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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
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
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
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
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
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
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
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
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
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
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
Gray, Cameron C.; Perkins, Dave; Ritsos, Panagiotis D. – Assessment & Evaluation in Higher Education, 2020
The field of learning analytics is progressing at a rapid rate. New tools, with ever-increasing number of features and a plethora of datasets that are increasingly utilized demonstrate the evolution and multifaceted nature of the field. In particular, the depth and scope of insight that can be gleaned from analysing related datasets can have a…
Descriptors: Educational Research, Data Collection, Data Analysis, Visual Aids
Ethan R. Van Norman; Emily R. Forcht – Journal of Education for Students Placed at Risk, 2024
This study evaluated the forecasting accuracy of trend estimation methods applied to time-series data from computer adaptive tests (CATs). Data were collected roughly once a month over the course of a school year. We evaluated the forecasting accuracy of two regression-based growth estimation methods (ordinary least squares and Theil-Sen). The…
Descriptors: Data Collection, Predictive Measurement, Predictive Validity, Predictor Variables
Flanagan, Matthew F.; Kutscher, Elisabeth L. – TEACHING Exceptional Children, 2021
Community-based instruction (CBI) is one type of community experience in which students with disabilities work toward instructional goals while engaged in activities occurring in a natural environment outside of a typical school setting (Hoover, 2016; Rowe et al., 2015). Educators who implement CBI capitalize on their students' time in the…
Descriptors: Community Based Instruction (Disabilities), Progress Monitoring, Students with Disabilities, High School Students
Kishida, Yuriko; Carter, Mark; Kemp, Coral – Australasian Journal of Special and Inclusive Education, 2021
Although the use of data is important for informing inclusive practice, research into Australian early childhood educators' data practice is limited. Types of data collected in early childhood settings and the use of these data were investigated. Surveys completed by 105 early childhood educators across Australia indicated that anecdotal written…
Descriptors: Data Use, Data Collection, Early Childhood Teachers, Early Childhood Education