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Linjing Wu; Xuelin Xiang; Xueyan Yang; Xuan Jin; Liang Chen; Qingtang Liu – Educational Technology Research and Development, 2025
Problem-solving strategies are crucial in learning programming. Owing to their hidden nature, traditional methods such as interviews and questionnaires cannot reflect the details and differences of problem-solving strategies in programming. This study uses the Hidden Markov Model to detect and compare the problem-solving strategies of different…
Descriptors: Markov Processes, Problem Solving, Programming, Identification
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
Zhaojun Duo; Jianan Zhang; Yonggong Ren; Xiaolu Xu – Education and Information Technologies, 2025
"Self-regulated learning" (SRL) significantly impacts the process and outcome of "programming problem-solving." Studies on SRL behavioural patterns of programming students based on trace data are limited in number and lack of coverage. In this study, hence, the Hidden Markov Model (HMM) was employed to probabilistically mine…
Descriptors: Students, Programming, Problem Solving, Self Management
Tarattakan Pachumwon; Thada Jantakoon; Rukthin Laoha – Higher Education Studies, 2025
This study introduces CAILE, a design thinking-driven conceptual framework for a Creative AI Learning Environment, designed to enhance programming skills. Evaluates clarity, appropriateness, and feasibility through expert judgment. Phase 1 synthesized 34 peer-reviewed studies (2019-2025) to articulate CAILE's structure across three layers: Inputs…
Descriptors: Creativity, Artificial Intelligence, Technology Uses in Education, Programming
Xu, Weiqi; Wu, Yajuan; Ouyang, Fan – International Journal of Educational Technology in Higher Education, 2023
Pair programming (PP), as a mode of collaborative problem solving (CPS) in computer programming education, asks two students work in a pair to co-construct knowledge and solve problems. Considering the complex multimodality of pair programming caused by students' discourses, behaviors, and socio-emotions, it is of critical importance to examine…
Descriptors: Cooperative Learning, Problem Solving, Computer Science Education, Programming
Ayesha Sohail; Huma Akram – Pedagogical Research, 2025
The ability to properly evaluate one's own academic progress has long been considered a predictor of academic success. However, its distinctive role in the context of computational mathematics remains underexplored. Grounded in social cognitive theory, this study investigates the critical role of self-regulated learning (SRL) strategies in…
Descriptors: Undergraduate Students, Mathematics Education, Mathematics Achievement, Self Evaluation (Individuals)
Siran Li; Jiangyue Liu; Qianyan Dong – Australasian Journal of Educational Technology, 2025
Recent advancements in generative artificial intelligence (GenAI) have drawn significant attention from educators and researchers. However, its effects on learners' programming performance, self-efficacy and learning processes remain inconclusive, while the mechanisms underlying its efficiency-enhancing potential are underexplored. This study…
Descriptors: Artificial Intelligence, Technology Uses in Education, Computer Science Education, Programming
Liu, Fang; Zhao, Liang; Zhao, Jiayi; Dai, Qin; Fan, Chunlong; Shen, Jun – IEEE Transactions on Learning Technologies, 2022
Educational process mining is now a promising method to provide decision-support information for the teaching-learning process via finding useful educational guidance from the event logs recorded in the learning management system. Existing studies mainly focus on mining students' problem-solving skills or behavior patterns and intervening in…
Descriptors: Data Use, Learning Management Systems, Problem Solving, Learning Processes
Wu, Wan-Rou; Yang, Kai-Lin – Cogent Education, 2022
This review study synthesises the literature on how computational thinking (CT) and mathematical thinking (MT) are integrated into mathematics education research with a focus on tasks. A review of 28 relevant articles on the Web of Science Core Collection database indicated that (1) CT helps students develop and apply mathematical concepts and…
Descriptors: Computation, Mathematics Education, Thinking Skills, Relationship
Margulieux, Lauren E.; Morrison, Briana B.; Decker, Adrienne – International Journal of STEM Education, 2020
Background: Programming a computer is an increasingly valuable skill, but dropout and failure rates in introductory programming courses are regularly as high as 50%. Like many fields, programming requires students to learn complex problem-solving procedures from instructors who tend to have tacit knowledge about low-level procedures that they have…
Descriptors: Programming, Computer Science Education, Introductory Courses, Withdrawal (Education)
Malik, Sohail Iqbal; Tawafak, Ragad M.; Shakir, Mohanaad – International Journal of Information and Communication Technology Education, 2021
A teaching approach plays an important role in teaching and learning process of an introductory programming (IP) course. The teaching approach should focus on different programming skills required by novice programmers. In this study, we introduced the teaching and learning approach based on an ADRI (Approach, Deployment, Result, Improvement)…
Descriptors: Computer Science Education, Programming, Teaching Methods, Learning Processes
Stone, Jeffrey A.; Cruz, Laura – Teaching & Learning Inquiry, 2021
Higher education has embraced integrative learning as a means of enabling students to tackle so-called "wicked" problems, i.e. problems that are sufficiently complex, contested, and ambiguous that conventional, disciplinary specific approaches are inadequate to address. However, challenges remain in defining integrative learning…
Descriptors: Introductory Courses, Computer Science Education, Interdisciplinary Approach, Integrated Activities
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
Wakhata, Robert; Balimuttajjo, Sudi; Mutarutinya, Védaste – Mathematics Teaching Research Journal, 2023
The present study explored 285 11th-grade students' preconceptions, misconceptions, and errors in solving mathematics tasks by graphical method. A descriptive-explorative study design was adopted. Cluster sampling was used to select students from sampled secondary schools in eastern and central Uganda. Students' paper and pen solution sketches…
Descriptors: Foreign Countries, Secondary School Mathematics, High School Students, Grade 11
Hosseini, Roya; Akhuseyinoglu, Kamil; Brusilovsky, Peter; Malmi, Lauri; Pollari-Malmi, Kerttu; Schunn, Christian; Sirkiä, Teemu – International Journal of Artificial Intelligence in Education, 2020
This research is focused on how to support students' acquisition of program construction skills through worked examples. Although examples have been consistently proven to be valuable for student's learning, the learning technology for computer science education lacks program construction examples with interactive elements that could engage…
Descriptors: Programming, Computer Science Education, Problem Solving, Learner Engagement

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