Objective: Self-report symptom inventories are commonly used in adult ADHD assessment, and research indicates they should be interpreted with caution. This study investigated one self-report symptom inventory for adult ADHD in a clinical sample. Method: Archival data were used to evaluate diagnostic utility of the Conners Adult ADHD Rating…

We sought to replicate prior findings that admissions tests' underprediction of female college performance was driven in part by the omission of Big 5 personality factors from the predictive model, using 5,400 college students. We investigated gender differences in an elaborated model subdividing the Big 5 into ten aspects. We found differences at…

This systematic literature review investigates the fairness of machine learning algorithms in educational settings, focusing on recent studies and their proposed solutions to address biases. Applications analyzed include student dropout prediction, performance prediction, forum post classification, and recommender systems. We identify common…

This article revisits the Mincer earnings function and presents comparable estimates of the average monetary returns associated with an additional year of education across different regions worldwide. In contrast to the traditional Ordinary Least Squares (OLS) method commonly employed in the literature, this study applied a cutting-edge approach…

The usefulness of college admissions test scores and high school GPA for predicting college success, particularly in STEM (science, technology, engineering, and mathematics), has been widely debated. As colleges across the country face challenges in STEM student retention and achievement, understanding the factors that contribute to college…

The moment a child walks into a new classroom, teachers and classmates form an impression based on minimal information. Yet, little is known about the accuracy of such impressions when it concerns children's social functioning at school. The current study examined the accuracy of children's, teachers' and adults' impressions of 18 unacquainted…

Increasing productivity in educational systems is of great importance. Researchers are keen to predict the academic performance of students; this is done to enhance the overall productivity of educational system by effectively identifying students whose performance is below average. This universal concern has been combined with data science…

Student success and drop-out predictions have gained increased attention in recent years, connected to the hope that by identifying struggling students, it is possible to intervene and provide early help and design programs based on patterns discovered by the models. Though by now many models exist achieving remarkable accuracy-values, models…

Background: The importance of high school completion for jobs and postsecondary opportunities is well- documented. Combined with federal laws where high school graduation rate is a core performance indicator, school systems and states face pressure to actively monitor and assess high school completion. This proposal employs machine learning…

The authors asked students enrolled in a wide range of college mathematics courses to predict their scores on quizzes and exams. They found that top and bottom performers were less accurate predictors, but those scoring in the middle range were more accurate in predicting their scores. Females were more accurate predictors of their scores than…

Acadience Reading (AR) is a screener for early detection of reading problems in elementary students. Limited research exists, however, on its technical adequacy for evaluation of English Learners (ELs). In this study, we tested the long-term predictive validity and diagnostic accuracies of AR and examined the differences between native…

Machine learning algorithms have recently been used to predict students' performance in an introductory physics class. The prediction model classified students as those likely to receive an A or B or students likely to receive a grade of C, D, F or withdraw from the class. Early prediction could better allow the direction of educational…

Regional Educational Laboratory Southwest partnered with the Arkansas Department of Education to examine Arkansas's middle school and high school indicators of postsecondary readiness and success, building on an earlier study of these indicators (Hester et al., 2021). Academic indicators include attaining proficiency on state academic…

Performance prediction is a leading topic in learning analytics research due to its potential to impact all tiers of education. This study proposes a novel predictive modeling method to address the research gaps in existing performance prediction research. The gaps addressed include: the lack of existing research focus on performance prediction…

Regional Educational Laboratory Southwest partnered with the Arkansas Department of Education (ADE) to examine Arkansas's middle and high school indicators of postsecondary readiness and success, building on an earlier study of these indicators (Hester et al., 2021). Academic indicators include attaining proficiency on state achievement tests,…