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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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Karen Murcia; Emma Cross; Geoffrey Lowe – Australian Educational Researcher, 2025
The importance of incorporating digital technologies into early childhood education is now widely accepted to help position children as creative producers and not just consumers of technology. Early childhood educators in turn have a key role to play in developing technology-related skills and competencies such as coding and computational thinking…
Descriptors: Young Children, Computation, Thinking Skills, Play
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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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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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Yun Dai – Education and Information Technologies, 2025
There is a growing consensus that AI literacy requires a holistic lens, including not only technical knowledge and skills but also social and ethical considerations. Yet, providing holistic AI education for upper-primary students remains challenging due to the abstract and complex nature of AI and a lack of pedagogical experiences in schools.…
Descriptors: Integrated Activities, Holistic Approach, Artificial Intelligence, Computer Science Education
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Emily R. DeFouw; Melissa A. Collier-Meek; Brian Daniels; Robin S. Codding; Margarida Veiga – Journal of Applied School Psychology, 2025
For schools implementing Response-to-Intervention, it is important to understand how to efficiently intensify interventions. Treatment intensity, or intervention design, is a critical yet overlooked and understudied aspect in math. More frequent dosage results in greater student gains. However, questions remain regarding how teaching episodes…
Descriptors: Mathematics Instruction, Teaching Methods, Outcomes of Education, Response to Intervention
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Zhizezhang Gao; Haochen Yan; Jiaqi Liu; Xiao Zhang; Yuxiang Lin; Yingzhi Zhang; Xia Sun; Jun Feng – International Journal of STEM Education, 2025
Background: With the increasing interdisciplinarity between computer science (CS) and other fields, a growing number of non-CS students are embracing programming. However, there is a gap in research concerning differences in programming learning between CS and non-CS students. Previous studies predominantly relied on outcome-based assessments,…
Descriptors: Computer Science Education, Mathematics Education, Novices, Programming