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Saima Ritonummi; Valtteri Siitonen; Markus Salo; Henri Pirkkalainen – Journal of Workplace Learning, 2024
Purpose: The purpose of this study is to investigate the barriers that prevent workers in the software industry from experiencing flow in their work. Design/methodology/approach: This study was conducted by using a qualitative critical incident technique-inspired questionnaire. Findings: The findings suggest that workers in the software industry…
Descriptors: Barriers, Computer Software, Computer Science, Attention Control
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
Mengning Mu; Man Yuan – Interactive Learning Environments, 2024
The necessity for students to clarify their own cognitive structure and the amount of their knowledge mastery for self-reflection is often ignored in building the student model in the adaptive model, which makes the construction of the cognitive structure pointless. Simultaneously, knowledge forgetting causes students' knowledge level to fall…
Descriptors: Individualized Instruction, Cognitive Processes, Graphs, Cognitive Structures
Lauren Zirpoli – ProQuest LLC, 2024
This convergent parallel mixed methods study with qualitative and quantitative content analysis was conducted to analyze and describe the cognitive complexity of the publicly released Advanced Placement Computer Science Principles Exam questions compared to the language of higher-order thinking found in research literature. Hess' Cognitive Rigor…
Descriptors: Advanced Placement, Tests, Questioning Techniques, Difficulty Level
Ying-Lien Lin; Wei-Tsong Wang; Zhi-Lun Lai – Education and Information Technologies, 2025
Although some studies have examined the effects of self-regulated learning (SRL) strategies on learning effectiveness, inconsistent results have been reported. Additionally, studies that adopt the perspective of SRL to evaluate the effect of metacognitive skills on students' actual learning effectiveness in digital game-based learning (DGBL)…
Descriptors: Prior Learning, Metacognition, Game Based Learning, Learning Strategies
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
Leveraging Large Language Models to Generate Course-Specific Semantically Annotated Learning Objects
Dominic Lohr; Marc Berges; Abhishek Chugh; Michael Kohlhase; Dennis Müller – Journal of Computer Assisted Learning, 2025
Background: Over the past few decades, the process and methodology of automatic question generation (AQG) have undergone significant transformations. Recent progress in generative natural language models has opened up new potential in the generation of educational content. Objectives: This paper explores the potential of large language models…
Descriptors: Resource Units, Semantics, Automation, Questioning Techniques
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
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
Gustavo Gutierrez Carreon – Journal of Information Technology Education: Innovations in Practice, 2025
Aim/Purpose: The need for this paper arises from the lack of comprehensive studies comparing the impact of cloud-based versus local database systems on student learning outcomes. Specifically, there is a need to understand how these different approaches affect usability and cognitive load in educational settings, which are critical factors for…
Descriptors: Cognitive Processes, Difficulty Level, Information Storage, Information Technology
Chun-Ying Chen – ACM Transactions on Computing Education, 2025
This study examined the effects of worked examples with different explanation types and novices' motivation on cognitive load, and how this subsequently influenced their programming problem-solving performance. Given the study's emphasis on both instructional approaches and learner motivation, the Cognitive Theory of Multimedia Learning served as…
Descriptors: Models, Learning Motivation, Cognitive Processes, Difficulty Level
Zuhan Liu; Lili Wang – Education and Information Technologies, 2025
With the continuous development of embodied cognition theory and virtual reality (VR) technology, its application in teaching has been paid more and more attention by researchers. However, there are still few practical studies on the combination of VR technology and embodied learning. Starting from literature research, the paper analyzes the…
Descriptors: Cognitive Processes, Computer Simulation, Human Body, Experiential Learning
Haoming Wang; Chengliang Wang; Zhan Chen; Fa Liu; Chunjia Bao; Xianlong Xu – Education and Information Technologies, 2025
With the rapid development of artificial intelligence technology in the field of education, AI-Agents have shown tremendous potential in collaborative learning. However, traditional Computer-Supported Collaborative Learning (CSCL) methods still have limitations in addressing the unique demands of programming education. This study proposes an…
Descriptors: Artificial Intelligence, Cooperative Learning, Programming, Computer Science Education
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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