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Ava Greenwood; Sara Davies; Timothy J. McIntyre – Australian Mathematics Education Journal, 2023
This article is motivated by the importance of developing statistically literate students. The authors present a selection of problems that could be used to motivate student interest in probability as well as providing additional depth to the curriculum when used alongside traditional resources. The solutions presented utilise natural frequencies…
Descriptors: Probability, Mathematics Instruction, Teaching Methods, Statistics Education
Peralta, Montserrat; Alarcon, Rosa; Pichara, Karim E.; Mery, Tomas; Cano, Felipe; Bozo, Jorge – IEEE Transactions on Learning Technologies, 2018
Educational resources can be easily found on the Web. Most search engines base their algorithms on a resource's text or popularity, requiring teachers to navigate the results until they find an appropriate resource. This makes searching for resources a tedious and cumbersome task. Specialized repositories contain resources that are annotated with…
Descriptors: Educational Resources, Metadata, Foreign Countries, Bayesian Statistics
Sinharay, Sandip – Grantee Submission, 2018
Producers and consumers of test scores are increasingly concerned about fraudulent behavior before and during the test. There exist several statistical or psychometric methods for detecting fraudulent behavior on tests. This paper provides a review of the Bayesian approaches among them. Four hitherto-unpublished real data examples are provided to…
Descriptors: Ethics, Cheating, Student Behavior, Bayesian Statistics
Uwimpuhwe, Germaine; Singh, Akansha; Higgins, Steve; Coux, Mickael; Xiao, ZhiMin; Shkedy, Ziv; Kasim, Adetayo – Journal of Experimental Education, 2022
Educational stakeholders are keen to know the magnitude and importance of different interventions. However, the way evidence is communicated to support understanding of the effectiveness of an intervention is controversial. Typically studies in education have used the standardised mean difference as a measure of the impact of interventions. This…
Descriptors: Program Effectiveness, Intervention, Multivariate Analysis, Bayesian Statistics
DiCerbo, Kristen – Learning, Media and Technology, 2016
The volume of data that can be captured and stored from students' everyday interactions with digital environments allows for the creation of models of student knowledge, skills, and attributes unobtrusively. However, models and techniques for transforming these data into information that is useful for educators have not been established. This…
Descriptors: Bayesian Statistics, Educational Technology, Electronic Learning, Learning Processes
Phelan, Julia; Ing, Marsha; Nylund-Gibson, Karen; Brown, Richard S. – Journal of STEM Education: Innovations and Research, 2017
This study extends current research by organizing information about students' expectancy-value achievement motivation, in a way that helps parents and teachers identify specific entry points to encourage and support students' science aspirations. This study uses latent class analysis to describe underlying differences in ability beliefs, task…
Descriptors: Self Concept, Science Instruction, Middle School Students, Multivariate Analysis
Stone, Clement A.; Tang, Yun – Practical Assessment, Research & Evaluation, 2013
Propensity score applications are often used to evaluate educational program impact. However, various options are available to estimate both propensity scores and construct comparison groups. This study used a student achievement dataset with commonly available covariates to compare different propensity scoring estimation methods (logistic…
Descriptors: Comparative Analysis, Probability, Sample Size, Program Evaluation
Huang, Jingshan; He, Lei; Davidson-Shivers, Gayle V. – Online Submission, 2011
Effective assessment is vital in educational activities. We propose IWAS (intelligent Web-based assessment system), an intelligent, generalized and real-time system to assess both learning and teaching. IWAS provides a foundation for more efficiency in instructional activities and, ultimately, students' performances. Our contributions are…
Descriptors: Student Evaluation, Educational Assessment, Probability, Internet
Vaughn, Brandon K. – Journal on School Educational Technology, 2008
This study considers the importance of contextual effects on the quality of assessments on item bias and differential item functioning (DIF) in measurement. Often, in educational studies, students are clustered in teachers or schools, and the clusters could impact psychometric issues yet are largely ignored by traditional item analyses. A…
Descriptors: Test Bias, Educational Assessment, Educational Quality, Context Effect
Lecoutre, Marie-Paule; Rovira, Katia; Lecoutre, Bruno; Poitevineau, Jacques – Statistics Education Research Journal, 2006
What people mean by randomness should be taken into account when teaching statistical inference. This experiment explored subjective beliefs about randomness and probability through two successive tasks. Subjects were asked to categorize 16 familiar items: 8 real items from everyday life experiences, and 8 stochastic items involving a repeatable…
Descriptors: Statistical Inference, Probability, Mathematics Instruction, College Mathematics