Introduction The Defining Issues Test (DIT) aimed to measure one's moral judgment development in terms of moral reasoning. The Neo-Kohlbergian approach, which is an elaboration of Kohlbergian theory, focuses on the continuous development of postconventional moral reasoning, which constitutes the theoretical basis of the DIT. However, very few studies have directly tested the internal structure of the DIT, which would indicate its construct validity. Objectives Using the DIT-2, a later revision of the DIT, we examined whether a bi-factor model or 3-factor CFA model showed a better model fit. The Neo-Kohlbergian theory of moral judgment development, which constitutes the theoretical basis for the DIT-2, proposes that moral judgment development occurs continuously and that it can be better explained with a softstage model. Given these assertions, we assumed that the bi-factor model, which considers the Schema-General Moral Judgment (SGMJ), might be more consistent with Neo-Kohlbergian theory. Methods We analyzed a large dataset collected from undergraduate students. We performed confirmatory factor analysis (CFA) via weighted least squares. A 3-factor CFA based on the DIT-2 manual and a bi-factor model were compared for model fit. The three factors in the 3-factor CFA were labeled as moral development schemas in Neo-Kohlbergian theory (i.e., personal interests, maintaining norms, and postconventional schemas). The bi-factor model included the SGMJ in addition to the three factors. Results In general, the bi-factor model showed a better model fit compared with the 3-factor CFA model although both models reported acceptable model fit indices.
Introduction The Defining Issues Test (DIT) aimed to measure one’s moral judgment development in terms of moral reasoning. The Neo-Kohlbergian approach, which is an elaboration of Kohlbergian theory, focuses on the continuous development of postconventional moral reasoning, which constitutes the theoretical basis of the DIT. However, very few studies have directly tested the internal structure of the DIT, which would indicate its construct validity. Objectives Using the DIT-2, a later revision of the DIT, we examined whether a bi-factor model or 3-factor CFA model showed a better model fit. The Neo-Kohlbergian theory of moral judgment development, which constitutes the theoretical basis for the DIT-2, proposes that moral judgment development occurs continuously and that it can be better explained with a soft-stage model. Given these assertions, we assumed that the bi-factor model, which considers the Schema-General Moral Judgment (SGMJ), might be more consistent with Neo-Kohlbergian theory. Methods We analyzed a large dataset collected from undergraduate students. We performed confirmatory factor analysis (CFA) via weighted least squares. A 3-factor CFA based on the DIT-2 manual and a bi-factor model were compared for model fit. The three factors in the 3-factor CFA were labeled as moral development schemas in Neo-Kohlbergian theory (i.e., personal interests, maintaining norms, and postconventional schemas). The bi-factor model included the SGMJ in addition to the three factors. Results In general, the bi-factor model showed a better model fit compared with the 3-factor CFA model although both models reported acceptable model fit indices. Conclusion We found that the DIT-2 scale is a valid measure of the internal structure of moral reasoning development using both CFA and bi-factor models. In addition, we conclude that the soft-stage model, posited by the Neo-Kohlbergian approach to moral judgment development, can be better supported with the bi-factor model that was tested in the present study.
Moral reasoning was investigated with respect to individual characteristics (i.e., education level, political orientation and sex) and school-related (i.e., university/college) factors using multilevel modeling and data mining analysis. We used the multilevel modeling to detect school effects on moral reasoning as well as individual effects for 16,334 students representing 79 different higher education institutions across the U.S. The school-related factors, such as the racial composition, student–faculty ratio, average SAT score, institution type, institutions’ geographical region, frequencies of morally relevant words in college course catalog, college mission and value statements were collected through website searches. Data mining analysis was utilized to extract and calculate the frequencies of morally relevant words from the website content. There were significant effects for the individual characteristic of political orientation. Additionally, all school-related factors were significant. Only main effects were observed for some school-related factors (i.e., average SAT score, institution type, frequency of morally relevant words in mission statements, value statements and course catalogs). For other school-related factors (i.e., the region, student–faculty ratio and racial composition), main effects were also observed; however, these effects were particularly illuminating given their interactions with political orientation. Implications for educational communities are discussed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.