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Charles J. Fitzsimmons; Clarissa A. Thompson – Metacognition and Learning, 2024
Metacognitive monitoring, recognizing when one is accurate or not, is important because judgments of one's performance or knowledge often relate to control decisions, such as help seeking. Unfortunately, children and adults struggle to accurately monitor their performance during number-magnitude estimation. People's accuracy in estimating number…
Descriptors: Metacognition, Progress Monitoring, Cues, Spatial Ability
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Adam J. Lekwa; Joseph Deegan; Christian Mathews – Assessment for Effective Intervention, 2025
Drawing on cognitive theory in reading comprehension, Sentence Order Fluency (SOF) is proposed as a method for monitoring progress in reading comprehension. In this article, we present results of a pilot study on SOF conducted between April and June 2023, with a group of 119 students in Grades 4, 5, and 6 in a charter school in the mid-Atlantic…
Descriptors: Progress Monitoring, Reading Comprehension, Elementary School Students, Grade 4
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Daniel Murphy; Sarah Quesen; Matthew Brunetti; Quintin Love – Educational Measurement: Issues and Practice, 2024
Categorical growth models describe examinee growth in terms of performance-level category transitions, which implies that some percentage of examinees will be misclassified. This paper introduces a new procedure for estimating the classification accuracy of categorical growth models, based on Rudner's classification accuracy index for item…
Descriptors: Classification, Growth Models, Accuracy, Performance Based Assessment
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Tao Hao; Zhe Wang; Shiting Dai; Yuxin Ren – Journal of Experimental Education, 2025
Irrespective of much research examining the effects of ego depletion on self-control related measures in social psychology, inadequate attention has been paid regarding whether ego depletion influences on logical reasoning performance. To address this gap, this experimental study randomly assigned Chinese college students (n = 112) to either an…
Descriptors: Foreign Countries, College Students, Public Colleges, Self Concept
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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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Ethan R. Van Norman; David A. Klingbeil; Kristen Truman; Peter M. Nelson; David C. Parker – Grantee Submission, 2024
The transition from sounding out unfamiliar words to effortlessly reading connected text does not occur all at once nor at the same rate for students. The purpose of this study was to explore the accuracy of three decision rules (data point, median, and trend line) applied to progress monitoring outcomes of alphabetic principle (nonsense word…
Descriptors: Progress Monitoring, Outcomes of Education, Reading Rate, Word Recognition
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Ethan R. Van Norman; David A. Klingbeil; Kirsten Truman; Peter M. Nelson; David C. Parker – Remedial and Special Education, 2024
The transition from sounding out unfamiliar words to effortlessly reading connected text does not occur all at once or at the same rate for students. The purpose of this study was to explore the accuracy of three decision rules (data point, median, and trend line) applied to progress monitoring outcomes of alphabetic principle (nonsense word…
Descriptors: Progress Monitoring, Outcomes of Education, Reading Rate, Word Recognition