Understanding software modelers' difficulties and evaluating their performance is crucial to Model-Driven Engineering (MDE) education. The software modeling process contains fine-grained information about the modelers' analysis and thought processes. However, existing research primarily focuses on identifying obvious issues in the software…

Due to the pandemic, the world's dependence shifted to online platforms. It has made all age groups vulnerable to cyberbullying. Now more than ever, there is a need for online behavior monitoring. Existing algorithms tend to classify friendly banter as cyberbullying. They make use of binary classification by identifying offensive keywords. The…

The ability to reach a large number of users on social networking sites makes it easy for anyone to be exposed to a phenomenon known as cyberbullying. To address this issue, researchers have proposed different classification models for the automatic detection of cyberbullying using machine learning. Yet, the state of incidents related to…

Research and policy reports estimate that 10%-40% of U.S. children and adolescents currently have or very recently have had at least one significant mental health condition. Students who exhibit substantial behavior and emotional problems in school often show less severe problems when younger. Screening for less severe problems at younger ages can…

Purpose: We aimed to create a comprehensive understanding of the dilemmas involved in the diagnosis of developmental language disorder (DLD) and to highlight the potential of a multidimensional spectral account of DLD for addressing these dilemmas. Method: We conducted an integrative literature review. Conclusions: Considerable gains in…

In scholarly research, racial categories are typically taken for granted. However, race categories vary over time and geography and reflect the social beliefs of the people who use them. Informed by quantitative critical race theory analysis, we interrogate how race categories align (or not) with 24,000 U.S. higher education students' responses to…

Autism spectrum disorder (ASD) is characterized by impairments in many functional areas requiring long-term interventions to promote autonomy. This study aims to map The Sensory Profile™ 2 (SP-2), one of the most widely used assessment tools in children with ASD, with the International Classification of Functioning, Disability and Health for…

This study investigates the prevalence and distribution of special educational needs and disabilities (SEND) among left-behind (LB) and non-left-behind (non-LB) children in rural China, adopting the UK's broader SEND framework to address the limitations of China's current classification system. Using quantitative data collected from 17 primary…

Student evaluations of teaching (SET) act as the primary means to gauge instructor effectiveness. Likewise, SETs provide the primary qualitative feedback to instructors via student comments. However, mostly students with strong feelings tend to write comments. Among the most recallable are toxic comments: comments that are unhelpful/hurtful in…

Preschool children considered at risk for future reading difficulties experience unique and complex combinations of risk factors. In this exploratory study, we used latent profile analysis (LPA) to investigate the underlying classifications of children identified as at-risk for reading difficulties (N = 281) along selected cognitive,…

Preschool children considered at risk for future reading difficulties experience unique and complex combinations of risk factors. In this exploratory study, we used latent profile analysis (LPA) to investigate the underlying classifications of children identified as at-risk for reading difficulties (N = 281) along selected cognitive,…

The Poor Comprehender (PC) reading profile is characterised by difficulty comprehending text despite age-appropriate decoding skills. Risk for this profile is typically identified through static screening instruments measuring pre-existing knowledge, which may produce biased estimates for culturally and linguistically diverse children. In…

Behavioral and emotional disorders in childhood can have lasting impacts in areas such as education and future employment, often extending into adulthood. Identifying the potential disorders in children's early grades is beneficial to provide proactive assistance. In this study, we employed a well-validated scale - the Strengths and Difficulties…

This study explores machine learning (ML) approaches for identifying gifted students by integrating academic and socioemotional characteristics from the data collected with the Having Opportunities Promotes Excellence teacher rating scale. By using the Gaussian Mixture Model (GMM) and ML approaches, including support vector machine (SVM) and…

It is very important to identify talented students as soon as they are admitted to college so that appropriate resources are provided and allocated to them to optimize and excel in their education. Currently, this process is labor-intensive and time-consuming, as it involves manual reviews of each student's academic record. This raises the…