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 Lognormal Response Time (LNRT) model measures the speed of test-takers relative to the normative time demands of items on a test. The resulting speed parameters and model residuals are often analyzed for evidence of anomalous test-taking behavior associated with fast and poorly fitting response time patterns. Extending this model, we…

The overriding aim of this study was to conduct a side-by-side comparative evaluation of two online suicide prevention gatekeeper-training programs: Question, Persuade, Refer (QPR) and Making Educators Partners in Youth Suicide Prevention (MEP). Specific aims included identifying program components, instructional methods, and technology elements…

Although cyber victimization has been suggested as a significant risk factor for the development of adolescents' depression, the underlying psychopathological process that mediates this relationship needs further exploration. Based on the psychological inflexibility model, this study aimed to examine cognitive fusion and experiential avoidance as…

The full implementation of MOOCs in online education offers new opportunities for integrating multidisciplinary and comprehensive STEM education. It facilitates the alignment between online learning content and learning behaviors. However, it also presents new challenges, such as a high rate of STEM dropouts. Many learners struggle to establish…

General principles of human cognition can help to explain why languages are more likely to have certain characteristics than others: structures that are difficult to process or produce will tend to be lost over time. One aspect of cognition that is implicated in language use is working memory--the component of short-term memory used for temporary…

The emergence of sophisticated AI tools such as ChatGPT, coupled with the transition to remote delivery of educational assessments in the COVID-19 era, has led to increasing concerns about academic integrity and test security. Using AI tools, test takers can produce high-quality texts effortlessly and use them to game assessments. It is thus…

Deconversion is a biographical change in which one goes from claiming adherence to a religion to departing from it. A meaning system model can help us understand the processes through which deconversion occurs. Drawing on that framework, we explored how perceiving hypocrisy in one's religious setting influences adolescent deconversion. Irrational…

With the advancements in technology and the growing demand for online education, Virtual Learning Environments (VLEs) have experienced rapid development in recent years. This demand was especially evident during the COVID-19 pandemic. The incorporation of new technologies in VLEs provides new opportunities to better understand the behaviors of…

In relational event networks, the tendency for actors to interact with each other depends greatly on the past interactions between the actors in a social network. Both the volume of past interactions and the time that has elapsed since the past interactions affect the actors' decision-making to interact with other actors in the network. Recently…

Objective: We offer an overview of ADHD research using mouse models of nicotine exposure. Method: Nicotine exposure of C57BL/6 or Swiss Webster mice occurred during prenatal period only or during the prenatal and the preweaning periods. Behavioral, neuroanatomical and neurotransmitter assays were used to investigate neurobiological mechanisms of…

Technology-enhanced learning supported by virtual learning environments (VLEs) facilitates tutors and students. VLE platforms contain a wealth of information that can be used to mine insight regarding students' learning behaviour and relationships between behaviour and academic performance, as well as to model data-driven decision-making. This…

We propose a novel model, Wide & Deep Item Response Theory (Wide & Deep IRT), to predict the correctness of students' responses to questions using historical clickstream data. This model combines the strengths of conventional Item Response Theory (IRT) models and Wide & Deep Learning for Recommender Systems. By leveraging clickstream…

The purposes of this study were to explore students' learning performance, knowledge construction, and behavioral patterns in computer-supported collaborative learning (CSCL) online discussions with/without using Form+Theme+Context (FTC) model guidance scaffolding in visual imagery education. In the online learning activities, the control group…