The DOI matches its Crossref record.
ScienceSpace: virtual realities for learning complex and abstract scientific concepts
Abstract
Three virtual worlds have been built to investigate the effect of immersive, multisensory computer-generated experiences on learning topics in science. Currently targeted at high school and beginning college students, these worlds address Newtonian mechanics, electrostatics, and molecular structure and dynamics. Data has been collected on usability and learning through questionnaires, pre- and post-tests, in situ prediction and experiment and post-session interviews. The results are not uniformly conclusive but suggest that students can improve their mastery of abstract concepts through the use of virtual environments that have been designed for learning. Moreover, usability studies have identified many significant problems that have been addressed in successive refinements of these worlds. Future work will include collaborative learning studies (both local and distant), use of intelligent agents, and comparison with two-dimensional microworlds.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
A Review of Research on Augmented Reality in Education: Advantages and Applications
Saidin, N. F., Abd Halim, N. D., & Yahaya, N. (2015) · International Education Studies · doi:10.5539/ies.v8n13p1 · Cited by 347
Liu, R., Wang, L., Lei, J., Wang, Q., & Ren, Y. (2020) · British Journal of Educational Technology · doi:10.1111/bjet.13028 · Cited by 267
Application of virtual reality technology in biology education
Shim, K.-C., Park, J.-S., Kim, H.-S., Kim, J.-H., Park, Y.-C., & Ryu, H.-I. (2003) · Journal of Biological Education · doi:10.1080/00219266.2003.9655854 · Cited by 152
A review: Can robots reshape K-12 STEM education?
Karim, M. E., Lemaignan, S., & Mondada, F. (2015) · 2015 IEEE International Workshop on Advanced Robotics and its Social Impacts (ARSO) · doi:10.1109/arso.2015.7428217 · Cited by 145
Metadata
- Authors
- Dede, C., Salzman, M. C., & Bowen Loftin, R.
- Venue
- Proceedings of the IEEE 1996 Virtual Reality Annual International Symposium
- Publisher
- IEEE
- Published
- 1996
- Pages
- 246-252
- OpenAlex
- W2545461012
- Cited by
- 201
- References
- 0
- FWCI
- 6.37
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: ScienceSpace: virtual realities for learning complex and abstract scientific concepts. https://app.cochat.ai/papers/10.1109/vrais.1996.490534
- The paper
- Dede, C., Salzman, M. C., & Bowen Loftin, R. (1996). ScienceSpace: virtual realities for learning complex and abstract scientific concepts. Proceedings of the IEEE 1996 Virtual Reality Annual International Symposium. https://doi.org/10.1109/vrais.1996.490534
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
