The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
An Empirical Test of the Theory of Gamified Learning: The Effect of Leaderboards on Time-on-Task and Academic Performance
Abstract
Background: The theory of gamified learning provides a theoretical framework to test the impact of gamification efforts upon learner behaviors and attitudes, as well as the effect of these behavioral and attitudinal changes on learning. It does so by providing mediating and moderating processes linking specific game elements to learning outcomes. Aim: This article links specific game elements common to leaderboards (conflict/challenge, rules/goals, and assessment) with a focal learner behavior, time-on-task, by exploring educational research on competition and psychological research on goal-setting theory. Method: The mediating process of the theory of gamified learning is tested experimentally by assigning learners completing an online wiki-based project to a gamified version with a leaderboard or to a control version without a leaderboard. Leaderboard achievement was not tied to course grades. Results: Random assignment to leaderboards supported a causal effect. Students with leaderboards interacted with their project 29.61 more times, on average, than those in a control condition. Bootstrapping was used to support the mediation of the effect of gamification on academic achievement by this amount of time. Conclusion: The mediating process of the theory of gamified instruction is supported. Leaderboards can be used to improve course performance under certain circumstances.
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Cites
SPSS and SAS procedures for estimating indirect effects in simple mediation models
Preacher, K. J., & Hayes, A. F. (2004) · Behavior Research Methods, Instruments, & Computers · doi:10.3758/bf03206553 · Cited by 17,383
The role of deliberate practice in the acquisition of expert performance
Ericsson, K. A., Krampe, R. T., & Tesch-Römer, C. (1993) · Psychological Review · doi:10.1037/0033-295x.100.3.363 · Cited by 9,564
Does Gamification Work? -- A Literature Review of Empirical Studies on Gamification
Hamari, J., Koivisto, J., & Sarsa, H. (2014) · 2014 47th Hawaii International Conference on System Sciences · doi:10.1109/hicss.2014.377 · Cited by 5,201
Kraiger, K., Ford, J. K., & Salas, E. (1993) · Journal of Applied Psychology · doi:10.1037/0021-9010.78.2.311 · Cited by 1,831 · cited 1×
“Fourth, we recommend rigorous evaluative techniques appropriate to the type of training/instruction conducted (see Kraiger, Ford, & Salas, 1993; Kuncel & Campbell, 2001; Landers & Callan, 2012).”
MethodToward a Taxonomy Linking Game Attributes to Learning: An Empirical Study
Bedwell, W. L., Pavlas, D., Heyne, K., Lazzara, E. H., & Salas, E. (2012) · Simulation & Gaming · doi:10.1177/1046878112439444 · Cited by 393
Landers, R. N., & Callan, R. C. (2011) · Serious Games and Edutainment Applications · doi:10.1007/978-1-4471-2161-9_20 · Cited by 272
Self-citation
Research works printed but not linked: 22
- 10.1016/j.compedu.2008.12.020 · DOI
- 10.1111/j.1744-6570.2001.tb00093.x · DOI
- 10.1007/978-3-319-10208-5_28 · DOI
- Cheong C., 2013, Proceedings of Pacific Asia Conference on Information Systems
- Cohen J., 1988, Statistical power analysis for the behavioral sciences
- Deterding S., 2011, Proceedings of the CHI 2011 Gamification Workshop
- 10.1016/j.compedu.2012.12.020 · DOI
- Doran G. T., 1981, Management Review, 70, 35
- Farzan R., 2008, Symposium on Persuasive Technology
- Goldstein I. L., 1993, Training in organizations: Needs assessment, development, and evaluation
- 10.1037/0021-9010.74.4.657 · DOI · Paper page
- Kuncel N. R., 2001, Handbook of industrial, work & organizational psychology, 2, 278
- Landers R. N., Simulation & Gaming: An Interdisciplinary Journal
- 10.1007/978-3-319-10208-5_9 · DOI
- Landers R. N., Callan R. C. (2012). Training evaluation in virtual worlds: Development of a model. Journal of Virtual Worlds Research, 5(3). Retrieved from https://journals.tdl.org/jvwr/index.php/jvwr/article/view/6335 · DOI
- Landers R. N., Computers in Human Behavior
- Locke E. A., 1990, A theory of goal setting & task performance
- 10.3102/00346543047001087 · DOI
- Pychyl T. A., 2000, Journal of Social Behavior and Personality, 15, 239
- 10.3102/00346543050002315 · DOI · Paper page
- 10.1080/02796015.2007.12087958 · DOI
- 10.1177/1046878198291002 · DOI
Cited by
Sailer, M., Hense, J. U., Mayr, S. K., & Mandl, H. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2016.12.033 · Cited by 2,064
Gamifying education: what is known, what is believed and what remains uncertain: a critical review
Dichev, C., & Dicheva, D. (2017) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-017-0042-5 · Cited by 2,112
Developing a Theory of Gamified Learning: Linking Serious Games and Gamification of Learning
Landers, R. N. (2014) · Simulation & Gaming · doi:10.1177/1046878114563660 · Cited by 918
Self-citationGamification of task performance with leaderboards: A goal setting experiment
Landers, R. N., Bauer, K. N., & Callan, R. C. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2015.08.008 · Cited by 474
Self-citationHuang, B., Hew, K. F., & Lo, C. K. (2019) · Interactive Learning Environments · doi:10.1080/10494820.2018.1495653 · Cited by 406
Metadata
- Authors
- Landers, R. N., & Landers, A. K.
- Venue
- Simulation & Gaming
- Publisher
- SAGE Publications
- Published
- 2014-12
- Volume
- 45
- Issue
- 6
- Pages
- 769-785
- ISSN
- 1046-8781 (ISSN-L)
- 1552-826X
- OpenAlex
- W2160363390
- Cited by
- 363
- References
- 6
- FWCI
- 33.70
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
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