Research and Publications - Department of Educational Studies in Psychology, Research Methodology, and Counseling

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Moral reasoning and moral competence as predictors of cooperative behavior in a social dilemma
(Nature Portfolio, 2023) Miranda-Rodriguez, Ruben Andres; Leenen, Iwin; Han, Hyemin; Palafox-Palafox, German; Garcia-Rodriguez, Georgina; Universidad Nacional Autonoma de Mexico; University of Alabama Tuscaloosa
The level of moral development may be crucial to understand behavior when people have to choose between prioritizing individual gains or pursuing general social benefits. This study evaluated whether two different psychological constructs, moral reasoning and moral competence, are associated with cooperative behavior in the context of the prisoner's dilemma game, a two-person social dilemma where individuals choose between cooperation or defection. One hundred and eighty-nine Mexican university students completed the Defining Issues Test (DIT-2; measuring moral reasoning) and the Moral Competence Test (MCT) and played an online version of the prisoner's dilemma game, once against each participant in a group of 6-10 players. Our results indicate that cooperative behavior is strongly affected by the outcomes in previous rounds: Except when both participants cooperated, the probability of cooperation with other participants in subsequent rounds decreased. Both the DIT-2 and MCT independently moderated this effect of previous experiences, particularly in the case of sucker-outcomes. Individuals with high scores on both tests were not affected when in previous rounds the other player defected while they cooperated. Our findings suggest that more sophisticated moral reasoning and moral competence promote the maintenance of cooperative behaviors despite facing adverse situations.
Moral growth mindset is associated with change in voluntary service engagement
(PLOS, 2018) Han, Hyemin; Choi, Youn-Jeng; Dawson, Kelsie J.; Jeong, Changwoo; University of Alabama Tuscaloosa; Seoul National University (SNU)
Incremental implicit theories are associated with a belief regarding it is possible to improve one's intelligence or ability through efforts. Previous studies have demonstrated that incremental implicit theories contributed to better academic achievement and positive youth development. Our study aimed to examine whether incremental implicit theories of morality significantly influenced change in students' engagement in voluntary service activities. In our study, 54 Korean college students for Study 1 and 180 Korean 8th graders for Study 2 were recruited to conduct two two-wave studies. We surveyed participants' implicit theories of morality and participation in voluntary service activities. The effect of implicit theories of morality on change in service engagement was analyzed through regression analysis. In Study 1, the moral growth mindset significantly moderated longitudinal change in service engagement. In Study 2, the moral growth mindset significantly influenced engagement in art-related activities, while it significantly moderated change in engagement in youth-related activities.
A method to adjust a prior distribution in Bayesian second-level fMRI analysis
(PeerJ, 2021) Han, Hyemin; University of Alabama Tuscaloosa
Previous research has shown the potential value of Bayesian methods in fMRI (functional magnetic resonance imaging) analysis. For instance, the results from Bayes factor-applied second-level fMRI analysis showed a higher hit rate compared with frequentist second-level fMRI analysis, suggesting greater sensitivity. Although the method reported more positives as a result of the higher sensitivity, it was able to maintain a reasonable level of selectivity in term of the false positive rate. Moreover, employment of the multiple comparison correction method to update the default prior distribution significantly improved the performance of Bayesian second-level fMRI analysis. However, previous studies have utilized the default prior distribution and did not consider the nature of each individual study. Thus, in the present study, a method to adjust the Cauchy prior distribution based on a priori information, which can be acquired from the results of relevant previous studies, was proposed and tested. A Cauchy prior distribution was adjusted based on the contrast, noise strength, and proportion of true positives that were estimated from a meta-analysis of relevant previous studies. In the present study, both the simulated images and real contrast images from two previous studies were used to evaluate the performance of the proposed method. The results showed that the employment of the prior adjustment method resulted in improved performance of Bayesian second-level fMRI analysis.
Stages of moral judgment development: Applying item response theory to Defining Issues Test data
(Routledge, 2018) van den Enden, Thijs; Boom, Jan; Brugman, Daniel; Thoma, Stephen; Utrecht University; University of Alabama Tuscaloosa
The Defining Issues Test (DIT) has been the dominant measure of moral development. The DIT has its roots in Kohlberg?s original stage theory of moral judgment development and asks respondents to rank a set of stage typed statements in order of importance on six stories. However, the question to what extent the DIT-data match the underlying stage model was never addressed with a statistical model. Therefore, we applied item response theory (IRT) to a large data set (55,319 cases). We found that the ordering of the stages as extracted from the raw data fitted the ordering in the underlying stage model good. Furthermore, difficulty differences of stages across the stories were found and their magnitude and location were visualized. These findings are compatible with the notion of one latent moral developmental dimension and lend support to the hundreds of studies that have used the DIT-1 and by implication support the renewed DIT-2.
An Embodied Approach to Understanding: Making Sense of the World Through Simulated Bodily Activity
(Frontiers Media, 2016) Soylu, Firat; University of Alabama Tuscaloosa
Even though understanding is a very widely used concept, both colloquially and in scholarly work, its definition is nebulous and it is not well-studied as a psychological construct, compared to other psychological constructs like learning and memory. Studying understanding based on third-person (e.g., behavioral, neuroimaging) data alone presents unique challenges. Understanding refers to a first-person experience of making sense of an event or a conceptual domain, and therefore requires incorporation of multiple levels of study, at the first-person (phenomenological), behavioral, and neural levels. Previously, psychological understanding was defined as a form of conscious knowing. Alternatively, biofunctional approach extends to unconscious, implicit, automatic, and intuitive aspects of cognition. Here, to bridge these two approaches an embodied and evolutionary perspective is provided to situate biofunctional understanding in theories of embodiment, and to discuss how simulation theories of cognition, which regard simulation of sensorimotor and affective states as a central tenet of cognition, can bridge the gap between biofunctional and psychological understanding.
Researching for Better Instructional Methods Using AB Experiments in MOOCs: Results and Challenges
(2016) Chen, Zhongzhou; Chudzicki, Christopher; Palumbo, Daniel; Alexandron, Giora; Choi, Youn-Jeng; Zhou, Qian; Pritchard, David E.; University of Alabama Tuscaloosa
We conducted two AB experiments (treatment vs. control) in a massive open online course. The first experiment evaluates deliberate practice activities (DPAs) for developing problem solving expertise as measured by traditional physics problems. We find that a more interactive drag-and-drop format of DPA generates quicker learning than a multiple choice format but DPAs do not improve performance on solving traditional physics problems more than normal homework practice. The second experiment shows that a different video shooting setting can improve the fluency of the instructor which in turn improves the engagement of the students although it has no significant impact on the learning outcomes. These two cases demonstrate the potential of MOOC AB experiments as an open-ended research tool but also reveal limitations. We discuss the three most important challenges: wide student distribution, “open-book” nature of assessments, and large quantity and variety of data. We suggest possible methods to cope with those.
Exploring student understanding of the engineering design process using distractor analysis
(Springer, 2019) Wind, Stefanie A.; Alemdar, Meltem; Lingle, Jeremy A.; Moore, Roxanne; Asilkalkan, Abdullah; University of Alabama Tuscaloosa; University System of Georgia; Georgia Institute of Technology
Typical approaches to assessing students' understanding of the engineering design process (EDP) include performance assessments that are time-consuming to score. It is also possible to use multiple-choice (MC) items to assess the EDP, but researchers and practitioners often view the diagnostic value of this assessment format as limited. However, through the use of distractor analysis, it is possible to glean additional insights into student conceptualizations of complex concepts. Using an EDP assessment based on MC items, this study illustrates the value of distractor analysis for exploring students' understanding of the EDP. Specifically, we analyzed 128 seventh grade students' responses to 20 MC itemsusing a distractor analysis technique based on Rasch measurement theory. Our results indicated that students with different levels of achievement have substantively different conceptualizations of the EDP, where there were different probabilities for selecting various answer choices among students with low, medium, and high relative achievement. We also observed statistically significant differences (p<0.05) in student achievement on several items when we analyzed the data separately by teacher. For these items, we observed different patterns of answer choice probabilities in each classroom. Qualitative results from student interviews corroborated many of the results from the distractor analyses. Together, these results indicated that distractor analysis is a useful approach to explore students' conceptualization of the EDP, and that this technique provides insight into differences in student achievement across subgroups. We discuss the results in terms of their implications for research and practice.
Efficient, helpful, or distracting? A literature review of media multitasking in relation to academic performance
(Springer, 2018) May, Kaitlyn E.; Elder, Anastasia D.; University of Alabama Tuscaloosa; Mississippi State University
Media multitasking, using two or more medias concurrently, prevails among adolescents and emerging adults. The inherent mental habits of media multitasking-dividing attention, switching attention, and maintaining multiple trains of thought-have significant implications and consequences for students' academic performance. The goal of this review is to synthesize research on the impacts of media multitasking on academic performance. The research indicates that media multitasking interferes with attention and working memory, negatively affecting GPA, test performance, recall, reading comprehension, note-taking, self-regulation, and efficiency. These effects have been demonstrated during in-class activities (largely lectures) and while students are studying. In addition, students struggle to accurately assess the impact media multitasking will have on their academic performance. Further research should attend to understanding effects of media multitasking in more diverse instructional contexts and for varied academic tasks. Fostering students' self-regulation around media multitasking is a promising area for future efforts towards improving academic performance of college students.
GDINA: An R Package for Cognitive Diagnosis Modeling
(American Statistical Association, 2020-05-09) Ma, Wenchao; de la Torre, Jimmy; University of Alabama Tuscaloosa; University of Hong Kong
Cognitive diagnosis models (CDMs) have attracted increasing attention in educational measurement because of their potential to provide diagnostic feedback about students' strengths and weaknesses. This article introduces the feature-rich R package GDINA for conducting a variety of CDM analyses. Built upon a general model framework, a number of CDMs can be calibrated using the GDINA package. Functions are also available for evaluating model-data fit, detecting differential item functioning, validating the item and attribute association, and examining classification accuracy. A grapical user interface is also provided for researchers who are less familar with R. This paper contains both technical details about model estimation and illustrations about how to use the package for data analysis. The GDINA package is also used to replicate published results, showing that it could provide comparable model parameter estimation.

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