Curriculum-based measurement (CBM) represents a critical strategy for data-based decisionmaking within educational settings. Visual analysis is frequently used to analyze CBM data; thus, CBM vendors often automatically generate graphs based on student data to facilitate analysis. Differences in graph formatting are apparent across CBM vendors, and…

Background: In educational settings, individuals are often best served by an intervention that is adapted over sequential stages to suit their initial and changing needs. The salience of an adaptive intervention is, perhaps, most clear in the classroom. Learning itself is a sequential process: mastering a given concept or technique frequently…

The visual analysis of data presented in time-series graphs are common in single-case design (SCD) research and applied practice in school psychology. A growing body of research suggests that visual analysts' ratings are often influenced by construct-irrelevant features including Y-axis truncation and compression of the number of data points per…

The purpose of this quantitative systematic literature review was to identify and describe published mathematics studies from 1980 to 2021 that incorporated a self-monitoring component (k = 22 studies; N = 1,787 students). We examined specific self-monitoring procedures, instructional contexts, implementation variables, and methodological quality.…

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…

"Best Practices in School Psychology" is one of the most influential books in school psychology history. Originally published in 1985 by Thomas and Grimes, it was the first book offered by the National Association of School Psychologists. Its six editions have been revised every 5-8 years. Utilizing Publish or Perish as well as…

In standard statistical data analysis, the effects of intervention or prevention efforts are evaluated in terms of variable relations. Results from application of regression-type methods suggest whether, overall, intervention is successful. In this article, we propose using configural frequency analysis (CFA) either in tandem with regression-type…

Purpose: The aim of this study was to map the use of implementation science frameworks, models, and theories in intervention research targeting learning needs in the classroom. Method: A scoping review was conducted. Electronic database and manual searches were conducted. Two reviewers independently completed screening, data extraction, and…

This study explored the experiences of school counselors utilizing peer-group supervision to assist in analyzing data to determine the effectiveness of interventions. The literature gap indicates that further research was needed regarding the relationship between appropriate supervision and its impact on school counselors' ability to analyze data.…

Early Warning Systems (EWS) are research-based analytics that use statistical models to assess dropout risk. School leaders use this analytic to consolidate data about a student and provide actionable data to craft an intervention. Little is currently known about the processes involved in school implementation or data use. By analyzing Montana EWS…

Interactive learning environments can generate massive learning behavior data and the support of learning behavior big data can ensure the completeness of data analysis and robustness of relationship verification. In this study, learning behaviors are divided into training set and testing set, BP neural network and recurrent Elman network are…

Context: Prolonged disconnection from school and work represents major setbacks during the transition to adulthood and is a distinct feature of the developmental trajectories of many disadvantaged youths, especially those from a marginalized racial background (Hong and Chung 2022; Shanahan 2000). Differential schooling experiences are hypothesized…

Recent reviews of the educational intervention literature have noted patterns of intervention impact fadeout on cognitive skills, whereby skill trajectories between children in the intervention and control group converge in the years following the end of the intervention. Some early childhood education (ECE) researchers have suggested that skill…

Participatory Theme Elicitation (PTE) is a new approach to increasing user-involvement in qualitative data analysis. In this five-step method, participants independently identify themes in the data using open card sorting, and are supported in their development of a set of themes that reflect all participant views. We describe and evaluate PTE…

Data-driven decision-making and data-intensive research are becoming prevalent in many sectors of modern society, i.e. healthcare, politics, business, and entertainment. During the COVID-19 pandemic, huge amounts of educational data and new types of evidence were generated through various online platforms, digital tools, and communication…