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Tamara Broderick; Andrew Gelman; Rachael Meager; Anna L. Smith; Tian Zheng – Grantee Submission, 2022
Probabilistic machine learning increasingly informs critical decisions in medicine, economics, politics, and beyond. To aid the development of trust in these decisions, we develop a taxonomy delineating where trust in an analysis can break down: (1) in the translation of real-world goals to goals on a particular set of training data, (2) in the…
Descriptors: Taxonomy, Trust (Psychology), Algorithms, Probability
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Huo, Rongrong – European Journal of Science and Mathematics Education, 2023
In our investigation of university students' knowledge about real numbers in relation to computer algebra systems (CAS) and how it could be developed in view of their future activity as teachers, we used a computer algorithm as a case to explore the relationship between CAS and the knowledge of real numbers as decimal representations. Our work was…
Descriptors: Numbers, Computer Science Education, Knowledge Level, Algorithms
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Kant, Elaine; Newell, Allen – Information Processing and Management, 1984
Presents model of algorithm design (activity in software development) based on analysis of protocols of two subjects designing three convex hull algorithms. Automation methods, methods for studying algorithm design, role of discovery in problem solving, and comparison of different designs of case study according to model are highlighted.…
Descriptors: Algorithms, Automation, Case Studies, Comparative Analysis
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Gal-Ezer, Judith; Lichtenstein, Orna – Mathematics and Computer Education, 1997
Shows by means of a mathematical example how algorithmic thinking and mathematical thinking complement each other. An algorithmic approach can lead to questions that deepen the understanding of mathematics material. (DDR)
Descriptors: Algorithms, Case Studies, Cognitive Processes, Computer Science Education