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Huang Ham; Bonan Zhao; Thomas L. Griffiths; Natalia Vélez – Cognitive Science, 2025
A hallmark of effective teaching is that it grants learners not just a collection of facts about the world, but also a toolkit of abstractions that can be applied to solve new problems. How do humans teach abstractions from examples? Here, we applied Bayesian models of pedagogy to a necklace-building task where teachers create necklaces to teach a…
Descriptors: Teaching Methods, Instructional Effectiveness, Skill Development, Problem Solving
Timothy H. Lehmann – Mathematics Education Research Journal, 2024
The aim of this study is to examine how algorithmatizing tasks engage mathematics students in algorithmic thinking. Structured, task-based interviews were conducted with eight Year 12 students as they completed a sequence of algorithmatizing tasks involving maximum flow problems. A deductive-inductive analytical process was used to first classify…
Descriptors: Secondary School Mathematics, Secondary School Students, Grade 12, Mathematics Instruction
Wawan Kurniawan; Khairul Anwar; Jufrida Jufrida; Kamid Kamid; Cicyn Riantoni – Journal of Information Technology Education: Innovations in Practice, 2025
Aim/Purpose: This study aims to implement and evaluate a personalized digital learning environment (PDLE) that delivers differentiated instruction for enhancing computational thinking competencies through robotics education. Background: The background emphasizes the growing demand for computational thinking skills in the modern workforce and the…
Descriptors: Individualized Instruction, Electronic Learning, Computation, Thinking Skills
Ampawan Yindeemak; Thada Jantakoon; Rukthin Laoha – Higher Education Studies, 2025
This study aimed to design, develop, and validate the RSiSTEM framework, a robotics-based simulation learning model intended to foster students' problem-solving and systems thinking competencies within STEM education. The research followed a two-phase developmental design. In Phase 1, the framework was constructed through a systematic synthesis of…
Descriptors: Computer Simulation, Robotics, Technology Uses in Education, Problem Solving
Orly Barzilai; Sofia Sherman; Moshe Leiba; Hadar Spiegel – Journal of Information Systems Education, 2024
Data Structures and Algorithms (DS) is a basic computer science course that is a prerequisite for taking advanced information systems (IS) curriculum courses. The course aims to teach students how to analyze a problem, design a solution, and implement it using pseudocode to construct knowledge and develop the necessary skills for algorithmic…
Descriptors: Statistics Education, Problem Solving, Information Systems, Algorithms
Noawanit Songkram; Supattraporn Upapong; Heng-Yu Ku; Narongpon Aulpaijidkul; Sarun Chattunyakit; Nutthakorn Songkram – Interactive Learning Environments, 2024
This research proposes the integration of robotic education and scenario-based learning (SBL) paradigm for teaching computational thinking (CT) to enhance the computational abilities of primary school students, based on digital innovation and a teaching assistant robot acceptance model. The sample group consisted of 532 primary school teachers and…
Descriptors: Foreign Countries, Elementary School Students, Elementary School Teachers, Grade 1
Emit Snake-Beings; Andrew Gibbons; Ricardo Sosa – Teaching and Learning Research Initiative, 2024
This study explores learner engagement with Advanced Computational Thinking (ACT) in the New Zealand digital curriculum. "Advanced" in ACT refers to an expansive, transdisciplinary, and future-looking understanding of computational thinking (CT). ACT promotes CT beyond narrow modes of problem-solving (abstraction, algorithmic thinking,…
Descriptors: Computation, Thinking Skills, Shared Resources and Services, Learner Engagement
Hayes-Roth, Frederick – 1977
This paper is a theoretical discussion of several functions of knowledge systems based on the idea of partial matching, that is, comparison of two or more descriptions by identification of their similarities. Several knowledge system functions are described in terms of partial or best matchings including analogical reasoning, inductive inference,…
Descriptors: Abstract Reasoning, Algorithms, Educational Research, Learning
Peer reviewedCauley, Kathleen M. – Journal of Educational Psychology, 1988
This study assessed the extent to which procedurally proficient children (N=34) construct the part/whole logical structure that underlies the borrowing algorithm in subtraction. Results indicate that an understanding of the part/whole logic of number may be necessary to understand place value and borrowing. (TJH)
Descriptors: Abstract Reasoning, Algorithms, Elementary School Mathematics, Elementary School Students
Sternberg, Robert J. – 1979
About 25 children in each of grades 3, 5, 7, 9, and 11 were tested in their ability to solve linear syllogisms, such as: John is taller than Mary. Mary is taller than Pete. Who is tallest--John, Mary, or Pete? Response latencies and error rates decreased across grade levels and sessions. Component latencies also generally decreased with increasing…
Descriptors: Abstract Reasoning, Age Differences, Algorithms, Cognitive Development
Sternberg, Robert J.; Weil, Evelyn M. – 1979
An aptitude-strategy interaction in linear syllogistic reasoning was tested on 144 undergraduate and graduate students of both sexes. It was hypothesized that the efficiency of each of four alternative strategies--control, visual, algorithmic, and mixed--would depend upon the subjects' pattern of verbal and spatial abilities. Two tests of verbal…
Descriptors: Abstract Reasoning, Algorithms, Aptitude Treatment Interaction, Cognitive Ability
PDF pending restorationFleener, M. Jayne; And Others – 1993
Higher order cognitive development and success in the study of high school mathematics and science require an understanding of rational number concepts and facility with proportional reasoning and computation. Proportional reasoning is an essential schema for developing formal operational thought. This study involving 16 ninth-grade students was…
Descriptors: Abstract Reasoning, Algorithms, Cognitive Development, Formal Operations

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