Design and evaluation of an interactive 3D dynamic visualizaton tool for functional anatomy

  • Joseph Grannum (Corresponding Author)
  • , Leo A. Siiman
  • , Ergi Bufasi
  • , Anna Liisa Tamm

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

2 Citations (Scopus)

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 languageEnglish
Title of host publicationIEEE 21st International Conference on Advanced Learning Technologies (ICALT 2021)
Subtitle of host publicationProceedings
EditorsMaiga Chang, Nian-Shing Chen, Demetrios G Sampson, Ahmed Tlili
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages216-220
Number of pages5
ISBN (Electronic)9781665441063
ISBN (Print)978-1-6654-3116-3
DOIs
Publication statusPublished - Jul 2021
Externally publishedYes
Event21st IEEE International Conference on Advanced Learning Technologies - Online, Tartu, Estonia
Duration: 12 Jul 202115 Jul 2021
Conference number: 21
https://ieeecs-media.computer.org/tc-media/sites/5/2020/12/29221821/ICALT-2021-front-matter.pdf

Publication series

NameIEEE International Conference on Advanced Learning Technologies
ISSN (Print)2161-3761
ISSN (Electronic)2161-377X

Conference

Conference21st IEEE International Conference on Advanced Learning Technologies
Abbreviated titleICALT 2021
Country/TerritoryEstonia
CityTartu
Period12/07/2115/07/21
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

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