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Thomas, Debra Kelly; Milenkovic, Lisa; Marousky, Annamargareth – Science and Children, 2019
Computer science (CS) and computational thinking (a problem-solving process used by computer scientists) teach students design, logical reasoning, and problem solving--skills that are valuable in life and in any career. Computational thinking (CT) concepts such as decomposition teach students how to break down and tackle a large complex problem.…
Descriptors: Computation, Thinking Skills, Computer Simulation, Computer Science Education
Office of Educational Technology, US Department of Education, 2019
To help teachers implement new, research-based approaches for leveraging technology to improve science, technology, engineering and mathematics (STEM) learning, a systematic review of the research literature on the impact of integrating innovative digital technology in STEM and computer science curricula and classrooms was conducted. For purposes…
Descriptors: STEM Education, Educational Technology, Technology Uses in Education, Teaching Methods
Jacksonville Public Education Fund, 2014
School grades were introduced in Florida in 1999, the first such A-F model for reporting on school accountability in the nation. The purpose of school grades was to make it easy for parents and citizens to understand and compare how schools were performing academically, and to compel low-performing schools to improve. Since then, the A-F grades…
Descriptors: Grades (Scholastic), Grading, Scoring Formulas, Student Evaluation
Kessler, Lawrence M. – ProQuest LLC, 2013
In this paper I propose Bayesian estimation of a nonlinear panel data model with a fractional dependent variable (bounded between 0 and 1). Specifically, I estimate a panel data fractional probit model which takes into account the bounded nature of the fractional response variable. I outline estimation under the assumption of strict exogeneity as…
Descriptors: Bayesian Statistics, Computation, Data, Models
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Johnson, Matthew T.; Lipscomb, Stephen; Gill, Brian – Journal of Research on Educational Effectiveness, 2015
Teacher value-added models (VAMs) must isolate teachers' contributions to student achievement to be valid. Well-known VAMs use different specifications, however, leaving policymakers with little clear guidance for constructing a valid model. We examine the sensitivity of teacher value-added estimates under different models based on whether they…
Descriptors: Teacher Effectiveness, Teacher Influence, Academic Achievement, Models
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Li, Feiming; Cohen, Allan S.; Kim, Seock-Ho; Cho, Sun-Joo – Applied Psychological Measurement, 2009
This study examines model selection indices for use with dichotomous mixture item response theory (IRT) models. Five indices are considered: Akaike's information coefficient (AIC), Bayesian information coefficient (BIC), deviance information coefficient (DIC), pseudo-Bayes factor (PsBF), and posterior predictive model checks (PPMC). The five…
Descriptors: Item Response Theory, Models, Selection, Methods
Lipscomb, Stephen; Teh, Bing-ru; Gill, Brian; Chiang, Hanley; Owens, Antoniya – Mathematica Policy Research, Inc., 2010
This report summarizes research findings and implementation practices for teacher and principal value-added models (VAMs), as a first step in the Team Pennsylvania Foundation's (Team PA) pilot project to inform the development of a full, statewide model evaluation system. We have selected 21 studies that represent key issues and findings in the…
Descriptors: Pilot Projects, Outcomes of Education, Principals, Models
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Brenner, James R. – Chemical Engineering Education, 2007
At Florida Tech, we have incorporated DataFit from Oakdale Engineering throughout the entire curriculum, beginning with ChE 1102, an eight-week, one-day-per-week, two-hour, one-credit-hour, second-semester Introduction to Chemical Engineering course in a hands-on computer classroom. Our experience is that students retain data analysis concepts…
Descriptors: Chemical Engineering, Data Analysis, Curriculum, Introductory Courses