The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Correlating the effects of flow and telepresence in virtual worlds: Enhancing our understanding of user behavior in game-based learning
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Citations
Cites
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
Measuring Presence in Virtual Environments: A Presence Questionnaire
Witmer, B. G., & Singer, M. J. (1998) · Presence: Teleoperators and Virtual Environments · doi:10.1162/105474698565686 · Cited by 6,371
Defining virtual reality: Dimensions determining telepresence
Steuer, J. (1992) · Journal of Communication · doi:10.1111/j.1460-2466.1992.tb00812.x · Cited by 5,459
Sweetser (2005) · doi:10.1145/1077246.1077253 · Cited by 2,124
Optimal experience in work and leisure.
Csikszentmihalyi, M., & LeFevre, J. (1989) · Journal of Personality and Social Psychology · doi:10.1037//0022-3514.56.5.815 · Cited by 1,943
Digital game-based learning: Towards an experiential gaming model
Kiili, K. (2005) · The Internet and Higher Education · doi:10.1016/j.iheduc.2004.12.001 · Cited by 1,457
Musings on Telepresence and Virtual Presence
Sheridan, T. B. (1992) · Presence: Teleoperators and Virtual Environments · doi:10.1162/pres.1992.1.1.120 · Cited by 1,344 · cited 4×
“This feeling is sometimes strongly associated with vividness, arousal, focused attention, and interactivity, as well as high degrees of skill and control (Choi & Kim, 2004; Draper & Blair, 1996; Finneran & Zhang, 2003; Novak et al., 2000; Sheridan, 1992; Steuer, 1992).”
Influential
Cited by
Shin, D. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2017.09.012 · Cited by 738
Optimal experience of flow enhanced by telepresence: evidence from social media use
Pelet, J.-É., Ettis, S., & Cowart, K. (2017) · Information & Management · doi:10.1016/j.im.2016.05.001 · Cited by 354
Chang, C.-C., Liang, C., Chou, P.-N., & Lin, G.-Y. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.01.031 · Cited by 292
Kim, M. J., Lee, C.-K., & Bonn, M. (2017) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2017.04.006 · Cited by 120
Marinho, A., Bittencourt, I. I., Dermeval, D., Santos, J., Challco, G., & Reis, M. (2025) · Technology, Knowledge and Learning · doi:10.1007/s10758-024-09796-5 · Cited by 5
Metadata
- Authors
- Faiola, A., Newlon, C., Pfaff, M., & Smyslova, O.
- Venue
- Computers in Human Behavior
- Publisher
- Elsevier BV
- Published
- 2013-05
- Volume
- 29
- Issue
- 3
- Pages
- 1113-1121
- ISSN
- 0747-5632 (ISSN-L)
- OpenAlex
- W1982610488
- Cited by
- 273
- References
- 7
- FWCI
- 26.48
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
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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.
