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Josefina Ventre; Agustina L. Renna; Francisco J. Ibañez – Journal of Chemical Education, 2023
It is crucial nowadays to predict in a fast and simple manner physical-chemical behaviors like, the size-dependent optical properties of gold nanospheres (Au NSs). The idea behind this experiment is trying to replace (as much as possible) robust and expensive microscopy techniques with UV-vis spectrophotometry and friendly simulations. Students…
Descriptors: Chemistry, Prediction, Science Experiments, Spectroscopy
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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Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating
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Kolata, Gina Bari – Science, 1974
Although today's computers can perform as many as one million operations per second, there are many problems that are still too large to be solved in a straightforward manner. Recent work indicates that many approximate solutions are useful and more efficient than exact solutions. (Author/RH)
Descriptors: Algorithms, Computers, Mathematics, Prediction
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Durnin, John; Scandura, Joseph M. – Journal of Educational Psychology, 1973
The purpose of this study was to compare three technologies: the item forms technology (domain-referenced testing) of Hively et al. (1968), the hierarchical or stratified item forms technology of Ferguson (1969), and the algorithmic technology of Scandura (1971, 1973). (Author/RK)
Descriptors: Algorithms, Behavior, Data Analysis, Educational Psychology
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Gray, John S. – Journal of Computing in Higher Education, 1994
A detailed analysis and computer-based solution to a puzzle addressing the arrangement of dominoes on a grid is presented. The problem is one used in a college-level data structures or algorithms course. The solution uses backtracking to generate all possible answers. Details of the use of backtracking and techniques for mapping abstract problems…
Descriptors: Algorithms, Computer Assisted Instruction, Computer Science Education, Computer Software