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Jaylin Lowe; Charlotte Z. Mann; Jiaying Wang; Adam Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2024
Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…
Descriptors: Randomized Controlled Trials, Middle School Mathematics, Middle School Students, Middle Schools
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Wenyi Lu; Joseph Griffin; Troy D. Sadler; James Laffey; Sean P. Goggins – Journal of Learning Analytics, 2025
Game-based learning (GBL) is increasingly recognized as an effective tool for teaching diverse skills, particularly in science education, due to its interactive, engaging, and motivational qualities, along with timely assessments and intelligent feedback. However, more empirical studies are needed to facilitate its wider application in school…
Descriptors: Game Based Learning, Predictor Variables, Evaluation Methods, Educational Games
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Munise Seçkin Kapucu; I?brahim Özcan; Hülya Özcan; Ahmet Aypay – International Journal of Technology in Education and Science, 2024
Our research aims to predict students' academic performance by considering the variables affecting academic performance in science courses using the deep learning method from machine learning algorithms and to determine the importance of independent variables affecting students' academic performance in science courses. 445 students from 5th, 6th,…
Descriptors: Secondary School Students, Science Achievement, Artificial Intelligence, Foreign Countries
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Johnson, Ashleigh M.; Kroshus, Emily; Hafferty, Kiana R.; Senturia, Kirsten; Garrett, Kimberly A.; Tandon, Pooja S. – American Journal of Health Education, 2023
Background: Most United States schools include school-based physical fitness testing (SB-PFT), yet little evidence shows how it is implemented, perceived, and used. Purpose: 1) Explore stakeholders' experiences with SB-PFT; 2) identify: challenges in analyzing fitness data, ways schools can use fitness data, and predictors of meeting fitness…
Descriptors: Physical Fitness, Testing, Middle School Students, Physical Activity Level
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Bowen, Natasha K.; Lucio, Robert; Patak-Pietrafesa, Michele; Bowen, Gary L. – Children & Schools, 2020
To support student success effectively, school teams need information on known predictors of youth behavior and academic performance. In contrast to measures of behavioral and academic outcomes that are commonly relied on in schools, the School Success Profile (SSP) for middle and high school students provides comprehensive information on…
Descriptors: Success, Predictor Variables, Behavior, Expectation
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Ndudi O. Ezeamuzie; Jessica S. C. Leung; Dennis C. L. Fung; Mercy N. Ezeamuzie – Journal of Computer Assisted Learning, 2024
Background: Computational thinking is derived from arguments that the underlying practices in computer science augment problem-solving. Most studies investigated computational thinking development as a function of learners' factors, instructional strategies and learning environment. However, the influence of the wider community such as educational…
Descriptors: Educational Policy, Predictor Variables, Computation, Thinking Skills
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Göktepe Körpeoglu, Seda; Göktepe Yildiz, Sevda – Education and Information Technologies, 2023
Examining students' attitudes towards STEM (science, technology, engineering, and mathematics) fields starting from middle school level is important in their career choices and future planning. However, there is a need to investigate which variables affect students' attitudes towards STEM. Here, we aimed to estimate middle school students'…
Descriptors: Comparative Analysis, Algorithms, Data Collection, Student Attitudes
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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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Yildiz, Muhammed Berke; Börekci, Caner – Journal of Educational Technology and Online Learning, 2020
Education systems produce a large number of valuable data for all stakeholders. The processing of these educational data and making studies on the future of education based on the data reveal highly meaningful results. In this study, an insight was tried to be developed on the educational data collected from ninth-grade students by using data…
Descriptors: Grade Prediction, Academic Achievement, Artificial Intelligence, Grade 9
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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
Adrea J. Truckenmiller; Eunsoo Cho; Gary A. Troia – Grantee Submission, 2022
Although educators frequently use assessment to identify who needs supplemental instruction and if that instruction is working, there is a lack of research investigating assessment that informs what instruction students need. The purpose of the current study was to determine if a brief (approximately 20 min) task that reflects a common middle…
Descriptors: Middle School Teachers, Middle School Students, Test Validity, Writing (Composition)
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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