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The impact of peer competition and collaboration on gamified learning performance in educational settings: a Meta-analytical study

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Abstract

This study is a meta-analytical study that examines the effectiveness of gamification in learning performance in educational settings (n = 29; year-span = 2011–2019). Specifically, it aimed to investigate (a) whether gamification could improve learning performance, and (b) whether peer interaction (i.e., peer competition and peer collaboration) moderated the effectiveness of gamification in learning performance. Results from random-effects models showed significant effects of gamification in learning performance (g = .595, 95% CI [.432, .758], N = 3515). This effect remained robust after excluding outliers and was stable in a sub-split analysis that excludes studies with low methodological rigor (i.e., studies with pre-post test design). Subgroup analyses revealed a moderating effect of peer competition in gamification in learning, suggesting that competitive games were better than non-competitive games for promoting learning performance in educational settings. However, this effect was not robust and no evidence of subgroup differences were found in the sub-split analysis. Peer collaboration did not moderate the effectiveness of gamification in learning as no subgroup differences were found between collaborative games and non-collaborative games. The effectiveness of games that were both competitive and collaborative did not differ from those that were only competitive. Other moderators such as education level and research design were also investigated. No subgroup differences were found for these two moderators. Educational implications and limitations were further discussed.

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Notes

  1. As the pre-post test correlation was required to compute the effect sizes of studies with pre-test measures (e.g., see Borenstein, 2009, p. 227, Equation 12.21), missing values of the correlation in some studies would lead to missing effect sizes of those studies. As the pre-post test correlations reported were inconsistent across studies (the average estimate is .634, range from .387 to .8), it was inappropriate to impute a common value from them (Higgins & Green, 2011). Therefore, a sensitivity analysis was conducted to evaluate the robustness of the results. Different estimates drawn from the aforementioned range of pre-post test correlations (.40, .60 and .8 0) were imputed for missing pre-post test correlations and no substantial change in results was found . Thus, we reported findings of an imputed estimate of .60 in this meta-analysis as this was approximate to the average

  2. In subgroup analysis, CMA offers two options in terms of computational models: a pooled estimate of τ2 and with separate estimates of τ2. In this study, separate estimates of τ2 were used for all moderators since a) the true study-to-study dispersion was expected to differ across subgroups; b) there were unequal numbers of studies in each subgroup; and c) the variances in subgroups were likely to vary for moderators with intervention effects (e.g., competitive games versus non-competitive games) (Borenstein et al., 2009)

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Acknowledgments

The authors would like to thank Prof. Catherine McBride, Prof. Wai Chan, Prof. Suzanne So and Prof. Scott Aubrey for their feedback on this manuscript.

Availability of data and material

The coding sheet will be made available to the public as supplementary documents in order to achieve data transparency.

Funding

No funding was received to assist with the preparation of this manuscript.

Author information

Authors and Affiliations

  1. Department of Psychology, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR

    Jana Chi-San Ho

  2. Hong Kong, Hong Kong SAR

    Yu-Sheng Hung

  3. Department of Psychology, The University of Macau, Macau SAR, China

    Letty Y.-Y. Kwan

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  1. Jana Chi-San Ho
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Contributions

Jana Chi-San Ho and Letty Y.-Y. Kwan contributed to the study conception and design. The search of included primary studies, coding process and data analysis were performed by Jana Chi-San Ho. Yu-Sheng Hung was the second coder and double-checked data analysis. The first draft of the manuscript was written by Jana Chi-San Ho and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Jana Chi-San Ho.

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Appendices

Appendix 1

See Table 3.

Table 3 Sensitivity Analysis
Full size table

Appendix 2

1.1 Risk of Bias

Note: A study can be awarded a maximum of one star for each numbered item within the Selection and Outcome categories.

Selection

  1. 1)

    Representativeness of the gaming condition

  1. a)

    truly representative of the average students in educational settings*

  2. b)

    somewhat representative of the average students in educational settings*

  3. c)

    selected group of users

  4. d)

    no description of the derivation of the condition

  1. 2)

    Selection of the non-gaming condition

  1. a)

    drawn from the same community as the gaming condition *

  2. b)

    drawn from a different source

  3. c)

    no description of the derivation of the non-gaming condition

  1. 3)

    Ascertainment of gamification

  1. a)

    features of gamification were demonstrated *

  2. b)

    game designs were illustrated *

  3. c)

    no description

  1. 4)

    Demonstration that learning performance was equal at start of study

  1. a)

    yes *

  2. b)

    no

Comparability.

Comparability of conditions on the basis of the design or analysis

  1. 1)

    study controls for pre-condition scores for learning performance *

  2. 2)

    participation in the gaming condition does not directly affect learning performance (e.g., no extra points are rewarded toward the test score for participation in games)*

Outcome

  1. 1)

    Assessment of learning performance

  1. a)

    record linkage (e.g., test score) *

  2. b)

    knowledge or skills measured *

  3. c)

    others

  1. 2)

    Was follow-up long enough (> two weeks) for the effect of gamification to occur

  1. a)

    yes *

  2. b)

    no

  3. c)

    unclear

  1. 3)

    Adequacy of follow up of conditions

  1. a)

    complete follow up - all subjects accounted for *

  2. b)

    subjects lost to follow up unlikely to introduce bias - small number lost - > 90% follow up, or description provided of those lost) *

  3. c)

    follow up rate < 90% and no description of those lost

  4. d)

    no statement

Table 4 Risk of Bias in Individual Studies
Full size table

Appendix 3

See Table 5.

Table 5 Study Characteristics
Full size table

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Ho, J.CS., Hung, YS. & Kwan, L.YY. The impact of peer competition and collaboration on gamified learning performance in educational settings: a Meta-analytical study. Educ Inf Technol 27, 3833–3866 (2022). https://doi.org/10.1007/s10639-021-10770-2

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  • DOI: https://doi.org/10.1007/s10639-021-10770-2

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