NotesFAQContact Us
Collection
Advanced
Search Tips
Laws, Policies, & Programs
Showing 61 to 75 of 497 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Hemer, David – Australian Mathematics Education Journal, 2020
This paper describes an investigation looking at the underlying mathematics of poker machines. The aim of the investigation is for students to get an appreciation of how poker machines are designed to ensure that in the long-term players will inevitably lose when playing. The first part of this paper describes how students can model a simple poker…
Descriptors: Equipment, Probability, Games, Mathematics Instruction
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Al Farra, Nabil Kamal; Al Owais, Najla Sultan; Belbase, Shashidhar – Mathematics Teaching Research Journal, 2022
The purpose of this study was to analyze the problem-solving techniques that students in a fifth-grade classroom applied while solving mathematical word problems. Fifth-grade students in a private school with Ministry of Education curricula in Al Ain, Abu Dhabi, were given a set of 15-word problems to solve with detailed justifications. The…
Descriptors: Foreign Countries, Mathematics Instruction, Problem Solving, Word Problems (Mathematics)
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Liebscher, Eckhard; Michael, Ben – International Electronic Journal of Mathematics Education, 2019
In the paper a software solution is presented for the generation of instances of exercises. The focus is on education in mathematics but the approach can be adopted in other fields such as computer science and natural science. The present solution uses the R environment for the generation process and LaTeX for the content presentation. In the…
Descriptors: Mathematics Instruction, Electronic Learning, Integrated Learning Systems, Probability
Peer reviewed Peer reviewed
Direct linkDirect link
Leite, Walter L.; Aydin, Burak; Gurel, Sungur – Journal of Experimental Education, 2019
This Monte Carlo simulation study compares methods to estimate the effects of programs with multiple versions when assignment of individuals to program version is not random. These methods use generalized propensity scores, which are predicted probabilities of receiving a particular level of the treatment conditional on covariates, to remove…
Descriptors: Probability, Weighted Scores, Monte Carlo Methods, Statistical Bias
Peer reviewed Peer reviewed
Direct linkDirect link
Smith, Bevan I.; Chimedza, Charles; Bührmann, Jacoba H. – International Journal of Artificial Intelligence in Education, 2020
Identifying students at risk of failing a course has potential benefits, such as recommending the At-Risk students to various interventions that could improve pass rates. The challenges however, are firstly in measuring how effective these interventions are, i.e. measuring treatment effects, and secondly, to not only predict overall (average)…
Descriptors: Artificial Intelligence, Man Machine Systems, Probability, Scoring
Paul T. von Hippel; Laura Bellows – Annenberg Institute for School Reform at Brown University, 2020
At least sixteen US states have taken steps toward holding teacher preparation programs (TPPs) accountable for teacher value-added to student test scores. Yet it is unclear whether teacher quality differences between TPPs are large enough to make an accountability system worthwhile. Several statistical practices can make differences between TPPs…
Descriptors: Teacher Effectiveness, Teacher Education Programs, Scores, Accountability
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Marcoulides, Katerina M. – Measurement: Interdisciplinary Research and Perspectives, 2018
This study examined the use of Bayesian analysis methods for the estimation of item parameters in a two-parameter logistic item response theory model. Using simulated data under various design conditions with both informative and non-informative priors, the parameter recovery of Bayesian analysis methods were examined. Overall results showed that…
Descriptors: Bayesian Statistics, Item Response Theory, Probability, Difficulty Level
Peer reviewed Peer reviewed
Direct linkDirect link
Kupzyk, Kevin A.; Beal, Sarah J. – Journal of Early Adolescence, 2017
In order to investigate causality in situations where random assignment is not possible, propensity scores can be used in regression adjustment, stratification, inverse-probability treatment weighting, or matching. The basic concepts behind propensity scores have been extensively described. When data are longitudinal or missing, the estimation and…
Descriptors: Probability, Longitudinal Studies, Data, Computation
Peer reviewed Peer reviewed
Direct linkDirect link
McNeish, Daniel – Journal of Experimental Education, 2018
Some IRT models can be equivalently modeled in alternative frameworks such as logistic regression. Logistic regression can also model time-to-event data, which concerns the probability of an event occurring over time. Using the relation between time-to-event models and logistic regression and the relation between logistic regression and IRT, this…
Descriptors: Measures (Individuals), Nonparametric Statistics, Item Response Theory, Regression (Statistics)
Peer reviewed Peer reviewed
Direct linkDirect link
McCartney, Mark – International Journal of Mathematical Education in Science and Technology, 2017
A number of probabilistic experiments are described to estimate e, p and v2, with results from computer simulations being used to investigate convergence. A number of possible classroom exercises and extensions are presented.
Descriptors: Probability, Mathematics Instruction, Computer Simulation, Teaching Methods
Peer reviewed Peer reviewed
Direct linkDirect link
Quane, Kate; Brown, Leni – Australian Primary Mathematics Classroom, 2022
Mathematics educators and researchers have advocated for the use of manipulatives to teach mathematics for decades. The purpose of this article is to provide illustrative uses of a readily available manipulative rather than a complete list. From an Australian perspective, Pop-it fidget toys can be used across the mathematics curriculum. This paper…
Descriptors: Mathematics Instruction, Toys, Manipulative Materials, Foreign Countries
Bishop, Crystal D.; Leite, Walter L.; Snyder, Patricia A. – Journal of Early Intervention, 2018
Data sets from large-scale longitudinal surveys involving young children and families have become available for secondary analysis by researchers in a variety of fields. Researchers in early intervention have conducted secondary analyses of such data sets to explore relationships between nonmalleable and malleable factors and child outcomes, and…
Descriptors: Probability, Weighted Scores, Statistical Bias, Data Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Stohlman, Micah – Australian Mathematics Teacher, 2018
The Price is Right Bidder's Row and games provide many opportunities for mathematical connections. The Price is Right website has videos or pictures for students to see how each game is played (http://www.priceisright.com/games/). This article will describe the mathematics of probability and statistics that is integrated in the famous television…
Descriptors: Mathematics Education, Mathematics Instruction, Teaching Methods, Games
Peer reviewed Peer reviewed
Direct linkDirect link
Henson, Robert; DiBello, Lou; Stout, Bill – Measurement: Interdisciplinary Research and Perspectives, 2018
Diagnostic classification models (DCMs, also known as cognitive diagnosis models) hold the promise of providing detailed classroom information about the skills a student has or has not mastered. Specifically, DCMs are special cases of constrained latent class models where classes are defined based on mastery/nonmastery of a set of attributes (or…
Descriptors: Classification, Diagnostic Tests, Models, Mastery Learning
Pages: 1  |  2  |  3  |  4  |  5  |  6  |  7  |  8  |  9  |  10  |  11  |  ...  |  34