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Rona Riantini; Mochamad Hariadi; Supeno Mardi Susiki Nugroho; Diah Puspito Wulandari; Wahyu Suci Rohqani – IEEE Transactions on Education, 2025
Contribution: This article proposes the systematic integration of embedded systems into training hardware to bridge the gap in structured troubleshooting education. Traditional methods often rely on manual explanations, virtual simulations, or on-the-job training, which lack structured learning experiences. The proof-of-work module, developed…
Descriptors: Engineering Education, Troubleshooting, Engineering, Experiential Learning
Rafi' Safadi; Nadera Hawa – Mathematics Teacher: Learning and Teaching PK-12, 2025
Graded Troubleshooting (GTS) is a powerful routine that teachers can use easily to engender students' metacognitive thinking and boost their understanding of mathematics concepts and procedures. This article describes a new GTS activity designed to prompt students to efficiently exploit worked examples when asked to diagnose erroneous examples…
Descriptors: Mathematics Education, Mathematics Instruction, Problem Solving, Troubleshooting
Heidi Taveter; Marina Lepp – Informatics in Education, 2025
Learning programming has become increasingly popular, with learners from diverse backgrounds and experiences requiring different support. Programming-process analysis helps to identify solver types and needs for assistance. The study examined students' behavior patterns in programming among beginners and non-beginners to identify solver types,…
Descriptors: Behavior Patterns, Novices, Expertise, Programming
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
Yuan Yao; Yiwen Sun; Siyu Zhu; Xinhua Zhu – European Journal of Education, 2025
Recent years have witnessed a growing application of generative artificial intelligence (GenAI) technology in writing instruction. Students should mobilise their metacognitive strategies during this endeavour to maximise the benefits of GenAI while avoiding the potential negative impacts. Within the context of tertiary education in Hong Kong, this…
Descriptors: Metacognition, Learning Strategies, Graduate Students, Technology Uses in Education
Xiner Liu; Andres Felipe Zambrano; Ryan S. Baker; Amanda Barany; Jaclyn Ocumpaugh; Jiayi Zhang; Maciej Pankiewicz; Nidhi Nasiar; Zhanlan Wei – Journal of Learning Analytics, 2025
This study explores the potential of the large language model GPT-4 as an automated tool for qualitative data analysis by educational researchers, exploring which techniques are most successful for different types of constructs. Specifically, we assess three different prompt engineering strategies -- Zero-shot, Few-shot, and Fewshot with…
Descriptors: Coding, Artificial Intelligence, Automation, Data Analysis
MiJeong Kim; JaMee Kim; WonGyu Lee – Education and Information Technologies, 2025
In the digital age, computational thinking (CT)-based problem-solving skills have emerged as essential competencies. Particularly, students with intellectual disabilities need equal educational opportunities and high-quality informatics education to cultivate CT-based problem-solving skills. However, research on the enhancement of CT-based…
Descriptors: Intellectual Disability, Programming, Computation, Thinking Skills
David DeLiema; Ashley Hufnagle; Miguel Ovies-Bocanegra – British Journal of Educational Psychology, 2025
Background: Moments of failure during learning present a wide range of opportunities for growth. However, experimental research and meta reviews focused on failure and learning tend to target singular valued learning processes, such as efficient fixes or transfer of conceptual understanding. These analytical decisions conflict with research…
Descriptors: Middle School Students, Nonprofit Organizations, Summer Programs, Workshops
Merve Aydin; Ünal Çakiroglu – Journal of Computer Assisted Learning, 2025
Background: Students experience higher-order thinking skills by finding ways to solve the problem, debugging errors while applying the solution, and testing the solution in programming. However, the inability to create schemas that will characterise programming structures is one of the difficulties during this process. Objectives: This study aimed…
Descriptors: Programming, Computer Science Education, Thinking Skills, Problem Solving