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Showing 1 to 15 of 21 results Save | Export
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Peng Chen; Dong Yang; Jia Zhao; Shu Yang; Jari Lavonen – Journal of Computer Assisted Learning, 2025
Background: Computational thinking (CT) refers to the ability to represent problems, design solutions and migrate solutions computationally. While previous studies have shown that self-explanation can enhance students' learning, few empirical studies have examined the effects of using different self-explanation prompts to cultivate students' CT…
Descriptors: Computation, Thinking Skills, Programming, Learning Processes
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Qing Yu; Kun Yu; Baomin Li – Journal of Educational Computing Research, 2025
Computer programming is regarded as an important skill for the future. However, many K-12 students face challenges and difficulties in learning traditional text-based programming. Block-based visual programming (BVP) can reduce the difficulty of learning programming and is seen as a potential programming education tool. Nevertheless, the effects…
Descriptors: Programming, Computer Science Education, Visual Aids, Outcomes of Education
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Xiaoheng Yan; Gila Hanna – International Journal of Mathematical Education in Science and Technology, 2025
As new technological developments continue to change the educational landscape, it is not an exception in the area of proof and proving. This classroom note introduces the use of one of the trending proofs assistants -- the Lean theorem prover. We first provide a technical account of Lean, then exemplify Lean proofs in propositional logic, number…
Descriptors: Mathematics Instruction, Undergraduate Students, Mathematical Logic, Validity
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Amedeo Pachera; Stefania Dumbrava; Angela Bonifati; Andrea Mauri – ACM Transactions on Computing Education, 2025
Query languages are the foundations of database teaching and education practices. The broad adoption of graph databases contrasts with the limited research into how they are taught. Contrary to relational databases, graph databases allow navigational queries with higher expressivity and lack an a priori schema. In this article, we design a…
Descriptors: Error Patterns, Graphs, Programming Languages, Databases
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Robin Samuelsson – British Journal of Educational Technology, 2025
Programming is becoming a key subject in early education globally, with surging problems of how computer science can become a subject for children of all ages and backgrounds. Problems of implementing new technologies in the old curricula have long been noted, and lately, concern over computer science education goals is often too narrow and…
Descriptors: Computer Science Education, Play, Early Childhood Education, Technology Integration
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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
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Hui-Zhi Hu; Li-Guo Zhang; Jia-Hua Zhang; Di Zhang; Jia-Rui Xie – Education and Information Technologies, 2025
Computer Science (CS) is a vital subject in K-12 education, and acquiring proficiency in CS is essential for nurturing talent. However, current teaching practices often rely on standardized tests to evaluate academic performance, which may not offer a comprehensive and multidimensional assessment of students' competency in learning CS.…
Descriptors: Evaluation Methods, Student Evaluation, Competence, Computer Literacy
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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
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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
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Ndudi Okechukwu Ezeamuzie; Mercy Noyenim Ezeamuzie – Review of Educational Research, 2025
Computer programming provides a framework for interdisciplinary learning in sciences, arts and languages. However, increasing integration of programming in K--12 shows that the block-based and text-based dichotomy of programming environments does not reflect the spectrum of their affordance. Hence, educators are confronted with a fundamental…
Descriptors: Kindergarten, Elementary Secondary Education, Computer Science Education, Programming
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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)
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Rahel Schmid; Robbert Smit; Nicolas Robin; Alexander Strahl – British Journal of Educational Psychology, 2025
Background: Students make many errors in visual programming. In order to learn from these, it is important that students regulate their emotions and view errors as learning opportunities. Aims: This study aimed to explore to what extent momentary emotions, specifically enjoyment, anxiety and boredom, as well as the error learning orientation of…
Descriptors: Psychological Patterns, Emotional Response, Learning Processes, Error Patterns
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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
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Isidor Kokalari; Kosta Lili – Science Education International, 2025
Physics, even though it is guided by simple principles, tends for many topics to be obscured in the mathematics redundancy. MATLAB®, as interactive software for computer algebra, has already had an important impact on the way physics is taught by educators. It has also had a substantial impact on the way research is performed by students to…
Descriptors: Computer Software, Physics, Science Instruction, Teaching Methods
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Elina Hannula; Kati Sormunen; Kai Hakkarainen; Tiina Korhonen – Education and Information Technologies, 2025
Transdisciplinary invention projects based on traditional and digital fabrication technologies engage young people in designing and making complex artifacts and constitute a central aspect of future-oriented education. In Finland, comprehensive school students (aged 7-15) from all over the country can practice their inventive skills in the annual…
Descriptors: Student Experience, Student Projects, Intellectual Property, Programming
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