This quantitative study investigates the predictive power of machine learning (ML) models on degree completion among adult learners in higher education, emphasizing the enhancement of data-driven decision-making (DDDM). By analyzing three ML models - Random Forest, Gradient-Boosting machine (GBM), and CART Decision Tree - within a not-for-profit,…

This non-experimental quantitative study utilized linear regression to examine if elementary school counselor and principal relationships predict elementary school counselors' implementation of the American School Counselor Association (ASCA) National Model. The sample (N = 163) included elementary school counselors (n = 108) and principals (n =…

This study leveraged the knowledge and experiences of youth with disabilities, their families, and transition stakeholders to model how the frequency of family engagement activities and services and employment preparation activities and services predict the frequency of youth development activities and services. This information was obtained…

A neurological disorder, along with several behavioral issues, may be to blame for a child's subpar performance in the academic journey (such as anxiety, depression, learning disorders, and irritability). These symptoms can be used to diagnose children with ASD, and supervised machine learning models can help differentiate between ASD traits and…

Having a job immediately after graduation is the dream of every IT graduate. However, not everyone can achieve this outcome. The study's primary goal is to develop predictive models to forecast IT graduates' chances of finding a job based on factors such as academic performance, socioeconomic status, academic habits, and demographic data.…

Traditional letter and number grades are inaccurate and harmful to children, while research indicates that standards-based grading is both more accurate and better for all stakeholders. However, despite standards-based report cards (SBRCs) coming in many forms, the best number and arrangement of performance level descriptors (PLDs) remains…

This quantitative, correlational study aims to determine if a predictive relationship exists between teacher perceptions of Tennessee's teacher evaluation and the linear combination of teacher gender, years of experience, and school-level taught (elementary, middle, high). Although teachers have recognized the current teacher evaluation system,…

Observable data in empirical social and behavioral science studies are often categorical (i.e., binary, ordinal, or nominal). When categorical data are outcomes, they fail to maintain the scale and distributional properties of linear regression and factor analysis. Attempting to estimate model parameters for categorical outcome data with the…

Higher education institutions face heightened accountability for student success. As such, higher education relies heavily on big data to predict student outcomes. This process is problematic because predictive models are developed on historical data, are deficit based, and are focused on student factors, neglecting institutional factors. The…

Cultural capital is a key term from the Social Reproduction Theory, and it is defined as the codes and practices that parents pass on to their children (Bourdieu, 1984). Previous empirical studies have confirmed the importance of cultural capital, and it is positively related to students' reading achievement (e.g., Kosutic, 2017; Noble &…

This study aimed to assess the effectiveness of existing insolvency predictive models employed for non-profit Higher Education Institutions (HEIs) and test a proposed predictive model utilizing statistical and ratio analysis by comparing HEIs in operations with those that closed from 2017 to 2020. The researcher incorporated a non-experimental,…

The American School Counselor Association National Model was developed to unify the profession and to ensure that students receive equitable access to comprehensive, developmental, and preventive school counseling programming through the delivery of school counseling curriculum and services (ASCA: 2003, 2005, 2012). Designed to promote the…

The importance of retention rate for higher education institutions has encouraged data analysts to present various methods to predict at-risk students. Their objective is to provide timely information that may enable educators to channel the most effective remedial treatments towards precisely targeted students in an efficient manner. The present…

Evidence-based early interventions for autism spectrum disorder (ASD) have been shown to improve child outcomes and quality of life (Lord et al., 2018; Reichow et al., 2018; Smith & Iadarola, 2015). However, response to intervention is variable across both children and implementation contexts. Understanding factors that influence this…

The growth of reading and cognitive skills is crucial for children's development. This study examined the utility of incorporating a cognitive framework for reading in intervention design among struggling readers receiving National Institute for Learning Development (NILD) Educational Therapy® over a 3- to 5-year period. Evidence from this…