Why do we need to employ Bayesian statistics and how can we employ it in studies of moral education?: With practical guidelines to use JASP for educators and researchers

ABSTRACT

In this article, we discuss the benefits of Bayesian statistics and how to utilize them in studies of moral education. To demonstrate concrete examples of the applications of Bayesian statistics to studies of moral education, we reanalyzed two data sets previously collected: one small data set collected from a moral educational intervention experiment, and one big data set from a large-scale Defining Issues Test-2 survey (DIT). The results suggest that Bayesian analysis of data sets collected from moral educational studies can provide additional useful statistical information, particularly that associated with the strength of evidence supporting alternative hypotheses, which has not been provided by the classical frequentist approach focusing on P-values. Finally, we introduce several practical guidelines pertaining to how to utilize Bayesian statistics, including the utilization of newly developed free statistical software, Jeffrey’s Amazing Statistics Program (JASP), and thresholding based on Bayes Factors (BF), to scholars in the field of moral education.

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KEYWORDS:

• Bayesian statistics
• Bayes Factor (BF)
• P-values
• statistical analysis
• Jeffrey’s Amazing Statistics Program (JASP)

Acknowledgements

The authors thank Maarten Marsman for assistance in data analysis.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. These were items found by using a keyword ‘Bayesian’ from JME: Derryberry and Thoma (2005), Heng, Blau, Fulmer, Bi, and Pereira (2017), Lee, Padilla-Walker, and Nelson (2015), and McGrath and Walker (2016).

2. This article demonstrates the result of Bayesian path analysis examining how motivational climate, basic psychological need, and moral disengagement influence antisocial and prosocial behavior in sport (Hodge & Gucciardi, 2015).

3. First, Kondo (1990) simulated the Bayesian Prisoner Dilemma game to model rational behavior, normative behavior, moral behavior, and cooperation. Second, Walker, Gustafson, and Hennig (2001) analyzed the consolidation and transition model in the development of moral reasoning measured by the Moral Judgment Interview with Bayesian techniques. Third, Walker, Gustafson, and Frimer (2007) overviewed benefits of Bayesian analysis and how to apply it in developmental psychology to address several methodological issues. Fourth, Railton's article (2017) discussed how moral learning occurs based on Bayesian perspective.

Additional information

Notes on contributors

Hyemin Han

Hyemin Han is an assistant professor in educational psychology and educational neuroscience at the University of Alabama. His research interests include moral development, moral education, social neuroscience, and computational modeling.

Joonsuk Park

Joonsuk Park is a graduate student in quantitative psychology at the Ohio State University. His research interests are mathematical psychology, Bayesian modeling, and research methodology. 

Stephen J. Thoma

Stephen J. Thoma is University Professor and Program Coordinator of Educational Psychology at the University of Alabama. His specialty area ispersonality and social development in late adolescence and youthwith a focus on moral judgment development.