Post-secondary educational outcomes for care-experienced youth are poor. This has been a consistent finding across studies in many countries. Most studies do not distinguish between different types of post-secondary educational pathways and outcomes, however. There has been limited attention to the potential for post-secondary vocational education…

Results of a Principal Investigators Programmatic Data Inventory (PDI) of a National Science Foundation Robert Noyce Track Four project are discussed in this paper. The PDI results shed light on the development of STEM teacher scholars as they progress through the programs and of the qualifications and procedures of the application process. The…

A significant body of recent research in the field of Learning Analytics has focused on leveraging machine learning approaches for predicting at-risk students in order to initiate timely interventions and thereby elevate retention and completion rates. The overarching feature of the majority of these research studies has been on the science of…

This paper applies the well-known cognitive bias of loss aversion from behavioural economics to student decisions over engagement with mathematically demanding coursework. This bias is shown to predict behaviour that is consistent with mathematics anxiety in a dynamic model of student engagement. It is shown that these forces can imply…

This study examined the effect of dual enrollment (DE) on college enrollment and degree completion for students with lower prior academic achievement who attended public high schools in Texas. We employed a propensity score matching method to reduce selection bias arising from DE participation and supplemented the analysis with a bounds test. The…

First graders with Developmental Language Disorder are considered at risk for exhibiting Specific Learning Disorder during school years. They also have deficiencies in their metacognitive skills, which leads to less effective learning processes. The current study examined, for the first time, the added value of various types of metacognitive…

The author focuses on positive psychology as an important approach to supporting the psychological well-being of students with gifts and talents. Research has identified protective factors that can counteract risk factors for suicidal behavior. These protective factors may be found within the individual, the family, peers, the school, the…

Background: Although most engineering graduate students are funded and usually complete their degrees faster than other disciplines, attrition remains a problem in engineering. Existing research has explored the psychological and sociological factors contributing to attrition but not the structural factors impacting attrition. Purpose/Hypothesis:…

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…