Experimental Research: Simulations and Serious Games for Sustainability
3
Issued Date
2022-01-01
Resource Type
ISSN
03029743
eISSN
16113349
Scopus ID
2-s2.0-85135879282
Journal Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
13219 LNCS
Start Page
101
End Page
114
Rights Holder(s)
SCOPUS
Bibliographic Citation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol.13219 LNCS (2022) , 101-114
Suggested Citation
Nguyen U.P., Hallinger P. Experimental Research: Simulations and Serious Games for Sustainability. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol.13219 LNCS (2022) , 101-114. 114. doi:10.1007/978-3-031-09959-5_9 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/84379
Title
Experimental Research: Simulations and Serious Games for Sustainability
Author(s)
Author's Affiliation
Other Contributor(s)
Abstract
A review of experimental studies accounts for the effectiveness of simulation-based learning in generating behavior and other variables towards sustainability. A set of 35 studies from 1997–2019 was derived from the bibliometric database on simulations and serious games (SSG) featuring education for sustainable development (ESD). Key findings highlighted the effects of SSG on sustainable variables. The SSG featured in experiments focused on either multiple or single dimensions of sustainability and appeared in academic, household and workplace settings. The experiments are overweighed with quasi-experimental designs, indicating the challenges to achieve random assignments. The majority of the simulation gaming interventions showed significant effects on knowledge, attitude and behavior towards sustainability. Interpreting the effects requires clear evidence, particularly when effect size indicators were likely to be ignored or skipped. Future researchers must use appropriate analytical tools and justify key results to achieve statistically significant effects of SSG on outcome variables.