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) | 2 |
Descriptor
| Depth Perception | 2 |
| Manipulative Materials | 2 |
| Models | 2 |
| Spatial Ability | 2 |
| Video Technology | 2 |
| Anatomy | 1 |
| Brain | 1 |
| Coding | 1 |
| College Science | 1 |
| Focus Groups | 1 |
| Foreign Countries | 1 |
| More ▼ | |
Author
| Akle, Veronica | 1 |
| Boxerman, Jonathan | 1 |
| Davenport, Jodi L. | 1 |
| Olson, Arthur | 1 |
| Peña-Silva, Ricardo A. | 1 |
| Rincón-Perez, Carlos W. | 1 |
| Silberglitt, Matt | 1 |
| Valencia, Diego M. | 1 |
Publication Type
| Reports - Research | 2 |
| Journal Articles | 1 |
| Speeches/Meeting Papers | 1 |
Education Level
| Higher Education | 2 |
| Postsecondary Education | 1 |
Audience
Location
| California | 1 |
| Colombia | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Validation of Clay Modeling as a Learning Tool for the Periventricular Structures of the Human Brain
Akle, Veronica; Peña-Silva, Ricardo A.; Valencia, Diego M.; Rincón-Perez, Carlos W. – Anatomical Sciences Education, 2018
Visualizing anatomical structures and functional processes in three dimensions (3D) are important skills for medical students. However, contemplating 3D structures mentally and interpreting biomedical images can be challenging. This study examines the impact of a new pedagogical approach to teaching neuroanatomy, specifically how building a…
Descriptors: Anatomy, Visualization, Brain, Medical Education
Davenport, Jodi L.; Silberglitt, Matt; Boxerman, Jonathan; Olson, Arthur – Grantee Submission, 2014
3D models derived from actual molecular structures have the potential to transform student learning in biology. We share findings related to our research questions: 1) what types of interactions with a protein folding kit promote specific learning objectives?, and 2) what features of the instructional environment (e.g., peer interactions, teacher…
Descriptors: Geometric Concepts, Depth Perception, Spatial Ability, Models

Peer reviewed
Direct link
