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Showing 1 to 15 of 37 results Save | Export
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J. S. Allison; L. Santana; I. J. H. Visagie – Teaching Statistics: An International Journal for Teachers, 2025
Given sample data, how do you calculate the value of a parameter? While this question is impossible to answer, it is frequently encountered in statistics classes when students are introduced to the distinction between a sample and a population (or between a statistic and a parameter). It is not uncommon for teachers of statistics to also confuse…
Descriptors: Statistics Education, Teaching Methods, Computation, Sampling
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Burke, Jon; Goukasian, Levon; Shearer, Robert – Journal of Statistics Education, 2020
Students often struggle with the concept of dependence of events or random variables. We present a simple coin flipping game that yields surprising results due to the dependencies within the game. The game is simple enough for young children to understand and play, yet complex enough to yield results that are counterintuitive to even most graduate…
Descriptors: Statistics Education, Teaching Methods, Games, Problem Solving
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Holman, Justin O.; Hacherl, Allie – Journal of Statistics and Data Science Education, 2023
It has become increasingly important for future business professionals to understand statistical computing methods as data science has gained widespread use in contemporary organizational decision processes in recent years. Used by scores of academics and practitioners in a variety of fields, Monte Carlo simulation is one of the most broadly…
Descriptors: Teaching Methods, Monte Carlo Methods, Programming Languages, Statistics Education
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Seebut, Supot; Wongsason, Patcharee; Kim, Dojin; Putjuso, Thanin; Boonpok, Chawalit – EURASIA Journal of Mathematics, Science and Technology Education, 2022
Simulation modeling is an effective tool for solving problems that cannot be explained analytically or when data cannot be collected. This is done by simulating the observed behavior of a problem under study using a computer program. In math education, this can develop knowledge and fundamental competencies of simulation modeling at a higher level…
Descriptors: Programming Languages, Mathematics Instruction, Grade 12, Secondary School Students
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Pavel Chernyavskiy; Traci S. Kutaka; Carson Keeter; Julie Sarama; Douglas Clements – Grantee Submission, 2024
When researchers code behavior that is undetectable or falls outside of the validated ordinal scale, the resultant outcomes often suffer from informative missingness. Incorrect analysis of such data can lead to biased arguments around efficacy and effectiveness in the context of experimental and intervention research. Here, we detail a new…
Descriptors: Bayesian Statistics, Mathematics Instruction, Learning Trajectories, Item Response Theory
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Šedivá, Blanka – International Journal for Technology in Mathematics Education, 2019
The Monte Carlo method is one of the basic simulation statistical methods which can be used both to demonstrate basic probability and statistical concepts as well as to analyse the behaviour stochastic models. The introduction part of the article provides a brief description of the Monte Carlo method. The main part of the article is concentrated…
Descriptors: Simulation, Monte Carlo Methods, Teaching Methods, Mathematics Instruction
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Ross, Matthew M.; Wright, A. Michelle – Journal of Education for Business, 2022
We use Markov chain Monte Carlo (MCMC) analysis to construct a three-question math quiz to assess key skills needed for introductory finance. We begin with data collected from a ten-question criterion-referenced math quiz given to 314 undergraduates on the first day of class. MCMC indicates the top three questions for predicting overall course…
Descriptors: Mathematics Tests, Markov Processes, Monte Carlo Methods, Introductory Courses
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Albert, Daniel R. – Journal of Chemical Education, 2020
Monte Carlo simulations for uncertainty propagation take as inputs the uncertainty distribution for each variable and an equation for the calculation of a desired quantity. The desired quantity is then calculated by randomly drawing from the specified uncertainty distributions of the input variables. This calculation is then repeated many times…
Descriptors: Monte Carlo Methods, Science Instruction, Measurement, Undergraduate Students
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Paulsen, Justin; Valdivia, Dubravka Svetina – Journal of Experimental Education, 2022
Cognitive diagnostic models (CDMs) are a family of psychometric models designed to provide categorical classifications for multiple latent attributes. CDMs provide more granular evidence than other psychometric models and have potential for guiding teaching and learning decisions in the classroom. However, CDMs have primarily been conducted using…
Descriptors: Psychometrics, Classification, Teaching Methods, Learning Processes
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Smith, Ben O.; Wagner, Jamie – Journal of Economic Education, 2018
In 2016, Walstad and Wagner developed a procedure to split pre-test and post-test responses into four learning types: positive, negative, retained, and zero learning. This disaggregation is not only useful in academic studies; but also provides valuable insight to the practitioner: an instructor would take different mitigating actions in response…
Descriptors: Pretests Posttests, Value Added Models, Guessing (Tests), Monte Carlo Methods
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Meyburg, Jan Philipp; Diesing, Detlef – Journal of Chemical Education, 2017
This article describes the implementation and application of a metal deposition and surface diffusion Monte Carlo simulation in a physical chemistry lab course. Here the self-diffusion of Ag atoms on a Ag(111) surface is modeled and compared to published experimental results. Both the thin-film homoepitaxial growth during adatom deposition onto a…
Descriptors: Monte Carlo Methods, Computer Simulation, Chemistry, Laboratory Experiments
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Sharda, Vandana; Sastri, O. S. K. S.; Bhardwaj, Jyoti; Jha, Arbind K. – Physics Education, 2016
In this paper, we present a simple spreadsheet based simulation activity that can be performed by students at the undergraduate level. This simulation is implemented in free open source software (FOSS) LibreOffice Calc, which is available for both Windows and Linux platform. This activity aims at building the probability distribution for the…
Descriptors: Computer Simulation, Spreadsheets, Concept Teaching, Scientific Concepts
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Michalenko, Joshua J.; Lan, Andrew S.; Waters, Andrew E.; Grimaldi, Philip J.; Baraniuk, Richard G. – International Educational Data Mining Society, 2017
An important, yet largely unstudied problem in student data analysis is to detect "misconceptions" from students' responses to "open-response" questions. Misconception detection enables instructors to deliver more targeted feedback on the misconceptions exhibited by many students in their class, thus improving the quality of…
Descriptors: Data Analysis, Misconceptions, Student Attitudes, Feedback (Response)
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Belland, Brian R.; Walker, Andrew E.; Kim, Nam Ju – Review of Educational Research, 2017
Computer-based scaffolding provides temporary support that enables students to participate in and become more proficient at complex skills like problem solving, argumentation, and evaluation. While meta-analyses have addressed between-subject differences on cognitive outcomes resulting from scaffolding, none has addressed within-subject gains.…
Descriptors: Bayesian Statistics, Meta Analysis, STEM Education, Computer Assisted Instruction
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Geerts, Walter M.; Steenbeek, Henderien W.; van Geert, Paul L. C. – International Education Studies, 2018
Video footage is frequently used at teacher education. According to Sherin and Dyer (2017), this is often done in a way that contradicts recent studies. According to them, video is suitable for observing and interpreting interactions in the classroom. This contributes to their situated knowledge, which allows expert teachers to act intuitively,…
Descriptors: Video Technology, Teacher Education Programs, Preservice Teachers, Educational Technology
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