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Kunyu Xu; Yu-Min Ku; Chenlu Ma; Chien-Hui Lin; Wan-Chen Chang – Metacognition and Learning, 2024
As an important construct in the cognitive process, comprehension monitoring has received much scholarly attention. Researchers have recognized comprehension monitoring as an ability closely linked with children's reading comprehension ability and working memory capacity. Evidence is also abundant to prove that comprehension monitoring skill…
Descriptors: Eye Movements, Computer Assisted Testing, Memory, Reading Comprehension
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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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Ethan R. Van Norman; Emily R. Forcht – Assessment for Effective Intervention, 2024
Curriculum-based measurement of reading (CBM-R) is a common assessment educators use to monitor student growth in broad reading skills and evaluate the effectiveness of instructional programs. Computer-adaptive tests (CATs), such as Star Reading, have been cited as a viable option to formatively assess reading growth. We used Bayesian…
Descriptors: Reading Improvement, Reading Skills, Reading Achievement, Curriculum Based Assessment
Chelsea Williams – ProQuest LLC, 2024
In rural Mississippi, addressing the issue of reading nonproficiency for third-grade students has posed a significant challenge. To tackle the issue's complexity, the Mississippi legislature implemented the Literacy-Based Promotion Act (LBPA), also known as the 'no social promotion grade-level retention gateway" (Barrett-Tatum et al., 2019).…
Descriptors: Reading, Progress Monitoring, High Stakes Tests, Rural Schools
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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
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Xin Wei; Jeremy Roschelle; Danae Kamdar; Tiffany Leones; Ximena Dominguez; William Corrin – Society for Research on Educational Effectiveness, 2024
Background/Context: Funders, researchers and developers share an interest in applying rapid cycle evaluation techniques in education (McNall & Foster-Fishman, 2007; Resch, 2016). Both rapid-cycle and other evaluation processes require monitoring the quality of implementation (Moir, 2018). By quickly monitoring and adjusting implementation,…
Descriptors: Elementary School Mathematics, Elementary School Students, Elementary School Teachers, Mathematics Instruction