Although using machine learning for predicting which students are at risk of failing a course is indeed valuable, how can we identify which characteristics of individual students contribute to their being At-Risk? By characterising individual At-Risk students we could potentially advise on specific interventions or ways to reduce their probability…

High-quality single-case design research should include measures that assess the social significance of intervention goals, the social importance of intervention outcomes, and the acceptability and feasibility of procedures. We conducted a systematic review to examine the inclusion and use of social validity metrics in academic and behavioral…

Rapid automatized naming (RAN) has surged in popularity recently as an important indicator of reading difficulties, including dyslexia. Despite an extensive history of research on RAN, including recent meta-analyses indicating a unique contribution of RAN to reading above and beyond phonemic awareness, questions remain regarding RAN's relationship…

This paper investigates the student dropout phenomenon in a technical Italian university from a time-to-event perspective. Shared frailty Cox time-dependent models are applied to analyse the careers of students enrolled in different engineering programs with the aim of identifying the determinants of student dropout through time, predicting the…

Early warning systems (EWS) using analytical tools that have been trained against prior years' data, can reliably predict dropout risk in individual students so that educators may intervene early to help avert this from happening. Risk profiles for dropouts aren't always useful since students often do not conform to the profiles. Researchers with…

The use of brief dyslexia rating scales is increasing given current dyslexia legislation efforts across the United States. The purpose of this article is to provide an overview of the historical context of the use of brief dyslexia rating scales, strengths, and limitations of using these measures, criteria for selecting these measures, and a…

Danish schools offering "preparatory basic education and training" (FGU schools) have students that are characterized by having different academic, social, or personal problems. In addition, many FGU students are at high risk of suicidal behavior. Many young people with suicide behavior do not seek help and early identification is…

The Great Mountain High School (GMHS) started a program to help support students at risk for not graduating high school. The focus of this study was to provide a formative program evaluation of the created program that (a) investigated the fidelity of implementation of the activities and processes of the program, (b) gathered an understanding of…

The present study explored the correlation between different types of stress (acute and chronic) and the influence of their negative emotional manifestations on delinquent tendencies in adolescent students. Within the framework of the general strain theory, the study aims to analyse the intermediary role of depression in the relationship between…

This study helps improve the early prediction of student performance by RNN-FitNets, which applies knowledge distillation (KD) to the time series direction of the recurrent neural network (RNN) model. The RNN-FitNets replaces the teacher model in KD with "an RNN model with a long-term time-series in which the features during the entire course…

This study will examine the first-to-second-year college persistence of students who graduated from Fort Worth Independent School District (FWISD) in the class of 2018. The study seeks to understand how the attainment of college readiness indicators correlates with college persistence in two categories of students, resourced and under-resourced.…

Stemmed from zero-tolerance policies, Disciplinary Alternative Education Programs/Classrooms (DAEPs) in Texas are disciplinary spaces designed to house students deemed at risk, while schools continue to serve students' educational needs of (Aron 2006, Tajalli & Garba, 2014). Once there, students are stereotyped with analogous carceral-framed…

The purpose of this study was to determine changes noted in at-risk students following the implementation of at-risk students of all ages. The study assessed the impact of mentorship on at-risk students' behavior, confidence, and self-efficacy. Qualitative and quantitative analyses were examined, and pre- and post-data were collected and analyzed.…

Virtual Reality (VR) has been found useful to improve engagement and retention level of students, for some topics, compared to traditional learning tools such as books, and videos. However, a student could still get distracted and disengaged due to a variety of factors including stress, mind-wandering, unwanted noise, external alerts, and internal…

Colleges are increasingly turning to predictive analytics to identify "at-risk" students in order to target additional supports. While recent research demonstrates that the types of prediction models in use are reasonably accurate at identifying students who will eventually succeed or not, there are several other considerations for the…