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Justice, Nicola; Le, Laura; Sabbag, Anelise; Fry, Elizabeth; Ziegler, Laura; Garfield, Joan – Journal of Statistics Education, 2020
One of the first simulation-based introductory statistics curricula to be developed was the NSF-funded Change Agents for Teaching and Learning Statistics curriculum. True to its name, this curriculum is constantly undergoing change. This article describes the story of the curriculum as it has evolved at the University of Minnesota and offers…
Descriptors: Statistics, College Mathematics, Simulation, Introductory Courses
Hurtado, Orlando Garcia; Camargo, Julian; Díaz, Miguel – Journal of Language and Linguistic Studies, 2022
This article shows results on the simulation of partial differential equations such as the heat equation, the Laplace equation and the wave equation in a course called mathematical methods at a university in Bogotá Colombia. In this course, the concept of partial differential equations and different solution methods were explained to them, both in…
Descriptors: Mathematics Instruction, Teaching Methods, Calculus, Equations (Mathematics)
Busrah, Zulfiqar; Pathuddin, Hikmawati – Journal of Research and Advances in Mathematics Education, 2021
Ethnomathematics can empirically improve the cognitive abilities of students in elementary and secondary schools. However, in undergraduate study, there are still limited studies on integrating ethnomathematics in learning resources. This study aims to apply interpolation in modelling polynomial functions and integral volume on the shape of…
Descriptors: Foreign Countries, Ethnography, Mathematics Education, College Mathematics
Chance, Beth; Tintle, Nathan; Reynolds, Shea; Patel, Ajay; Chan, Katherine; Leader, Sean – Statistics Education Research Journal, 2022
Using simulation-based inference (SBI), such as randomization tests, as the primary vehicle for introducing students to the logic and scope of statistical inference has been advocated with the potential of improving student understanding of statistical inference and the statistical investigative process. Moving beyond the individual class…
Descriptors: Mathematics Curriculum, Simulation, Student Characteristics, Prior Learning
Tintle, Nathan; Clark, Jake; Fischer, Karen; Chance, Beth; Cobb, George; Roy, Soma; Swanson, Todd; VanderStoep, Jill – Journal of Statistics Education, 2018
The recent simulation-based inference (SBI) movement in algebra-based introductory statistics courses (Stat 101) has provided preliminary evidence of improved student conceptual understanding and retention. However, little is known about whether these positive effects are preferentially distributed across types of students entering the course. We…
Descriptors: Statistics, College Mathematics, College Preparation, Mathematical Concepts
Backman, Matthew D.; Delmas, Robert C.; Garfield, Joan – Statistics Education Research Journal, 2017
Cognitive transfer is the ability to apply learned skills and knowledge to new applications and contexts. This investigation evaluates cognitive transfer outcomes for a tertiary-level introductory statistics course using the CATALST curriculum, which exclusively used simulation-based methods to develop foundations of statistical inference. A…
Descriptors: Introductory Courses, Statistics, Mathematics Instruction, Simulation
Tague, Jenna; Joseph, Manjula Peter; Zhang, Pingping – North American Chapter of the International Group for the Psychology of Mathematics Education, 2017
The focus of the current proposal is to examine the effect of two dynamic simulations on the participants' conceptions of rate of change. Conceptions of rate of change were measured according to Carlson et al.'s (2002) Mental Actions framework and how the participants related the physical simulations to the graphical representations (Heid, et al.,…
Descriptors: Simulation, Mental Computation, Algebra, Mathematical Logic
Ruggieri, Eric – PRIMUS, 2016
The Central Limit Theorem is one of the most important concepts taught in an introductory statistics course, however, it may be the least understood by students. Sure, students can plug numbers into a formula and solve problems, but conceptually, do they really understand what the Central Limit Theorem is saying? This paper describes a simulation…
Descriptors: College Mathematics, Mathematics Instruction, Undergraduate Study, Mathematical Logic
Chance, Beth; Wong, Jimmy; Tintle, Nathan – Journal of Statistics Education, 2016
"Simulation-based inference" (e.g., bootstrapping and randomization tests) has been advocated recently with the goal of improving student understanding of statistical inference, as well as the statistical investigative process as a whole. Preliminary assessment data have been largely positive. This article describes the analysis of the…
Descriptors: Statistical Inference, Simulation, College Mathematics, Statistics
Axvig, Nathan; David, John; Falcetti, Alex – PRIMUS, 2015
The Applied and Industrial Mathematics program partners applied mathematics students with businesses, governments, laboratories, and agencies to solve real problems. We will discuss the logistics of the program and give advice on starting and running similar programs. We also give a detailed example of a specific project, namely our work with the…
Descriptors: Mathematics Instruction, Undergraduate Study, College Mathematics, Problem Solving
McLean, Jeffrey A.; Doerr, Helen M. – North American Chapter of the International Group for the Psychology of Mathematics Education, 2015
This study focuses on the development of four tertiary introductory statistics students' informal inferential reasoning while engaging in data driven repeated sampling and resampling activities. Through the use of hands-on manipulatives and simulations with technology, the participants constructed empirical sampling distributions in order to…
Descriptors: College Mathematics, College Students, Statistics, Statistical Inference
Caudle, Kyle A.; Ruth, David M. – Journal of Computers in Mathematics and Science Teaching, 2013
Teaching undergraduates the basic properties of an estimator can be difficult. Most definitions are easy enough to comprehend, but difficulties often lie in gaining a "good feel" for these properties and why one property might be more desired as compared to another property. Simulations which involve visualization of these properties can…
Descriptors: Computation, Statistics, College Mathematics, Mathematics Instruction
Price, James C. – PRIMUS, 2015
This article presents four inquiry-based learning activities developed for a liberal arts math course. The activities cover four topics: the Pythagorean theorem, interest theory, optimization, and the Monty Hall problem. Each activity consists of a dialogue, with a theme and characters related to the topic, and a manipulative, that allow students…
Descriptors: Inquiry, Active Learning, Learning Activities, Mathematics Instruction
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
Lu, Yun; Vasko, Francis J.; Drummond, Trevor J.; Vasko, Lisa E. – Mathematics Teacher, 2014
If the prospective students of probability lack a background in mathematical proofs, hands-on classroom activities may work well to help them to learn to analyze problems correctly. For example, students may physically roll a die twice to count and compare the frequency of the sequences. Tools such as graphing calculators or Microsoft Excel®…
Descriptors: Probability, Mathematical Logic, Validity, Heuristics

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