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Showing 1 to 15 of 42 results Save | Export
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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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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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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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Kathleen Lynne Lane; Katie Scarlett Lane Pelton; Nathan Allen Lane; Mark Matthew Buckman; Wendy Peia Oakes; Kandace Fleming; Rebecca E. Swinburne Romine; Emily D. Cantwell – Behavioral Disorders, 2025
We report findings of this replication study, examining the internalizing subscale (SRSS-I4) of the revised version of the Student Risk Screening Scale for Internalizing and Externalizing behavior (SRSS-IE 9) and the internalizing subscale of the Teacher Report Form (TRF). Using the sample from 13 elementary schools across three U.S. states with…
Descriptors: Data Analysis, Decision Making, Data Use, Measures (Individuals)
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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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Ann Marie Cotman; F. Chris Curran; Katharine Harris-Walls – Education Policy Analysis Archives, 2024
Choices made on data visualizations guide how users make meaning of the information presented. This research investigates design decisions made on 115 state-level dashboards reporting school safety data. Using pre-determined codes drawn from a framework of visualization rhetoric, dashboard characteristics were described and analyzed. Analysis…
Descriptors: School Safety, Data, Visual Aids, State Agencies
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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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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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Aom Perkash; Qaisar Shaheen; Robina Saleem; Furqan Rustam; Monica Gracia Villar; Eduardo Silva Alvarado; Isabel de la Torre Diez; Imran Ashraf – Education and Information Technologies, 2024
Developing tools to support students, educators, intuitions, and government in the educational environment has become an important task to improve the quality of education and learning outcomes. Information and communication technology (ICT) is adopted by educational institutions; one such instance is video interaction in flipped teaching.…
Descriptors: Academic Achievement, Colleges, Artificial Intelligence, Predictor Variables
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Kathleen Lynne Lane; Nathan Allen Lane; Mark Matthew Buckman; Katie Scarlett Lane Pelton; Kandace Fleming; Rebecca E. Swinburne Romine – Behavioral Disorders, 2025
We report the results of a convergent validity study examining the externalizing subscale (SRSS-E5, five items) of the adapted Student Risk Screening Scale for Internalizing and Externalizing (SRSS-IE 9) with the externalizing subscale of the Teacher Report Form (TRF) with two samples of K-12 students. Results of logistic regression and receiver…
Descriptors: Data Analysis, Decision Making, Data Use, Test Validity
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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
Salvatore Robert D'Angelo – ProQuest LLC, 2024
My dissertation studies the relationship between counseling and violence within U.S. schools. Much of the research on school security and school safety tends to lean heavily on routine activities theory and other opportunity theories, which limits the study of other factors critically relevant to this topic such as school climate. This…
Descriptors: School Safety, School Counseling, Educational Environment, School Violence
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
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Kerstin Huber; Maria Bannert – Journal of Computing in Higher Education, 2024
The empirical study investigates what log files and process mining can contribute to promoting successful learning. We want to show how monitoring and evaluation of learning processes can be implemented in the educational life by analyzing log files and navigation behavior. Thus, we questioned to what extent log file analyses and process mining…
Descriptors: Learning Processes, Data Analysis, Navigation (Information Systems), Student Behavior
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Shuanghong Shen; Qi Liu; Zhenya Huang; Yonghe Zheng; Minghao Yin; Minjuan Wang; Enhong Chen – IEEE Transactions on Learning Technologies, 2024
Modern online education has the capacity to provide intelligent educational services by automatically analyzing substantial amounts of student behavioral data. Knowledge tracing (KT) is one of the fundamental tasks for student behavioral data analysis, aiming to monitor students' evolving knowledge state during their problem-solving process. In…
Descriptors: Student Behavior, Electronic Learning, Data Analysis, Models
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