level, Programming, Interaction
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Yu Lei; Xin Fu; Jingjie Zhao; Baolin Yi – Education and Information Technologies, 2025
Grouping students according to their abilities and promoting deeper interaction and moderation are key issues in improving computational thinking in collaborative programming. However, the distribution characteristics and evolving pathways of computational thinking in different groups have not been deeply explored. During the course of a…
Descriptors: Ability Grouping, Computation, Programming, Cooperative Learning
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Eunsung Park; Jongpil Cheon – Journal of Educational Computing Research, 2025
Debugging is essential for identifying and rectifying errors in programming, yet time constraints and students' trivialization of errors often hinder progress. This study examines differences in debugging challenges and strategies among students with varying computational thinking (CT) competencies using weekly coding journals from an online…
Descriptors: Undergraduate Students, Programming, Computer Software, Troubleshooting
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Marius Banut; Ion Albulescu – Journal on Efficiency and Responsibility in Education and Science, 2024
In pedagogical language, "scaffolding" is frequently used to replace the expression "support in learning". In didactic terms, the practice in the classroom shows that various types of support, such as the teacher, colleagues, and technologies, contribute to more efficient learning. In terms of technologies, the present study…
Descriptors: Scaffolding (Teaching Technique), Music Education, Foreign Countries, Urban Environment
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Yoonhee Shin; Jaewon Jung; Seohyun Choi; Bokmoon Jung – Education and Information Technologies, 2025
This study investigates the effects of metacognitive and cognitive strategies for computational thinking (CT) on managing cognitive load and enhancing problem-solving skills in collaborative programming. Four different scaffolding conditions were provided to help learners optimize cognitive load and improve their problem-solving abilities. A total…
Descriptors: Scaffolding (Teaching Technique), Mental Computation, Cognitive Processes, Difficulty Level
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Stephanie Yang; Miles Baird; Eleanor O’Rourke; Karen Brennan; Bertrand Schneider – ACM Transactions on Computing Education, 2024
Students learning computer science frequently struggle with debugging errors in their code. These struggles can have significant downstream effects--negatively influencing how students assess their programming ability and contributing to their decision to drop out of CS courses. However, debugging instruction is often an overlooked topic, and…
Descriptors: Computer Science Education, Troubleshooting, Programming, Teaching Methods
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Selena Steinberg; Melissa Gresalfi; Lauren Vogelstein; Corey Brady – Journal of Research on Technology in Education, 2024
This paper considers how a curricular design that integrated computer programming and creative movement shaped students' engagement with computing. We draw on data from a camp for middle schoolers, focusing on an activity in which students used the programming environment NetLogo to re-represent their physical choreography. We analyze the extent…
Descriptors: Dance, Programming, Computation, Computer Simulation
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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
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Yang Shi; Robin Schmucker; Keith Tran; John Bacher; Kenneth Koedinger; Thomas Price; Min Chi; Tiffany Barnes – Journal of Educational Data Mining, 2024
Understanding students' learning of knowledge components (KCs) is an important educational data mining task and enables many educational applications. However, in the domain of computing education, where program exercises require students to practice many KCs simultaneously, it is a challenge to attribute their errors to specific KCs and,…
Descriptors: Programming Languages, Undergraduate Students, Learning Processes, Teaching Models
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Wen-shuang Fu; Jia-hua Zhang; Di Zhang; Tian-tian Li; Min Lan; Na-na Liu – Journal of Educational Computing Research, 2025
Cognitive ability is closely associated with the acquisition of programming skills, and enhancing learners' cognitive ability is a crucial factor in improving the efficacy of programming education. Adaptive feedback strategies can provide learners with personalized support based on their learning context, which helps to stimulate their interest…
Descriptors: Feedback (Response), Cognitive Ability, Programming, Computer Science Education
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Sanna Forsström; Melissa Bond – International Journal of Computer Science Education in Schools, 2024
Despite the widespread adoption of computational thinking (CT) across educational levels, challenges persist in its assessment due to diverse definitions, frameworks, and practical applications in classroom settings. This meta-synthesis investigates the assessment of computational thinking (CT) in primary and secondary education, synthesising…
Descriptors: Computation, Thinking Skills, Elementary Secondary Education, Barriers
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Xin Gong; Weiqi Xu; Shufan Yu; Jingjing Ma; Ailing Qiao – British Journal of Educational Technology, 2025
Tangible programming tools have become a mainstream teaching aid in gamification programming learning (GPL) due to their interactivity and ability to enhance novice learners' computational thinking and spatial reasoning skills. However, comparing the relative efficacy of different programming tools that simultaneously support these skills was not…
Descriptors: Computation, Thinking Skills, Spatial Ability, Gamification
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Hugo G. Lapierre; Patrick Charland; Pierre-Majorique Léger – Computer Science Education, 2024
Background and Context: Current programming learning research often compares novices and experienced programmers, leaving early learning stages and emotional and cognitive states under-explored. Objective: Our study investigates relationships between cognitive and emotional states and learning performance in early stage programming learners with…
Descriptors: Programming, Computer Science Education, Psychological Patterns, Cognitive Processes
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Minji Jeon; Kyungbin Kwon – TechTrends: Linking Research and Practice to Improve Learning, 2024
This study investigated the computational thinking (CT) practices of eight pre-service teachers through their Scratch and Python programs. Conducted within an undergraduate-level computer science education course, students learned CT concepts via parallel instruction in block-based programming (Scratch) and text-based programming (Python). The…
Descriptors: Preservice Teacher Education, Preservice Teachers, Computation, Cognitive Processes
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Hao-Yue Jin; Maria Cutumisu – Education and Information Technologies, 2024
Computational thinking (CT) is considered to be a critical problem-solving toolkit in the development of every student in the digital twenty-first century. Thus, it is believed that the integration of deeper learning in CT education is an approach to help students transfer their CT skills beyond the classroom. Few literature reviews have mapped…
Descriptors: Computation, Thinking Skills, Problem Solving, Artificial Intelligence
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