Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 0 |
| Since 2007 (last 20 years) | 3 |
Descriptor
| Bayesian Statistics | 3 |
| Cognitive Development | 3 |
| Simulation | 3 |
| Decision Making | 2 |
| Learning | 2 |
| Models | 2 |
| Academic Achievement | 1 |
| Adolescents | 1 |
| At Risk Students | 1 |
| Behavior | 1 |
| Benchmarking | 1 |
| More ▼ | |
Author
| Almond, Russell G. | 1 |
| Goodman, Noah D. | 1 |
| Rieskamp, Jorg | 1 |
| Scheibehenne, Benjamin | 1 |
| Tenenbaum, Joshua B. | 1 |
| Ullman, Tomer D. | 1 |
| Wagenmakers, Eric-Jan | 1 |
Publication Type
| Journal Articles | 3 |
| Reports - Evaluative | 2 |
| Reports - Research | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Scheibehenne, Benjamin; Rieskamp, Jorg; Wagenmakers, Eric-Jan – Psychological Review, 2013
Many theories of human cognition postulate that people are equipped with a repertoire of strategies to solve the tasks they face. This theoretical framework of a cognitive toolbox provides a plausible account of intra- and interindividual differences in human behavior. Unfortunately, it is often unclear how to rigorously test the toolbox…
Descriptors: Cognitive Processes, Behavior, Models, Bayesian Statistics
Goodman, Noah D.; Ullman, Tomer D.; Tenenbaum, Joshua B. – Psychological Review, 2011
The very early appearance of abstract knowledge is often taken as evidence for innateness. We explore the relative learning speeds of abstract and specific knowledge within a Bayesian framework and the role for innate structure. We focus on knowledge about causality, seen as a domain-general intuitive theory, and ask whether this knowledge can be…
Descriptors: Causal Models, Logical Thinking, Cognitive Development, Bayesian Statistics
Almond, Russell G. – ETS Research Report Series, 2007
Over the course of instruction, instructors generally collect a great deal of information about each student. Integrating that information intelligently requires models for how a student's proficiency changes over time. Armed with such models, instructors can "filter" the data--more accurately estimate the student's current proficiency…
Descriptors: Markov Processes, Decision Making, Student Evaluation, Learning Processes

Peer reviewed
Direct link
