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Higgins, Traci; Mokros, Jan; Rubin, Andee; Sagrans, Jacob – Teaching Statistics: An International Journal for Teachers, 2023
In the context of an afterschool program in which students explore relatively large authentic datasets, we investigated how 11- to 14-year old students worked with categorical variables. During the program, students learned to use the Common Online Data Analysis Platform (CODAP), a statistical analysis platform specifically designed for middle and…
Descriptors: Classification, After School Programs, Data Analysis, Middle School Students
Hu, Mingjia; Nosofsky, Robert M. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022
In a novel version of the classic dot-pattern prototype-distortion paradigm of category learning, Homa et al. (2019) tested a condition in which individual training instances never repeated, and observed results that they claimed severely challenged exemplar models of classification and recognition. Among the results was a dissociation in which…
Descriptors: Classification, Recognition (Psychology), Computation, Models
So, Joseph Chi-ho; Wong, Adam Ka-lok; Tsang, Kia Ho-yin; Chan, Ada Pui-ling; Wong, Simon Chi-wang; Chan, Henry C. B. – Journal of Technology and Science Education, 2023
The project presented in this paper aims to formulate a recommendation framework that consolidates the higher education students' particulars such as their academic background, current study and student activity records, their attended higher education institution's expectations of graduate attributes and self-assessment of their own generic…
Descriptors: Pattern Recognition, Artificial Intelligence, Higher Education, College Students

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