Abstract
The use of 2D teaching materials and laboratory classes form the gold standard of anatomy education. Students are typically required to extract spatial information from 2D representations (usually pictures or videos) and create mental 3D models; a major cognitive leap that educators underestimate. The purpose of this study was to design and evaluate a 3D dynamic visualization (3D Viz) to improve spatial thinking, and thereby, anatomical learning. The design applied certain features aimed at decreasing cognitive load while learning with the 3D Viz. A user experience approach was initially taken using a cognitive walkthrough and think-aloud protocol to evaluate the 3D Viz. Then an experimental intervention was conducted to compare 3D Viz with comparable 2D teaching materials. Complete data from a total of 22 participants was obtained. The intervention included a survey, learning tasks using 3D or 2D materials, a spatial anatomy test and a measurement of mental workload using the NASA Task Load Index. The results indicated that the overall mental workload did not differ significantly between 3D and 2D groups. However, the 3D group reported better performance and less frustration workload. The 3D group performed better on the spatial anatomy test. We propose that visual chunking was a strategy the 3D group tended to use when working with the learning tasks. Overall, the findings suggest that the 3D Viz can be used to improve spatial thinking and thereby anatomy knowledge. We recommend further investigation of the learning strategies and mechanisms by which 3D Viz in general can provide beneficial outcomes for learners.
| Original language | English |
|---|---|
| Title of host publication | IEEE 21st International Conference on Advanced Learning Technologies (ICALT 2021) |
| Subtitle of host publication | Proceedings |
| Editors | Maiga Chang, Nian-Shing Chen, Demetrios G Sampson, Ahmed Tlili |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 216-220 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781665441063 |
| ISBN (Print) | 978-1-6654-3116-3 |
| DOIs | |
| Publication status | Published - Jul 2021 |
| Externally published | Yes |
| Event | 21st IEEE International Conference on Advanced Learning Technologies - Online, Tartu, Estonia Duration: 12 Jul 2021 → 15 Jul 2021 Conference number: 21 https://ieeecs-media.computer.org/tc-media/sites/5/2020/12/29221821/ICALT-2021-front-matter.pdf |
Publication series
| Name | IEEE International Conference on Advanced Learning Technologies |
|---|---|
| ISSN (Print) | 2161-3761 |
| ISSN (Electronic) | 2161-377X |
Conference
| Conference | 21st IEEE International Conference on Advanced Learning Technologies |
|---|---|
| Abbreviated title | ICALT 2021 |
| Country/Territory | Estonia |
| City | Tartu |
| Period | 12/07/21 → 15/07/21 |
| Internet address |
Keywords*
- 3D design
- 3D dynamic visualization
- Anatomy education
- Mental workload
- Spatial thinking
- Visual chunking
Field of Science*
- 5.3 Educational sciences
- 1.2 Computer and information sciences
Publication Type*
- 3.1. Articles or chapters in proceedings/scientific books indexed in Web of Science and/or Scopus database