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…

When a school district in North Dakota began having hard conversations about its struggling status, a simple, yet crucial, contributor to academic success became abundantly clear: student attendance. That conversation laid the groundwork for a districtwide project, enacted in partnership with the Region 11 Comprehensive Center (R11CC), North…

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…

This article characterizes and reflects on the possible uses of early warning systems (hereafter, EWS) in the region as effective tools to support educational pathways, whenever they identify risks of dropout, difficulties for the achievement of substantive learning, and the possibility of organizing specific actions. This article was developed in…

Missing values that fail to be appropriately accounted for may lead to reduced statistical power, biased estimators, reduced representativeness of the sample, and incorrect interpretations and conclusions (Gorelick, 2006). The current study provided an ontological perspective of data manipulation by explaining how statistical results can…

Educational data mining has gained a lot of attention among scientists in recent years and constitutes an efficient tool for unraveling the concealed knowledge in educational data. Recently, semisupervised learning methods have been gradually implemented in the educational process demonstrating their usability and effectiveness. Cotraining is a…

Students at risk for behavioral difficulties have unique needs that affect their academic, behavioral, and social skills. Many of these students are served in various educational settings, possibly transitioning back and forth from traditional schools to alternative settings. As they transition, there is a chance that the students' behavioral data…

Teachers may benefit from using classroom-delivered, low-intensity strategies to increase engagement of students at-risk for emotional and behavioral disorders and academic failure in the general education classroom. This project focused on empowering teachers to be involved in every step of the research process: screening, planning, data…

Students who are at risk for or show low-intensity behavioral problems may need targeted, Tier 2 interventions. Often, Tier 2 problem-solving teams are charged with monitoring student responsiveness to intervention. This process may be difficult for those who are not trained in data collection and analysis procedures. To aid practitioners in these…

Addressing student absenteeism continues to permeate education policy and practice. California and a majority of other states have incorporated "chronic absenteeism" as an accountability metric under the Every Student Succeeds Act. It is therefore a crucial time to take stock of what we know on the research, policy, and practice to…

Surveys show rates of sexual harassment and misogyny among students are high in U.S. secondary schools--yet most schools fail to deal with this problem. Many educators would like to intervene when they hear students use degrading or sexualized language about girls (or LGBTQ youth) or harass them, but don't know how to do so effectively. The…

Students receiving behavioral supports in the third tier of the schoolwide positive behavioral interventions and supports (SWPBIS) framework are often identified as having emotional and behavior disabilities. Although educators implement evidence-based practices with fidelity, these practices are not always effective in supporting students with…

While learning analytics (LA) practices have been shown to be practical and effective, most of them require a huge amount of data and effort. This paper reports a case study which demonstrates the feasibility of practising LA at a low cost for instructors to identify at-risk students in an undergraduate business quantitative methods course.…

Each school year, approximately 6.8 million students miss at least 15 days of school, putting their academic success at risk and making them chronically absent as defined by the federal government. This report provides case studies that detail specific ways cities are leading efforts to get students to school each day. Case studies for the…

The U.S. education system is founded on the idea that students are in class every weekday; simply put, to benefit from school, a student must be in attendance. Nevertheless, many students miss school on a regular basis, thereby missing out on valuable instruction. Statistics on absenteeism among homeless students are particularly concerning, with…