Publication Date
| In 2025 | 0 |
| Since 2024 | 0 |
| Since 2021 (last 5 years) | 0 |
| Since 2016 (last 10 years) | 2 |
| Since 2006 (last 20 years) | 2 |
Descriptor
| Data Interpretation | 3 |
| Learning Strategies | 3 |
| Models | 3 |
| Arithmetic | 1 |
| Associative Learning | 1 |
| Coding | 1 |
| College Students | 1 |
| Cooperative Learning | 1 |
| Cytology | 1 |
| Drills (Practice) | 1 |
| Inferences | 1 |
| More ▼ | |
Author
| Anderson, John R. | 1 |
| Bolger, Molly S. | 1 |
| Meddleton, Shanice | 1 |
| Stolovitch, Harold D. | 1 |
| Tenison, Caitlin | 1 |
| Zagallo, Patricia | 1 |
Publication Type
| Journal Articles | 3 |
| Reports - Research | 3 |
| Guides - Classroom - Teacher | 1 |
Education Level
| Higher Education | 2 |
| Postsecondary Education | 2 |
Audience
Location
| Arizona | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkZagallo, Patricia; Meddleton, Shanice; Bolger, Molly S. – CBE - Life Sciences Education, 2016
We present our design for a cell biology course to integrate content with scientific practices, specifically data interpretation and model-based reasoning. A 2-year research project within this course allowed us to understand how students interpret authentic biological data in this setting. Through analysis of written work, we measured the extent…
Descriptors: Undergraduate Students, Science Education, Cytology, Instructional Design
Tenison, Caitlin; Anderson, John R. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
A focus of early mathematics education is to build fluency through practice. Several models of skill acquisition have sought to explain the increase in fluency because of practice by modeling both the learning mechanisms driving this speedup and the changes in cognitive processes involved in executing the skill (such as transitioning from…
Descriptors: Skill Development, Mathematics Skills, Learning Processes, Markov Processes
Stolovitch, Harold D. – Performance and Instruction, 1990
Explains a model that can be used for debriefing after a highly interactive training activity such as role playing or simulation games. Elements of the model include (1) general decompression; (2) factual information from the activity; (3) inferences; (4) transfer, i.e., from the activity to real world situations; (5) generalizations; and (6)…
Descriptors: Data Interpretation, Inferences, Interaction, Learning Strategies
