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Jain, G. Panka; Gurupur, Varadraj P.; Schroeder, Jennifer L.; Faulkenberry, Eileen D. – IEEE Transactions on Learning Technologies, 2014
In this paper, we describe a tool coined as artificial intelligence-based student learning evaluation tool (AISLE). The main purpose of this tool is to improve the use of artificial intelligence techniques in evaluating a student's understanding of a particular topic of study using concept maps. Here, we calculate the probability distribution of…
Descriptors: Artificial Intelligence, Concept Mapping, Teaching Methods, Student Evaluation
Kahle, David – Journal of Statistics Education, 2014
In this article, I introduce a novel applet ("module") for exploring probability distributions, their samples, and various related statistical concepts. The module is primarily designed to be used by the instructor in the introductory course, but it can be used far beyond it as well. It is a free, cross-platform, stand-alone interactive…
Descriptors: Monte Carlo Methods, Learning Modules, Probability, Statistical Distributions
National Center for Education Statistics, 2011
Representative samples of fourth- and eighth-grade public school students from 21 urban districts participated in the 2011 National Assessment of Educational Progress (NAEP) in mathematics. Eighteen of the districts participating in the 2011 NAEP Trial Urban District Assessment (TUDA) participated in earlier assessment years, while three districts…
Descriptors: Achievement Gap, Algebra, Comparative Analysis, Disabilities
National Center for Education Statistics, 2011
Representative samples of fourth- and eighth-grade public school students from 21 urban districts participated in the 2011 National Assessment of Educational Progress (NAEP) in reading. Eighteen of the districts participating in the 2011 NAEP Trial Urban District Assessment (TUDA) participated in earlier assessment years, while three districts…
Descriptors: Achievement Gap, Comparative Analysis, Disabilities, Educational Assessment

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