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Soyoung Park; Pamela M. Stecker; Sarah R. Powell – Intervention in School and Clinic, 2024
This article provides teachers with a toolkit for assessing students in the context of data-based individualization (DBI) in mathematics. Assessing students is a critical component of DBI because it provides teachers with information about what they may need to modify in their instructional programs. In this article, we provide teachers with…
Descriptors: Student Evaluation, Individualized Instruction, Mathematics Instruction, Progress Monitoring
Australian Government Tertiary Education Quality and Standards Agency, 2024
The Australian Government Tertiary Education Quality and Standards Agency's (TEQSA's) guidance notes are concise documents designed to provide high-level, principles-based guidance on interpretation and application of specific standards of the Higher Education Standards Framework (Threshold Standards) 2021. They also draw attention to other…
Descriptors: Foreign Countries, Instructional Improvement, Quality Assurance, Data Collection
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Natasha Arthars; Kate Thompson; Henk Huijser; Steven Kickbusch; Samuel Cunningham; Gavin Winter; Roger Cook; Lori Lockyer – Australasian Journal of Educational Technology, 2024
Assessing group work formatively in higher education poses a significant challenge. The complexity of evaluating individual contributions is compounded by the lack of efficient and effective methods for tracking, analysing and assessing individual engagement and contributions, which can impede timely feedback and the development of group work…
Descriptors: Formative Evaluation, Cooperative Learning, College Students, Student Evaluation
Sylvester L. Sison – ProQuest LLC, 2022
The purpose of this study was to explore the perceptions of employees regarding changes in their workplace experience following the implementation of an electronic performance monitoring (EPM) system. The study's conceptual framework utilized Burke and Litwin's (1992) model of organizational change and Bandura's (1986) social cognitive theory to…
Descriptors: Job Performance, Progress Monitoring, Information Science, Employee Attitudes
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Marissa J. Filderman; Christy R. Austin – Beyond Behavior, 2024
Students with and at risk for emotional and behavioral disorders (EBD) struggle to acquire and develop writing skills. To support their students' unique needs, it is important for teachers to monitor student writing progress to make instructional decisions based on data. In this article we describe methods for progress monitoring focused on…
Descriptors: Emotional Disturbances, Behavior Disorders, At Risk Students, Writing Skills
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Shepley, Collin; Grisham-Brown, Jennifer; Lane, Justin D.; Ault, Melinda J. – Topics in Early Childhood Special Education, 2022
Progress-monitoring data collection is an essential skill for teachers serving children for whom the general curriculum is insufficient. As the field of early childhood education moves toward tiered service provision models, the importance of routine data collection is heightened. Therefore, we evaluated the effects of a training package on…
Descriptors: Early Childhood Education, Preschool Teachers, Teacher Behavior, Data Collection
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Khan, Ijaz; Ahmad, Abdul Rahim; Jabeur, Nafaa; Mahdi, Mohammed Najah – Smart Learning Environments, 2021
A major problem an instructor experiences is the systematic monitoring of students' academic progress in a course. The moment the students, with unsatisfactory academic progress, are identified the instructor can take measures to offer additional support to the struggling students. The fact is that the modern-day educational institutes tend to…
Descriptors: Artificial Intelligence, Academic Achievement, Progress Monitoring, Data Collection
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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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Silva, Meghan R.; Collier-Meek, Melissa A.; Codding, Robin S.; Kleinert, Whitney L.; Feinberg, Adam – Contemporary School Psychology, 2021
Response-to-intervention (RtI) is a multi-tiered framework designed to prevent academic difficulties by facilitating robust, research-based instruction and providing targeted or individualized short-term interventions for students at-risk per periodic screening and progress monitoring data. The cornerstone of RtI is data-based decision-making to…
Descriptors: Data Collection, Data Analysis, Response to Intervention, Decision Making
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Ian Hardy – Professional Development in Education, 2024
Schooling in Australia has become subject to increased processes of data-based governance. This article draws upon the insights of an experienced teacher, 'Meriam', who, having taught more than 34-years over almost a 50-year span, reflected upon the nature of such changes. Utilising theorising in relation to datafication processes and…
Descriptors: Foreign Countries, Experienced Teachers, Teacher Attitudes, Educational Change
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Kumm, Skip; Maggin, Daniel M. – Beyond Behavior, 2021
Goal setting is a research-informed intervention that has demonstrated improved behavioral outcomes for students with emotional and behavioral disorders. However, not all students will respond to goal-setting interventions delivered in a standard format, requiring planning, implementation, and ongoing evaluation of more intensive goal-setting…
Descriptors: Goal Orientation, Intervention, Emotional Disturbances, Behavior Disorders
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Swain, Kristine D.; Hagaman, Jessica L.; Leader-Janssen, Elizabeth M. – Preventing School Failure, 2022
Utilizing effective data collection methods to track student progress on Individual Education Program (IEP) goals is essential to quality programming and meeting each student's specific needs. This study surveyed special education teachers in four midwestern states to understand IEP data collection methods and assessment training. Results…
Descriptors: Data Collection, Progress Monitoring, Individualized Education Programs, Special Education
Chad J. Coleman – ProQuest LLC, 2021
Determining which students are at-risk of poorer outcomes -- such as dropping out, failing classes, or decreasing standardized examination scores -- has become an important area of both research and practice in K-12 education. The models produced from this type of predictive modeling research are increasingly used by high schools in Early Warning…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Elementary Secondary Education
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
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Allen, Ray; Ferkel, Rick; Fisher, Kevin; Wawersik, Andrew – Journal of Physical Education, Recreation & Dance, 2022
The purpose of this paper is to present an assessment system that enables physical education programs to collect data capable of meeting their assessment. Assessment at the elementary level is a daunting task. Practitioners are charged to teach multiple objectives across all learning domains to hundreds of students in multiple grades in a limited…
Descriptors: Physical Education, Educational Assessment, Data Collection, Elementary School Teachers
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