The DOI matches its Crossref record.
Virtual Labs: E-Learning for Tomorrow
Open accessAbstract
At Stanford University, the Virtual Labs project takes full advantage of information technology to provide innovative resources for learning and teaching
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“As an alternative to hands on tutorials, virtual laboratory simulations (vLAB) represent an exciting new way of preparing students for hands on exercises, such as laboratory work [7][8][9]”
From Virtual simulations as preparation for lab exercises: Assessing learning of key laboratory skills in microbiology and improvement of essential non-cognitive skills (2016) · cites this paper as [7]
Experimental — accuracy not yet measured
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
Cites
Still being checked.
Cited by
Makransky, G., Thisgaard, M. W., & Gadegaard, H. (2016) · PLOS ONE · doi:10.1371/journal.pone.0155895 · Cited by 212
Virtualization of science education: a lesson from the COVID-19 pandemic
Ray, S., & Srivastava, S. (2020) · Journal of Proteins and Proteomics · doi:10.1007/s42485-020-00038-7 · Cited by 143
Virtual Labs in proteomics: New E-learning tools
Ray, S., Koshy, N. R., Reddy, P. J., & Srivastava, S. (2012) · Journal of Proteomics · doi:10.1016/j.jprot.2012.03.014 · Cited by 52
Doubleday, E. G., O’Loughlin, V. D., & Doubleday, A. F. (2011) · Anatomical Sciences Education · doi:10.1002/ase.252 · Cited by 48
Mr. Vetro: A Collective Simulation for teaching health science
Ioannidou, A., Repenning, A., Webb, D. C., Keyser, D., Luhn, L., & Daetwyler, C. J. (2010) · International Journal of Computer-Supported Collaborative Learning · doi:10.1007/s11412-010-9082-8 · Cited by 46
Metadata
- Authors
- Huang, C.
- Affiliations
- Stanford University (US)
- Corresponding author
- Huang, Camillan
- Venue
- PLoS Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2004-06-15
- Volume
- 2
- Issue
- 6
- Pages
- e157
- ISSN
- 1544-9173 (ISSN-L)
- 1545-7885
- PMC
- PMC423136
- OpenAlex
- W2023483713
- Cited by
- 34
- References
- 0
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 3 · 2022: 1 · 2021: 2 · 2020: 4 · 2019: 1 · 2018: 2 · 2017: 1 · 2016: 3 · 2015: 1 · 2014: 1 · 2013: 1 · 2012: 2
- FWCI
- 4.21
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- Funders
- Howard Hughes Medical Institute
- Topics
- Social Sciences › Education › Experimental Learning in Engineering
- Physical Sciences › Computer Science › Information Systems › Educational Technology and E-Learning
- Social Sciences › Education › Various Chemistry Research Topics
- Keywords
- virtual laboratory, online learning, ICT in education, Stanford University, innovative teaching resources
- MeSH terms
- Computer-Assisted Instruction, Computer Graphics, Computer Simulation, Models, Biological, User-Computer Interface, Computational Biology, Education, Distance
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