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Showing 1 to 15 of 16 results Save | Export
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Shao, Lucy; Levine, Richard A.; Guarcello, Maureen A.; Wilke, Morten C.; Stronach, Jeanne; Frazee, James P.; Fan, Juanjuan – International Journal of Artificial Intelligence in Education, 2023
Propensity score matching and weighting methods are applied to balance covariates and reduce selection bias in the analysis of observational study data, and ultimately estimate a treatment effect. We wish to evaluate the impact of a Supplemental Instruction (SI) program on student success in an Introductory Statistics course. In such student…
Descriptors: Statistical Bias, Probability, Scores, Weighted Scores
Schonberg, Christina – Online Submission, 2023
IXL is an end-to-end teaching and learning solution that engages learners in grades Pre-K through 12 with a comprehensive curriculum and a first-of-its-kind assessment suite. A core component of IXL's assessment suite is the IXL Diagnostic, an interim assessment designed by a team of educators and mathematicians that uses Item Response Theory…
Descriptors: Academic Achievement, Achievement Tests, Computer Uses in Education, Elementary School Students
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Käser, Tanja; Schwartz, Daniel L. – International Journal of Artificial Intelligence in Education, 2020
Modeling and predicting student learning in computer-based environments often relies solely on sequences of accuracy data. Previous research suggests that it does not only matter what we learn, but also how we learn. The detection and analysis of learning behavior becomes especially important, when dealing with open-ended exploration environments,…
Descriptors: Inquiry, Learning Strategies, Outcomes of Education, Academic Achievement
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Carly Oddleifson; Stephen Kilgus; David A. Klingbeil; Alexander D. Latham; Jessica S. Kim; Ishan N. Vengurlekar – Grantee Submission, 2025
The purpose of this study was to conduct a conceptual replication of Pendergast et al.'s (2018) study that examined the diagnostic accuracy of a nomogram procedure, also known as a naive Bayesian approach. The specific naive Bayesian approach combined academic and social-emotional and behavioral (SEB) screening data to predict student performance…
Descriptors: Bayesian Statistics, Accuracy, Social Emotional Learning, Diagnostic Tests
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Cohausz, Lea – Journal of Educational Data Mining, 2022
Student success and drop-out predictions have gained increased attention in recent years, connected to the hope that by identifying struggling students, it is possible to intervene and provide early help and design programs based on patterns discovered by the models. Though by now many models exist achieving remarkable accuracy-values, models…
Descriptors: Guidelines, Academic Achievement, Dropouts, Prediction
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Chan, Wendy – Journal of Research on Educational Effectiveness, 2017
Recent methods to improve generalizations from nonrandom samples typically invoke assumptions such as the strong ignorability of sample selection, which is challenging to meet in practice. Although researchers acknowledge the difficulty in meeting this assumption, point estimates are still provided and used without considering alternative…
Descriptors: Generalization, Inferences, Probability, Educational Research
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Callister Everson, Kimberlee; Feinauer, Erika; Sudweeks, Richard R. – Harvard Educational Review, 2013
In this article, the authors provide a methodological critique of the current standard of value-added modeling forwarded in educational policy contexts as a means of measuring teacher effectiveness. Conventional value-added estimates of teacher quality are attempts to determine to what degree a teacher would theoretically contribute, on average,…
Descriptors: Teacher Evaluation, Teacher Effectiveness, Evaluation Methods, Accountability
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Tipton, Elizabeth; Fellers, Lauren; Caverly, Sarah; Vaden-Kiernan, Michael; Borman, Geoffrey; Sullivan, Kate; Ruiz de Castillo, Veronica – Society for Research on Educational Effectiveness, 2015
Randomized experiments are commonly used to evaluate if particular interventions improve student achievement. While these experiments can establish that a treatment actually "causes" changes, typically the participants are not randomly selected from a well-defined population and therefore the results do not readily generalize. Three…
Descriptors: Site Selection, Randomized Controlled Trials, Educational Experiments, Research Methodology
Northwest Evaluation Association, 2014
Recently, the Northwest Evaluation Association (NWEA) completed a study to connect the scale of the North Carolina State End of Grade (EOG) Testing Program used for North Carolina's mathematics and reading assessments with NWEA's Rausch Interval Unit (RIT) scale. Information from the state assessments was used in a study to establish…
Descriptors: Alignment (Education), Testing Programs, Equated Scores, Standard Setting
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Méndez, Gonzalo; Ochoa, Xavier; Chiluiza, Katherine; de Wever, Bram – Journal of Learning Analytics, 2014
Learning analytics has been as used a tool to improve the learning process mainly at the micro-level (courses and activities). However, another of the key promises of learning analytics research is to create tools that could help educational institutions at the meso- and macro-level to gain better insight into the inner workings of their programs…
Descriptors: Data Analysis, Data Collection, Educational Research, Curriculum Design
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Heinrich, Carolyn J.; Nisar, Hiren – American Educational Research Journal, 2013
School districts required under No Child Left Behind (NCLB) to provide supplemental educational services (SES) to students in schools that are not making adequate yearly progress rely heavily on the private sector to offer choice in services. If the market does not drive out ineffective providers, students may not gain through SES participation.…
Descriptors: Federal Legislation, Educational Legislation, Educational Indicators, Federal Programs
Wilson, Jennifer L. – ProQuest LLC, 2010
The study analyzed 2005 posttest data compared to 2008 posttest data to determine student end of school year academic achievement outcomes across three academic levels (above average, average, and below average chemistry potential) and two teacher homework evaluation methods (assigned but not graded and assigned and graded) on teacher prepared…
Descriptors: Outcomes of Education, Test Results, Graduation Requirements, Program Effectiveness
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Rutkowski, Leslie; Gonzalez, Eugenio; Joncas, Marc; von Davier, Matthias – Educational Researcher, 2010
The technical complexities and sheer size of international large-scale assessment (LSA) databases often cause hesitation on the part of the applied researcher interested in analyzing them. Further, inappropriate choice or application of statistical methods is a common problem in applied research using these databases. This article serves as a…
Descriptors: Research Methodology, Measures (Individuals), Data Analysis, Databases
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Wendt, Heike; Bos, Wilfried; Goy, Martin – Educational Research and Evaluation, 2011
Several current international comparative large-scale assessments of educational achievement (ICLSA) make use of "Rasch models", to address functions essential for valid cross-cultural comparisons. From a historical perspective, ICLSA and Georg Rasch's "models for measurement" emerged at about the same time, half a century ago. However, the…
Descriptors: Measures (Individuals), Test Theory, Group Testing, Educational Testing
Allen, Jeff; Sconing, Jim – American College Testing (ACT), Inc., 2005
In this report, we establish benchmarks of readiness for four common first-year college courses: English Composition, College Algebra, Social Science, and Biology. Using grade data from a large sample of colleges, we modeled the probability of success in these courses as a function of ACT test scores. Success was defined as a course grade of B or…
Descriptors: Probability, Biology, Social Sciences, Scores
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