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Yikai Lu; Lingbo Tong; Ying Cheng – Journal of Educational Data Mining, 2024
Knowledge tracing aims to model and predict students' knowledge states during learning activities. Traditional methods like Bayesian Knowledge Tracing (BKT) and logistic regression have limitations in granularity and performance, while deep knowledge tracing (DKT) models often suffer from lacking transparency. This paper proposes a…
Descriptors: Models, Intelligent Tutoring Systems, Prediction, Knowledge Level
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Narjes Rohani; Behnam Rohani; Areti Manataki – Journal of Educational Data Mining, 2024
The prediction of student performance and the analysis of students' learning behaviour play an important role in enhancing online courses. By analysing a massive amount of clickstream data that captures student behaviour, educators can gain valuable insights into the factors that influence students' academic outcomes and identify areas of…
Descriptors: Mathematics Education, Models, Prediction, Knowledge Level
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Emma R. Dear; Bryce D. McLeod; Nicole M. Peterson; Kevin S. Sutherland; Michael D. Broda; Alex R. Dopp; Aaron R. Lyon – Grantee Submission, 2024
Introduction: Due to usability, feasibility, and acceptability concerns, observational treatment fidelity measures are often challenging to deploy in schools. Teacher self-report fidelity measures with specific design features might address some of these barriers. This case study outlines a community-engaged, iterative process to adapt the…
Descriptors: Measures (Individuals), Data Collection, Observation, Learning Analytics
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Prasoon Patidar; Tricia J. Ngoon; Neeharika Vogety; Nikhil Behari; Chris Harrison; John Zimmerman; Amy Ogan; Yuvraj Agarwal – Journal of Learning Analytics, 2024
Classroom sensing systems can capture data on teacher-student behaviours and interactions at a scale far greater than human observers can. These data, translated to multi-modal analytics, can provide meaningful insights to educational stakeholders. However, complex data can be difficult to make sense of. In addition, analyses done on these data…
Descriptors: Learning Analytics, Classroom Observation Techniques, Data Analysis, Student Behavior
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Duncan Culbreth; Rebekah Davis; Cigdem Meral; Florence Martin; Weichao Wang; Sejal Foxx – TechTrends: Linking Research and Practice to Improve Learning, 2025
Monitoring applications (MAs) use digital and online tools to collect and track data on student behavior, and they have become increasingly popular among schools. Empirical research on these complex surveillance platforms is scant, and little is known about the efficacy or impact that they have on students. This study used a multi-method…
Descriptors: High School Students, COVID-19, Pandemics, Progress Monitoring
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Xiaofang Hao – International Journal of Web-Based Learning and Teaching Technologies, 2025
Online education is an important component of education reform and one of the important learning modes in today's society, which can achieve the goal of learning anytime, anywhere and for everyone. Therefore, this paper constructs an analysis model of online education course emotional perception and course resource integration based on new media…
Descriptors: Stakeholders, Online Courses, Education Courses, Instructional Materials
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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
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Melanie M. Keller; Takuya Yanagida; Oliver Lüdtke; Thomas Goetz – Educational Psychology Review, 2025
Students' emotions in the classroom are highly dynamic and thus typically strongly vary from one moment to the next. Methodologies like experience sampling and daily diaries have been increasingly used to capture these momentary emotional states and its fluctuations. A recurring question is to what extent aggregated state ratings of emotions over…
Descriptors: Foreign Countries, High School Students, Affective Behavior, Emotional Response
Christine G. Casey, Editor – Centers for Disease Control and Prevention, 2024
The "Morbidity and Mortality Weekly Report" ("MMWR") series of publications is published by the Office of Science, Centers for Disease Control and Prevention (CDC), U.S. Department of Health and Human Services. Articles included in this supplement are: (1) Overview and Methods for the Youth Risk Behavior Surveillance System --…
Descriptors: High School Students, At Risk Students, Health Behavior, National Surveys
Juan D’Brot; W. Chris Brandt – Region 5 Comprehensive Center, 2024
In today's educational landscape, state and local educational agencies (SEAs and LEAs) often experience challenges connecting large-scale accountability data with actual school improvement initiatives. These challenges tend to be rooted in incoherent design and use of data systems for continuous improvement. As we aim to support SEAs in…
Descriptors: Educational Improvement, Data Collection, State Departments of Education, School Districts
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Marla J. Lohmann; Samantha Riggleman; Johanna P. Higgins – Early Childhood Education Journal, 2024
Over one-third of preschoolers with disabilities are fully included in the classroom with their typically developing peers and another large percentage receive some instruction in the inclusive classroom. In order to support young children and increase the likelihood of the desired learning and behavior outcomes, teachers must use individual data…
Descriptors: Handheld Devices, Early Childhood Education, Student Behavior, Classroom Environment
Office of Educational Technology, US Department of Education, 2025
As outlined in the 2024 National Educational Technology Plan, digital health, safety, and citizenship skills reflect the full set of knowledge and habits students need to use technology appropriately, responsibly, and safely. For schools and districts, creating the conditions for those skills to develop includes policies regulating the use of…
Descriptors: Computer Use, Technology Uses in Education, Safety, Student Responsibility
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K. Brigid Flannery; Mimi McGrath Kato; Angus Kittelman; Nadia Katul Sampson; Kent McIntosh – Behavioral Disorders, 2024
The purpose of this study was to provide initial evidence of the effectiveness of Check-In/Check-Out-High School (CICO-HS) on high school student outcomes. Check-In/Check-Out-High School is a version of CICO, an established Tier 2 intervention designed to improve student academic and social behavior, adapted to increase effectiveness and…
Descriptors: High School Students, Intervention, Positive Behavior Supports, Program Effectiveness
Office of Educational Technology, US Department of Education, 2024
Digital health, safety, and citizenship skills reflect the full set of knowledge and habits students can adopt to protect themselves and others in online spaces. For schools and districts, protecting student health and safety while those skills develop means taking an approach that can include policies governing the use of school-provided…
Descriptors: LGBTQ People, Minority Group Students, Student Behavior, Safety