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Elena C. Papanastasiou; Michalis P. Michaelides – Large-scale Assessments in Education, 2024
Test-taking behavior is a potential source of construct irrelevant variance for test scores in international large-scale assessments where test-taking effort, motivation, and behaviors in general tend to be confounded with test scores. In an attempt to disentangle this relationship and gain further insight into examinees' test-taking processes,…
Descriptors: Grade 4, Testing, Student Behavior, Test Wiseness
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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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Jing Liu; Julie Cohen – Educational Evaluation and Policy Analysis, 2021
Valid and reliable measurements of teaching quality facilitate school-level decision-making and policies pertaining to teachers. Using nearly 1,000 word-to-word transcriptions of fourth- and fifth-grade English language arts classes, we apply novel text-as-data methods to develop automated measures of teaching to complement classroom observations…
Descriptors: Grade 4, Grade 5, Language Arts, Elementary School Teachers
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Kuddar, Cagla; Cetin, Sevda – International Journal of Assessment Tools in Education, 2022
The purpose of the study is to analyze the affective traits that affect mathematics achievement through Structural Equation Modeling (SEM) as a traditional regression model and Multivariate Adaptive Regression Splines (MARS), as one of the data mining methods. Structural Equation Modeling, one of the regression-based methods, is quite popular for…
Descriptors: Mathematics Achievement, Structural Equation Models, Regression (Statistics), Achievement Tests
Jing Liu; Julie Cohen – Annenberg Institute for School Reform at Brown University, 2020
Valid and reliable measurements of teaching quality facilitate school-level decision-making and policies pertaining to teachers, but conventional classroom observations are costly, prone to rater bias, and hard to implement at scale. Using nearly 1,000 word-to-word transcriptions of 4th- and 5th-grade English language arts classes, we apply novel…
Descriptors: Grade 4, Grade 5, Language Arts, Elementary School Teachers
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Sorensen, Lucy C. – Educational Administration Quarterly, 2019
Purpose: In an era of unprecedented student measurement and emphasis on data-driven educational decision making, the full potential for using data to target resources to students has yet to be realized. This study explores the utility of machine-learning techniques with large-scale administrative data to identify student dropout risk. Research…
Descriptors: At Risk Students, Dropouts, Data Collection, Data Analysis
Yang, Dandan; Zargar, Elham; Adams, Ashley Marie; Day, Stephanie L.; Connor, Carol McDonald – Assessment for Effective Intervention, 2021
Stealth assessment has been successfully embedded in educational games to measure students' learning in an unobtrusive and supportive way. This study explored the possibility of applying stealth assessment in a digital reading platform and sought to identify potential in-system indicators of students' digital learning outcomes. Utilizing the user…
Descriptors: Electronic Publishing, Books, Computer Assisted Instruction, Reading Processes
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Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – Grantee Submission, 2015
Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…
Descriptors: Educational Environment, Predictive Measurement, Predictor Variables, Cooperative Learning
Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – International Educational Data Mining Society, 2015
Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…
Descriptors: Educational Environment, Predictive Measurement, Predictor Variables, Cooperative Learning
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Adelson, Jill L.; Dickinson, Emily R.; Cunningham, Brittany C. – Educational Researcher, 2016
This brief examined the patterns of reading achievement using statewide data from all students (Grades 3-10) in multiple years to examine gaps based on student, school, and district characteristics. Results indicate reading achievement varied most between students within schools and that students' prior achievement was the strongest predictor of…
Descriptors: Reading Achievement, Achievement Gap, School Districts, Institutional Characteristics
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Konstantopoulos, Spyros; Shen, Ting – Educational Research and Evaluation, 2016
Class size reduction has been viewed as one school mechanism that can improve student achievement. Nonetheless, the literature has reported mixed findings about class size effects. We used 4th- and 8th-grade data from TIMSS 2003 and 2007 to examine the association between class size and mathematics achievement in public schools in Cyprus. We…
Descriptors: Class Size, Mathematics Achievement, Evidence, International Assessment
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Kozina, Ana – Educational Studies, 2015
In this study, we analyse the predictive power of home and school environment-related factors for determining pupils' aggression. The multiple regression analyses are performed for fourth- and eighth-grade pupils based on the Trends in Mathematics and Science Study (TIMSS) 2007 (N = 8394) and TIMSS 2011 (N = 9415) databases for Slovenia. At the…
Descriptors: Aggression, Elementary Schools, Predictive Validity, Educational Environment
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Kastberg, David; Roey, Stephen; Ferraro, David; Lemanski, Nita; Erberber, Ebru – National Center for Education Statistics, 2013
The "U.S. TIMSS and PIRLS 2011 Technical Report and User's Guide" provides an overview of the design and implementation of the Trends in International Mathematics and Science Study (TIMSS) 2011 and the Progress in International Reading Literacy Study (PIRLS) 2011 in the United States and the nine participating benchmarking states:…
Descriptors: Educational Trends, Mathematics Achievement, Science Achievement, Reading Achievement
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Adzima, Kerry – Journal of School Choice, 2014
As charter school waitlists around the United States continue to grow, it is important to analyze the factors that are possibly attracting parents away from the traditional public school setting and into the charter school system. Using waitlist data from Pennsylvania to proxy for parental valuation, the article examines numerous factors that…
Descriptors: Charter Schools, Parent Attitudes, Performance Factors, Data Analysis
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Pozzoli, Tiziana; Gini, Gianluca – Journal of Early Adolescence, 2013
The authors employed Latane and Darley's model about bystanders' behavior to explain children's active defending and passive bystanding behavior in school bullying. The three central steps of the model were operationalized by measuring provictim attitudes, personal responsibility for intervention, and coping strategies. Moreover, the role of…
Descriptors: Foreign Countries, Bullying, Models, Childhood Attitudes
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