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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
Ragonis, Noa; Shmallo, Ronit – Informatics in Education, 2022
Object-oriented programming distinguishes between instance attributes and methods and class attributes and methods, annotated by the "static" modifier. Novices encounter difficulty understanding the means and implications of "static" attributes and methods. The paper has two outcomes: (a) a detailed classification of aspects of…
Descriptors: Programming, Computer Science Education, Concept Formation, Thinking Skills
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
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
Mahatanankoon, Pruthikrai; Wolf, James – Information Systems Education Journal, 2021
Learning a computer programming language is typically one of the basic requirements of being an information technology (IT) major. While other studies previously investigate computer programming self-efficacy and grit, their relationships between "shallow" and "deep" learning (Miller et al., 1996) have not been thoroughly…
Descriptors: Cognitive Processes, Learning Strategies, Introductory Courses, Computer Science Education
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
Ezeamuzie, Ndudi O.; Leung, Jessica S. C.; Garcia, Raycelle C. C.; Ting, Fridolin S. T. – Journal of Computer Assisted Learning, 2022
Background: The idea of computational thinking is underpinned by the belief that anyone can learn and use the underlying concepts of computer science to solve everyday problems. However, most studies on the topic have investigated the development of computational thinking through programming activities, which are cognitively demanding. There is a…
Descriptors: Computation, Thinking Skills, Problem Solving, Cognitive Processes
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
Troussas, Christos; Krouska, Akrivi; Sgouropoulou, Cleo – IEEE Transactions on Education, 2021
Contribution: This article presents the instruction of computer programming using adaptive learning activities considering students' cognitive skills based on the learning theory of the Revised Bloom Taxonomy (RBT). To achieve this, the system converts students' knowledge level to fuzzy weights, and using rule-based decision making, delivers…
Descriptors: Undergraduate Students, Intelligent Tutoring Systems, Computer Science Education, Programming
Hao, Xiaoxin; Xu, Zhiyi; Guo, Mingyue; Hu, Yuzheng; Geng, Fengji – International Journal of STEM Education, 2023
Background: Coding has become an integral part of STEM education. However, novice learners face difficulties in processing codes within embedded structures (also termed nested structures). This study aimed to investigate the cognitive mechanism underlying the processing of embedded coding structures based on hierarchical complexity theory, which…
Descriptors: Cognitive Processes, Difficulty Level, Programming, Computer Science Education
Ma, Ning; Qian, Jinglong; Gong, Kaixin; Lu, Yao – Education and Information Technologies, 2023
Computational thinking is an important competence for learners in the twenty-first century. As an effective approach for cultivating competence in computational thinking, programming education has been extended from college to elementary school teaching. However, it is challenging to engage beginners in programming in elementary school education.…
Descriptors: Elementary School Students, Programming, Computer Science Education, Novices
Qin, Chao; Liu, Yanjia; Zhang, Hemei – Journal of Computer Assisted Learning, 2023
Background: Being easy to learn and fun, block-based programming tools are widely used to teach students introductory programming. Scratch and LEGO robots are two popular block-based programming tools. However, the objects they manipulate are completely different. Scratch manipulates graphical virtual sprites, whereas LEGO robots manipulate…
Descriptors: Foreign Countries, Undergraduate Students, Learner Engagement, Robotics
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
Rosenberg-Kima, Rinat B.; Merrill, M. David; Baylor, Amy L.; Johnson, Tristan E. – Educational Technology Research and Development, 2022
Novice programmers, who have yet to form effective mental models of the domain, often experience high cognitive load, low confidence, and high anxiety, negatively affecting learning and retention rates. These cognitive and affective limitations pose an instructional challenge. This study aimed to investigate the effectiveness of a whole-task…
Descriptors: Computer Science Education, Instructional Effectiveness, Novices, Programming
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