Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 2 |
| Since 2007 (last 20 years) | 2 |
Descriptor
| Accuracy | 2 |
| Classification | 2 |
| Cognitive Processes | 1 |
| Computation | 1 |
| Decision Making | 1 |
| Mathematics Skills | 1 |
| Models | 1 |
| Number Concepts | 1 |
| Simulation | 1 |
| Undergraduate Students | 1 |
Source
| Cognitive Science | 2 |
Author
| Charlesworth, Arthur | 1 |
| Edmunds, Charlotte E. R. | 1 |
| Landy, David | 1 |
| Milton, Fraser | 1 |
| Ottmar, Erin | 1 |
| Wills, Andy J. | 1 |
Publication Type
| Journal Articles | 2 |
| Reports - Research | 2 |
Education Level
| Higher Education | 1 |
| Postsecondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Edmunds, Charlotte E. R.; Milton, Fraser; Wills, Andy J. – Cognitive Science, 2018
Behavioral evidence for the COVIS dual-process model of category learning has been widely reported in over a hundred publications (Ashby & Valentin, 2016). It is generally accepted that the validity of such evidence depends on the accurate identification of individual participants' categorization strategies, a task that usually falls to…
Descriptors: Simulation, Models, Cognitive Processes, Classification
Landy, David; Charlesworth, Arthur; Ottmar, Erin – Cognitive Science, 2017
How do people stretch their understanding of magnitude from the experiential range to the very large quantities and ranges important in science, geopolitics, and mathematics? This paper empirically evaluates how and whether people make use of numerical categories when estimating relative magnitudes of numbers across many orders of magnitude. We…
Descriptors: Undergraduate Students, Computation, Mathematics Skills, Number Concepts

Peer reviewed
Direct link
