The education sector has been quick to recognize the power of predictive analytics to enhance student success rates. However, there are challenges to widespread adoption, including the lack of accessibility and the potential perpetuation of inequalities. These challenges present in different stages of modeling, including data preparation, model…

Predicting students' success is crucial in educational settings to improve academic performance and prevent dropouts. This study aimed to improve student performance prediction by combining advanced machine learning (ML) approaches. Convolutional Neural Networks (CNNs) and attention mechanisms were used for extracting relevant features from…

While the field advocates for a diversified and comprehensive professional role (National Association of School Psychologists, 2020), school psychologists have long spent most of their time in assessment-related activities (Farmer et al., 2021), averaging about eight cognitive evaluations monthly (Benson et al., 2020). Assessment practices have…

In Part 1 of this series, the authors briefly reviewed some challenges inherent in using standardized tools with students who are not well represented in norming data. To help readers clearly conceptualize the framework steps, the authors present two case studies that showcase how a nonstandardized approach to assessment can be individualized to…

School attendance/absenteeism (SA/A) is a crucial indicator of health and development in youth but educational policies and health-based practices in this area rely heavily on a simple metric of physical presence or absence in a school setting. SA/A data suffer from problems of quality (reliability, construct validity, data integrity) and utility…

Policy researchers have difficulty understanding stratification in enrollment in US higher education when race and ethnicity data are plagued by missing values. Students who decline to ethnoracially self-identify become part of a "race unknown" reporting category. In undergraduate enrollment, "race unknown" students are not…

Objective: College students who receive an acute care visit (ACV) from an emergency or inpatient unit require mental health follow-up (MHF) to improve long-term outcomes. This study describes tracking ACVs and MHF, while identifying characteristics of multiple vs. single ACVs. Participants: 191 students who received an ACV (N = 231) at one public…

In the 1930s schooling in the United States underwent fundamental transformations, ultimately responding to the profound social, economic, and technological changes taking place in the early decades of the twentieth century. Students' social and emotional health needed support, especially for entry into a rapidly changing nation and world. One…

Accuracy and precision are measures of experimental error and are fundamental to most chemical analysis laboratory classes. Assessment of accuracy and precision is often based on the comprehension of the results generated by students rather than on the quality of the data generated. This activity focused on developing a chemical analysis…

The rapid development of education informatization has accumulated a large amount of data for learning analytics, and adopting educational data mining to find new patterns of data, develop new algorithms and models, and apply known predictive models to the teaching system to improve learning is the challenge and vision of the education field in…

Alternative education settings (AES) educate many students with social, emotional, and behavioral (SEB) challenges. However, there is limited synthesized research available on how to best support students' SEB functioning. This systematic review examined SEB intervention and outcome research conducted in alternative schools between 2010 and 2020.…

This article evaluates the applicability at the state and district level of web scraping--an automated data-extraction technique that regularly exports and refreshes data from the Internet--to provide a low-cost way to get a close-to-real-time snapshot of the demand side of the teacher labor market. Once set up, web scraping can quickly build and…

The need for a comprehensive education data governance -- the regulation of who collects what data, how it is used and why -- continues to grow. Technologically, data can be collected by third parties, rendering schools unable to control their use. Legal frameworks partially achieve data governance as businesses continue to exploit existing…

Institutional staff such as enrollment managers, business officers, and institutional researchers are often asked to predict enrollments. Developing any predictive model can be intimidating, particularly when there is no textbook to follow. This paper provides a practical framework for generating enrollment projection options and for evaluating…

Understanding the early teacher pipeline, how many and what types of individuals are pursuing a teaching credential, is critically important. Unfortunately, as Dan Goldhaber and Kris Holden explain, the two national data collections that can be used to explore these areas provide incomplete and sometimes contrasting pictures about the number of…