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…

While foster youth miss more school versus their non-foster counterparts, their status as a foster youth is not static, with many of them entering and exiting the foster care system over time. These dynamics of entry and exit can represent particularly crucial transition periods of stability and instability that may differentially influence…

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…

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:…

Oral reading fluency (ORF) assessments are commonly used to screen at-risk readers and evaluate interventions' effectiveness as curriculum-based measurements. Similar to the standard practice in item response theory (IRT), calibrated passage parameter estimates are currently used as if they were population values in model-based ORF scoring.…

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…

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 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…

Unaddressed social, emotional, and behavioral (SEB) needs and academic challenges may lead to negative youth outcomes. Universal behavioral risk screeners, like the student self-report Social, Academic, and Emotional Behavior Risk Screener (SAEBRS-SRS), identify at-risk students. To improve screening tool use, research is needed to identify the…