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Hancock, Stacey A.; Rummerfield, Wendy – Journal of Statistics Education, 2020
Sampling distributions are fundamental to an understanding of statistical inference, yet research shows that students in introductory statistics courses tend to have multiple misconceptions of this important concept. A common instructional method used to address these misconceptions is computer simulation, often preceded by hands-on simulation…
Descriptors: Teaching Methods, Sampling, Experiential Learning, Computer Simulation
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Takkaç Tulgar, Aysegül; Yilmaz, Rabia Meryem; Topu, Fatma Burcu – Participatory Educational Research, 2022
The main aim of this research is to display research trends in studies on augmented reality (AR) in teaching English as a foreign language by using bibliometric mapping and content analysis. For this purpose, 64 studies in total published up to 2019 were accessed for bibliometric analysis. In addition, 49 articles published between 2007 and 2019…
Descriptors: Technology Uses in Education, Computer Simulation, Educational Technology, Second Language Instruction
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Lane, David M. – Journal of Statistics Education, 2015
Recently Watkins, Bargagliotti, and Franklin (2014) discovered that simulations of the sampling distribution of the mean can mislead students into concluding that the mean of the sampling distribution of the mean depends on sample size. This potential error arises from the fact that the mean of a simulated sampling distribution will tend to be…
Descriptors: Statistical Distributions, Sampling, Sample Size, Misconceptions
Gillespie, Steven – ProQuest LLC, 2013
The primary purpose of this quantitative study was to examine if simulation training correlated with the decision-making abilities of firefighters from two departments (one in a mountain state and one in a southwest state). The other purposes were to determine if firefighter demographics were correlated with the completion of the simulation…
Descriptors: Fire Protection, Fire Science Education, Training, Simulation
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Watkins, Ann E.; Bargagliotti, Anna; Franklin, Christine – Journal of Statistics Education, 2014
Although the use of simulation to teach the sampling distribution of the mean is meant to provide students with sound conceptual understanding, it may lead them astray. We discuss a misunderstanding that can be introduced or reinforced when students who intuitively understand that "bigger samples are better" conduct a simulation to…
Descriptors: Simulation, Sampling, Sample Size, Misconceptions
Conley, Quincy – ProQuest LLC, 2013
Statistics is taught at every level of education, yet teachers often have to assume their students have no knowledge of statistics and start from scratch each time they set out to teach statistics. The motivation for this experimental study comes from interest in exploring educational applications of augmented reality (AR) delivered via mobile…
Descriptors: Statistics, Mathematics Instruction, Simulated Environment, Computer Simulation
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Arnold, Pip; Pfannkuch, Maxine; Wild, Chris J.; Regan, Matt; Budgett, Stephanie – Journal of Statistics Education, 2011
Computer simulations and animations for developing statistical concepts are often not understood by beginners. Hands-on physical simulations that morph into computer simulations are teaching approaches that can build students' concepts. In this paper we review the literature on visual and verbal cognitive processing and on the efficacy of…
Descriptors: Foreign Countries, Statistics, Learning Theories, Cues
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Chau, Chak-Tong – Research in Higher Education, 1997
A study tested a resampling methodology (bootstrap simulation) by examining the effects of class size and student motivation on students' ratings of teaching effectiveness. Results suggest that evaluations based on student ratings should look at more than class averages, and that class size and student motivation affect overall ratings. Examples…
Descriptors: Class Size, College Instruction, Higher Education, Institutional Research