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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
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
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
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
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
Stewart, Wayne; Stewart, Sepideh – PRIMUS, 2014
For many scientists, researchers and students Markov chain Monte Carlo (MCMC) simulation is an important and necessary tool to perform Bayesian analyses. The simulation is often presented as a mathematical algorithm and then translated into an appropriate computer program. However, this can result in overlooking the fundamental and deeper…
Descriptors: Markov Processes, Monte Carlo Methods, College Mathematics, Mathematics Instruction
Carver, Andrew B. – Decision Sciences Journal of Innovative Education, 2013
Equity Indexed Annuities (EIAs) are controversial financial products because the payoffs to investors are based on formulas that are supposedly too complex for average investors to understand. This brief describes how Monte Carlo simulation can provide insight into the true risk and return of an EIA. This approach can be used as a project…
Descriptors: Monte Carlo Methods, Investigations, Financial Services, Simulation
Mallavarapu, Aditi; Lyons, Leilah; Shelley, Tia; Minor, Emily; Slattery, Brian; Zellner, Moria – Journal of Educational Data Mining, 2015
Interactive learning environments can provide learners with opportunities to explore rich, real-world problem spaces, but the nature of these problem spaces can make assessing learner progress difficult. Such assessment can be useful for providing formative and summative feedback to the learners, to educators, and to the designers of the…
Descriptors: Spatial Ability, Urban Areas, Neighborhoods, Conservation (Environment)
Morio, Jerome – European Journal of Physics, 2011
Sensitivity analysis is the study of how the different input variations of a mathematical model influence the variability of its output. In this paper, we review the principle of global and local sensitivity analyses of a complex black-box system. A simulated case of application is given at the end of this paper to compare both approaches.…
Descriptors: Mathematical Models, Models, Teaching Methods, Comparative Analysis
Selvanathan, Rani G. – International Journal of Higher Education, 2013
There are many definitions that are attributable to the meaning of sustainability. Sustainability can be viewed as long-lasting, effective result of a project, venture, action, or investment without consuming additional future resources. Because of the wide nature of its applicability, a universal measure of sustainability is hard to come by. This…
Descriptors: Sustainability, Educational Development, Educational Change, Models
Morio, Jerome; Pastel, Rudy; Le Gland, Francois – European Journal of Physics, 2010
Monte Carlo simulations are a classical tool to analyse physical systems. When unlikely events are to be simulated, the importance sampling technique is often used instead of Monte Carlo. Importance sampling has some drawbacks when the problem dimensionality is high or when the optimal importance sampling density is complex to obtain. In this…
Descriptors: Science Instruction, Physics, Simulation, Sampling
Tolvanen, Asko; Kiuru, Noona; Leskinen, Esko; Hakkarainen, Kai; Inkinen, Mikko; Lonka, Kirsti; Salmela-Aro, Katariina – International Journal of Behavioral Development, 2011
This study presents a new approach to estimation of a nonlinear growth curve component with fixed and random effects in multilevel modeling. This approach can be used to estimate change in longitudinal data, such as day-of-the-week fluctuation. The motivation of the new approach is to avoid spurious estimates in a random coefficient regression…
Descriptors: Monte Carlo Methods, Computation, Longitudinal Studies, Teaching Methods
Capizzo, M. C.; Sperandeo-Mineo, R. M.; Zarcone, M. – European Journal of Physics, 2008
We present a pedagogic approach aimed at modelling electric conduction in semiconductors in order to describe and explain some macroscopic properties, such as the characteristic behaviour of resistance as a function of temperature. A simple model of the band structure is adopted for the generation of electron-hole pairs as well as for the carrier…
Descriptors: Teaching Methods, Science Instruction, Laboratory Equipment, Science Experiments

Huck, Schuyler W.; And Others – Journal of Educational Statistics, 1985
Classroom demonstrations can help students gain insights into statistical concepts and phenomena. After discussing four kinds of demonstrations, the authors present three possible approaches for determining how much data are needed for the demonstration to have a reasonable probability for success. (Author/LMO)
Descriptors: Computer Simulation, Demonstrations (Educational), Higher Education, Monte Carlo Methods

Newell, G. J.; MacFarlane, J. D. – Australian Mathematics Teacher, 1985
Presents sports-oriented examples (cricket and football) in which Monte Carlo methods are used on microcomputers to teach probability concepts. Both examples include computer programs (with listings) which utilize the microcomputer's random number generator. Instructional strategies, with further challenges to help students understand the role of…
Descriptors: Computer Simulation, Computer Software, Estimation (Mathematics), Mathematics Education
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