Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 1 |
| Since 2007 (last 20 years) | 3 |
Descriptor
| Computer Assisted Testing | 5 |
| Mathematical Models | 5 |
| Problem Solving | 5 |
| Artificial Intelligence | 3 |
| Educational Technology | 3 |
| Probability | 3 |
| Cognitive Processes | 2 |
| Cognitive Style | 2 |
| Computer Software | 2 |
| Correlation | 2 |
| Error Patterns | 2 |
| More ▼ | |
Author
| Tatsuoka, Kikumi K. | 2 |
| Tatsuoka, Maurice M. | 2 |
| Koedinger, Kenneth R. | 1 |
| Lu, Hong | 1 |
| Pavlik, Philip I., Jr. | 1 |
| Wang, Chao | 1 |
| Yudelson, Michael | 1 |
Publication Type
| Reports - Research | 4 |
| Collected Works - Proceedings | 1 |
| Journal Articles | 1 |
| Speeches/Meeting Papers | 1 |
Education Level
| Elementary Secondary Education | 1 |
| Grade 6 | 1 |
| Grade 7 | 1 |
| Higher Education | 1 |
| Postsecondary Education | 1 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Wang, Chao; Lu, Hong – Educational Technology & Society, 2018
This study focused on the effect of examinees' ability levels on the relationship between Reflective-Impulsive (RI) cognitive style and item response time in computerized adaptive testing (CAT). The total of 56 students majoring in Educational Technology from Shandong Normal University participated in this study, and their RI cognitive styles were…
Descriptors: Item Response Theory, Computer Assisted Testing, Cognitive Style, Correlation
Pavlik, Philip I., Jr.; Yudelson, Michael; Koedinger, Kenneth R. – Society for Research on Educational Effectiveness, 2011
The objective of this research was to better understand the transfer of learning between different variations of pre-algebra problems. While the authors could have addressed a specific variation that might address transfer, they were interested in developing a general model of transfer, so we gathered data from multiple problem types and their…
Descriptors: Transfer of Training, Item Analysis, Educational Technology, Algebra
Tatsuoka, Kikumi K.; Tatsuoka, Maurice M. – 1986
The rule space model permits measurement of cognitive skill acquisition, diagnosis of cognitive errors, and detection of the strengths and weaknesses of knowledge possessed by individuals. Two ways to classify an individual into his or her most plausible latent state of knowledge include: (1) hypothesis testing--Bayes' decision rules for minimum…
Descriptors: Artificial Intelligence, Bayesian Statistics, Cognitive Development, Computer Assisted Testing
Tatsuoka, Kikumi K.; Tatsuoka, Maurice M. – 1985
The study examines the rule space model, a probabilistic model capable of measuring cognitive skill acquisition and of diagnosing erroneous rules of operation in a procedural domain. The model involves two important components: (1) determination of a set of bug distributions (bug density functions representing clusters around the rules); and (2)…
Descriptors: Artificial Intelligence, Cognitive Processes, Computer Assisted Testing, Computer Software
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers

Peer reviewed
Direct link
