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Quin-Anne Hinrichs; Chelsea R. Johnston; Laura Feuerborn; Ashli Tyre – Beyond Behavior, 2025
Implementation of a culturally responsive positive behavioral interventions and supports (PBIS) framework is associated with positive outcomes for secondary students when implemented schoolwide. Yet, educators often report more implementation challenges in secondary school as compared to elementary school settings. Difficulties obtaining student…
Descriptors: Behavior Modification, Positive Behavior Supports, Student Behavior, Behavior Problems
Majdi Beseiso – TechTrends: Linking Research and Practice to Improve Learning, 2025
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…
Descriptors: Prediction, Success, Academic Achievement, Artificial Intelligence
Heilmann, John; Miller, Jon F. – Perspectives of the ASHA Special Interest Groups, 2023
Purpose: In the early 1980s, researchers and speech-language pathologists (SLPs) collaborated to develop the Systematic Analysis of Language Transcripts (SALT). Research and development over the ensuing decades has culminated into SALT Solutions, a set of tools to assist SLPs to efficiently complete language sample analysis (LSA) with their…
Descriptors: Sampling, Language Usage, Data Analysis, Data Collection
Prophet-Bullock, Ebony E. – ProQuest LLC, 2023
This qualitative case study sought to discover how school-level data teams can intentionally use effective data practices to identify and implement high-leverage interventions that support all students, including Black and Latinx boys, in attaining the necessary academic requirements for high school graduation. The researcher analyzed data from…
Descriptors: High School Students, African American Students, Hispanic American Students, Males
Robin Clausen – Discover Education, 2025
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…
Descriptors: Dropout Prevention, Data Analysis, Principals, School Counselors
Aoife L. Gallagher; Rachel Murphy; Ciara Ni Eochaidh; Johanna Fitzgerald; Carol-Anne Murphy; James Law – Language, Speech, and Hearing Services in Schools, 2023
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…
Descriptors: Program Implementation, Intervention, Educational Research, Speech Language Pathology
Nancy Montes; Fernanda Luna – UNESCO International Institute for Educational Planning, 2024
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…
Descriptors: Data Collection, Data Use, At Risk Students, Foreign Countries
Pavelko, Stacey L.; Owens, Robert E., Jr. – Perspectives of the ASHA Special Interest Groups, 2023
Purpose: The purposes of this tutorial are (a) to describe a method of language sample analysis (LSA) referred to as SUGAR (Sampling Utterances and Grammatical Analysis Revised) and (b) to offer step-by-step instructions detailing how to collect, transcribe, analyze, and interpret the results of a SUGAR language sample. Method: The tutorial begins…
Descriptors: Sampling, Language Tests, Data Collection, Data Analysis
Caspari-Sadeghi, Sima – Cogent Education, 2023
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…
Descriptors: Learning Analytics, Data Analysis, Higher Education, Feedback (Response)
Yu-Jie Wang; Chang-Lei Gao; Xin-Dong Ye – Education and Information Technologies, 2024
The continuous development of Educational Data Mining (EDM) and Learning Analytics (LA) technologies has provided more effective technical support for accurate early warning and interventions for student academic performance. However, the existing body of research on EDM and LA needs more empirical studies that provide feedback interventions, and…
Descriptors: Precision Teaching, Data Use, Intervention, Educational Improvement
Jingjing Long; Jiaxin Lin – Education and Information Technologies, 2024
English language learning students in China often feel challenged to learn English due to lack of motivation and confidence, pronunciation and grammar difference, lack of practice and people to communicate with etc., which affects students mental health. Adopting Big data and AI will help in overcoming these limitations as it provides personalized…
Descriptors: Foreign Countries, English Language Learners, College Students, Mental Health
Kuntz, Emily M.; Massey, Cynthia C.; Peltier, Corey; Barczak, Mary; Crowson, H. Michael – Teacher Education and Special Education, 2023
Through time-series graphs, teachers often evaluate progress monitoring data to make both low- and high-stakes decisions for students. The construction of these graphs--specifically, the presence of an aimline and the data points per x- to y-axis ratio (DPPXYR)--may impact decisions teachers make. The purpose of this study was to evaluate the…
Descriptors: Graphs, Preservice Teachers, Accuracy, Decision Making
Khulbe, Manisha; Tammets, Kairit – Technology, Knowledge and Learning, 2023
Insights derived from classroom data can help teachers improve their practice and students' learning. However, a number of obstacles stand in the way of widespread adoption of data use. Teachers are often sceptical about the usefulness of data. Even when willing to work with data, they often do not have the relevant skills. Tools for analysis of…
Descriptors: Faculty Development, Learning Analytics, Intervention, Teacher Attitudes
Vaccarello, Cara; Kratochwill, Thomas R.; Asmus, Jennifer M. – Journal of Educational and Psychological Consultation, 2023
We examined the outcomes of elementary school-based problem-solving teams (PSTs) who participated in a multi-component consultation focused on enhancing systematic problem solving. Consultation provided to each PST included training in the use of a problem-solving protocol (i.e., "Outcomes: Planning Monitoring, and Evaluating"…
Descriptors: Elementary School Teachers, Problem Solving, Consultation Programs, Coaching (Performance)
Esther Tenorio; Jimel Sandoval; Jenae Sanchez; Ryan Sanchez; Melina Salvador; Deborah B. Altschul – Health Education & Behavior, 2025
The Tribal-Academic partnership model described in this article uses Community-Based Participatory Research (CBPR) approaches to foster collaboration between community partners and academic researchers throughout study design, implementation, data collection, interpretation, and dissemination. Literature highlights the importance of community…
Descriptors: School Community Relationship, Research Design, Data Collection, Data Analysis

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