Search

Although some previous studies have investigated the relationship between moral foundations and moral judgment development, the methods used have not been able to fully explore the relationship. In the present study, we used Bayesian Model Averaging (BMA) in order to address the limitations in traditional regression methods that have been used previously. Results showed consistency with previous findings that binding foundations are negatively correlated with post-conventional moral reasoning and positively correlated with maintaining norms and personal interest schemas. In addition to previous studies, our results showed a positive correlation for individualizing foundations and post-conventional moral reasoning. Implications are discussed as well as a detailed explanation of the novel BMA method in order to allow others in the field of moral education to be able to use it in their own studies.

Having an agreed-upon definition of character education would be useful for both researchers and practitioners in the field. However, even experts in character education disagree on how they would define it. We attempted to achieve greater conceptual clarity on this issue through a prototype analysis in which the features perceived as most central to character education were identified. In Study 1 (N = 77), we asked character education experts to enumerate features of character education. Based on these lists, we identified 30 features. In Study 2 (N = 101), experts assessed which features were central to character education through a categorization task. In Study 3 (N = 166), we assessed the extent of centrality using scalar items. We conclude by offering practical advice for the development of future character education studies and programs rooted in what is deemed central to such programs.

We examined the links between moral identity--the centrality of moral principles to identity--and political purpose during emerging adulthood. We analyzed data from two waves of a longitudinal study of civic purpose. T1 surveys were collected before high school graduation, and T2 surveys were collected 2 years later. We categorized people (N = 1,578 at T1 and N = 480 at T2) into political purpose groups based on the person-centered perspective and then performed a multinomial logistic regression analysis to test whether moral identity was associated with categories of political purpose. The findings from our study indicate that moral identity at T1 is linked with the maintenance and formation of T2 political purpose.

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.

We developed and tested a behavioral version of the Defining Issues Test-1 revised (DIT-1r), which is a measure of the development of moral judgment. We conducted a behavioral experiment using the behavioral Defining Issues Test (bDIT) to examine the relationship between participants' moral developmental status, moral competence, and reaction time when making moral judgments. We found that when the judgments were made based on the preferred moral schema, the reaction time for moral judgments was significantly moderated by the moral developmental status. In addition, as a participant becomes more confident with moral judgment, the participant differentiates the preferred versus other schemas better particularly when the participant's abilities for moral judgment are more developed.

The extent to which individuals with a variety of cultural backgrounds differ in empathic responsiveness is unknown. This article describes the differences in trait empathy in one independent and one interdependent society (i.e., the US and Iran, respectively). The analysis of data collected from self-reported questionnaires answered by 326 adults indicated a significant difference in the cognitive component of empathy concerning participants' affiliation to either egocentric or socio-centric society: Iranian participants with interdependent cultural norms, reported higher cognitive empathy compared to American participants who share independent cultural norms. In line with previous studies, gender differences were observed in all subscales of questionnaires, except the Empathy Quotient (EQ). Female participants demonstrated more empathy than males in both samples. Implications for understanding the cross-cultural differences of various components of empathy are discussed.

In the present study, I developed and tested an R module to explore the best models within the context of multilevel modeling in research in public health. The module that I developed, explore.models, compares all possible candidate models generated from a set of candidate predictors with information criteria, Akaike information criterion (AIC), and Bayesian information criterion (BIC), with multiprocessing. For testing, I ran explore.models with datasets analyzed in three previous studies in public health, which assumed candidate models with different degrees of model complexity. These three studies examined the predictors of psychological well-being, compliance with preventive measures, and vaccine intent during the COVID-19 pandemic. After conducting model exploration with explore.models, I cross-validated the nomination results with calculated model Bayes Factors to examine whether the model exploration was performed accurately. The results suggest that explore.models using AIC and BIC can nominate best candidate models and such nomination outcomes are supported by the calculated model Bayes Factors. In particular, all the identified models are superior to the full models in terms of model Bayes Factors. Also, by employing AIC and BIC with multiprocessing, explore.models requires a shorter processing time than model Bayes Factor calculations. These results indicate that explore.models is a reliable, valid, and feasible tool to conduct data-driven model exploration with datasets collected from multiple groups in research on health psychology and education. [ABSTRACT FROM AUTHOR]

Measurement alignment adjusts factor loadings and intercepts across different groups to achieve measurement invariance, which assumes the equal measurement model is validated across different groups. It should be achieved for validly conducting analysis and comparison in studies involving multiple groups, such as cross‐cultural or cross‐national studies. In this paper, I presented how to conduct measurement alignment with R. In addition to measurement alignment, I explained how to perform the Monte Carlo simulation to test the consistency and validity of alignment results and factor score calculation to facilitate further statistical analysis. A tutorial R code that implements all described procedures is freely shared via GitHub to inform readers who intend to use the alignment technique in their research projects. [ABSTRACT FROM AUTHOR]

In the present study, we examined how the perceived attainability and relatability of moral exemplars predicted moral elevation and pleasantness among both adult and college student participants. Data collected from two experiments were analyzed with Bayesian multilevel modeling to explore which factors significantly predicted outcome variables at the story level. The analysis results demonstrated that the main effect of perceived relatability and the interaction effect between attainability and relatability shall be included in the best prediction model, and thus, were deemed to predict the outcome variables significantly. The main effect of relatability as well as its interaction with attainability positively predicted elevation and pleasantness. We discussed educational implications of the findings in terms of how relatability may be the first point of emphasis for moral educators to focus on and attainability can then bolster the effectiveness. These relatable and attainable moral exemplars can be sources for moral elevation and pleasantness, which promote motivation to emulate moral behavior presented by the exemplars. [ABSTRACT FROM AUTHOR]

The present study aimed to examine how to improve the effectiveness of moral exemplar-applied interventions based on the pillars of the self-determination theory framework, autonomy, competence, and relatedness. Past research has mainly focused on the relatedness and attainability of moral exemplars for predicting motivation outcomes. The data for this study consisted of synthesized data sets from previous studies examining the motivational impacts of distinct moral exemplars and intervention methods. The main syntheses for these data sets used multilevel modeling focusing on relatability, attainability, and intervention methods, corresponding to relatedness, competence, and autonomy in the self-determination theory, respectively, as predictors. In general, there was a significant interaction effect between the attainability or relatability, and the intervention method. Autonomous instruction methods, which support autonomy, were demonstrated to boost motivational outcomes. Implications from this study support the employment of self-determination theory to examine the use of moral exemplars in moral education and were consistent with previous exemplar studies. [ABSTRACT FROM AUTHOR]

This study is a comparative analysis of the characteristics of moral exemplars presented in moral education textbooks in Korea and Japan. The purpose of the study is to examine and compare moral values presented through the lives and stories of moral exemplars in the two countries that have moral education as an independent and separate subject based on the national curriculum. To this end, the study uses analytical criteria such as gender, nationality, social roles, historical backgrounds, and specific moral values in order to investigate characteristics of 307 moral exemplars in Korea's and Japan's most used moral education textbooks. The results show significant similarities and differences in moral exemplars between the two nations. In the case of the similarities, both countries emphasize moral autonomy and respect for human life. In the case of the differences, while Korea presents more historic figures as moral exemplars, Japan presents more students and ordinary people as moral exemplars.

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.

In the present study, I explore the relationship between purpose, which was measured by the Claremont Purpose Scale, and moral psychological indicators, moral reasoning, moral identity, and empathy. Purpose was quantified in terms of three subcomponents: meaning, goal, and beyond-the-self motivation. Moral reasoning was assessed in terms of utilization of postconventional moral reasoning. Moral identity was examined with two subscales: moral internalization, and symbolization. Among diverse subscales of empathy, I focused on empathic concern and perspective taking, which have been reported to be strongly related to morality. To explore the best prediction models using the data, I employed Bayesian Model Selection and Bayesian regression analysis. In general, purpose was significantly predicted by most surveyed moral psychological indicators but not by moral symbolization. The best prediction model for beyond-the-self motivation included the most moral psychological indicator predictors including moral reasoning, which did not significantly predict other dependent variables. [ABSTRACT FROM AUTHOR]

This study investigated the effects of internal and demographic variables on civic development in late adolescence using the construct "civic purpose." We conducted surveys on civic engagement with 480 high school seniors, and surveyed them again 2 years later. Using multivariate regression and linear mixed models, we tested the main effects of civic purpose dimensions (beyond-the-self motivation, future civic intention), ethnicity, and education on civic development from Time 1 to Time 2. Results showed that while there is an overall decrease in civic engagement in the transition out of high school, both internal and social factors protected participants from steep civic decline. Interaction effects varied. Ethnicity and education interacted in different ways with the dimensions of civic purpose to predict change in traditional and expressive political engagement, and community service engagement.

The present study meta-analyzed 45 experiments with 959 subjects and 463 activation foci reported in 43 published articles that investigated the neural mechanism of moral functions by comparing neural activity between the moral task conditions and non-moral task conditions with the Activation Likelihood Estimation method. The present study examined the common activation foci of morality-related task conditions. In addition, the study compared the neural correlates of moral sensitivity with the neural correlates of moral judgment, which are the two functional components in the Neo-Kohlbergian model of moral functioning. The results showed that brain regions associated with the default mode network were significantly more active during morality-related task conditions than during non-morality task conditions. These brain regions were also commonly activated in both moral judgment and moral sensitivity task conditions. In contrast, the right temporoparietal junction and supramarginal gyrus were found to be more active only during conditions of moral judgment. These findings suggest that the neural correlates of moral sensitivity and moral judgment are perhaps commonly associated with brain circuitries of self-related psychological processes, but the neural correlates of those two functional components are distinguishable from each other.