Early identification of student success is crucial for enabling timely interventions, reducing dropout rates, and promoting on-time graduation. In educational settings, AI-powered systems have become essential for predicting student performance due to their advanced analytical capabilities. However, effectively leveraging diverse student data to…

This study explores the use of webcam-based eye tracking during a learning task to predict and better understand neurodivergence with the aim of improving personalized learning to support diverse learning needs. Using WebGazer, a webcam-based eye tracking technology, we collected gaze data from 354 participants as they engaged in educational…

The development of science and technology without individual environmental awareness has led to a decline in environmental quality. This issue can be addressed by enhancing environmental literacy, which includes ecological knowledge, cognitive skills, environmental attitudes, and behaviors. In practice, the question arises as to whether knowledge…

Purpose: Children with congenital hearing loss (HL) have auditory impairments that may place them at increased risk for delays or variability in language development. However, obtaining reliable brain markers for early classification of young children with HL versus those with normal hearing (NH), as well as for precise assessment of HL children's…

Community colleges often employ measures to determine student course placement. Though much research has examined the predictive validity of placement measures such as ACT or high-school GPA, little research examines the effects of students' traditional and non-traditional status. Using data from a rural state community college, we examined the…

This research report is on fostering young children's metacognitive skills. The study was conducted at a private early childhood education center in a Midwestern city in the United States in 2020. The design of the study was a mixed approach including Time Series experimentation, naturalistic observation, and interviews. Children aged 3-4 years…

Learning style recognition is an indispensable part of achieving personalized learning in online learning systems. The traditional inventory method for learning style identification faces the limitations such as subject and static characteristics. Therefore, an automatic and reliable learning style recognition mechanism is designed in this…

Background: Income inequality is theorized to impact health. However, evidence among adolescents is limited. This study examined the association between income inequality and health-related school absenteeism (HRSA) in adolescents. Methods: Participants were adolescents (n = 74,501) attending secondary schools (n = 136) that participated in the…

Despite recent methodological advances in saturation, guidelines for its estimation in more complex research designs--such as ethnographic studies--have been lacking. We present an accessible, step-by-step approach to empirical assessment of data saturation, tested on a moderately sized ethnographic study with 109 combined direct observations and…

Teaching Institutions could benefit from Early Warning Systems to identify at-risk students before learning difficulties affect the quality of their acquired knowledge. An Early Warning System can help preemptively identify learners at risk of dropping out by monitoring them and analyzing their traces to promptly react to them so they can continue…

Model evaluation is a crucial step in SEM, consisting of two broad areas: global and local fit, where local fit indices are use to modify the original model. In the modification process, the modification index (MI) and the standardized expected parameter change (SEPC) are used to select the parameters that can be added to improve the fit. The…

Existing systems for automating the assessment of risk-of-bias (RoB) in medical studies are supervised approaches that require substantial training data to work well. However, recent revisions to RoB guidelines have resulted in a scarcity of available training data. In this study, we investigate the effectiveness of generative large language…

Background: Perceptual and speech production abilities of children with cochlear implants (CIs) are usually tested by word and sentence repetition or naming tests. However, these tests are quite far apart from daily life linguistic contexts. Aim: Here, we describe a way of investigating the link between language comprehension and anticipatory…

Whether machine learning algorithms effectively predict college students' course outcomes using learning management system data is unknown. Identifying students who will have a poor outcome can help institutions plan future budgets and allocate resources to create interventions for underachieving students. Therefore, knowing the effectiveness of…

The capacity of families with autistic children to demonstrate resilience is a notable strength that has received little attention in the literature. A potential predictor of family resilience in households with autistic youth is neighborhood support. This study examined the relationship between neighborhood support and family resilience in…