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Doleck, Tenzin; Lemay, David John; Basnet, Ram B.; Bazelais, Paul – Education and Information Technologies, 2020
Large swaths of data are readily available in various fields, and education is no exception. In tandem, the impetus to derive meaningful insights from data gains urgency. Recent advances in deep learning, particularly in the area of voice and image recognition and so-called complete knowledge games like chess, go, and StarCraft, have resulted in a…
Descriptors: Learning Analytics, Prediction, Information Retrieval, Accuracy
Ajao, Adeola; Fitzallen, Noleine; Chick, Helen; Oates, Greg – Mathematics Education Research Group of Australasia, 2023
In this paper, the SOLO taxonomy is used to identify different levels of student understanding of the statistical concepts associated with sampling distribution. This study was part of a research project investigating students' conceptual understanding of concepts of hypothesis testing taught with the support of simulation learning activities. The…
Descriptors: Taxonomy, Statistics Education, Learning Activities, Simulation
Western Interstate Commission for Higher Education, 2023
This report outlines key data elements related to the Western Undergraduate Exchange (WUE), Western Regional Graduate Program (WRGP), and Professional Student Exchange Program (PSEP) for the 2022-23 academic year and is a core resource for policymakers, institutional leaders, counselors and other stakeholders across the region. This report…
Descriptors: Access to Education, Graduate Study, Data, Undergraduate Study
Sisso, Danielle; Bass, Nicole; Williams, Immanuel – Teaching Statistics: An International Journal for Teachers, 2023
This paper provides introductory statistics instructors with the capacity to use engaging National Basketball Association (NBA) data within a web application to either strengthen students' understanding or introduce the concept of variance and one-way analysis of variance. Using engaging data within the classroom provides context to data that…
Descriptors: Statistics Education, Teaching Methods, Statistical Analysis, Introductory Courses
Plak, Simone; van Klaveren, Chris; Cornelisz, Ilja – British Journal of Educational Technology, 2023
Participation in educational activities is an important prerequisite for academic success, yet often proves to be particularly challenging in digital settings. Therefore, this study set out to increase participation in an online proctored formative statistics exam by digital nudging. We exploited targeted nudges based on the Fogg Behaviour Model,…
Descriptors: Learner Engagement, Technology Uses in Education, Cues, Student Motivation
Shao, Lucy; Levine, Richard A.; Guarcello, Maureen A.; Wilke, Morten C.; Stronach, Jeanne; Frazee, James P.; Fan, Juanjuan – International Journal of Artificial Intelligence in Education, 2023
Propensity score matching and weighting methods are applied to balance covariates and reduce selection bias in the analysis of observational study data, and ultimately estimate a treatment effect. We wish to evaluate the impact of a Supplemental Instruction (SI) program on student success in an Introductory Statistics course. In such student…
Descriptors: Statistical Bias, Probability, Scores, Weighted Scores
Kim, Stella Yun; Lee, Won-Chan – Applied Measurement in Education, 2023
This study evaluates various scoring methods including number-correct scoring, IRT theta scoring, and hybrid scoring in terms of scale-score stability over time. A simulation study was conducted to examine the relative performance of five scoring methods in terms of preserving the first two moments of scale scores for a population in a chain of…
Descriptors: Scoring, Comparative Analysis, Item Response Theory, Simulation
Sestir, Marc A.; Kennedy, Lindsay A.; Peszka, Jennifer J.; Bartley, Joanna G. – Teaching of Psychology, 2023
Background: A philosophical shift in statistics regarding emphasis on "New Statistics" (NS; Cumming, G. (2014). The new statistics: Why and how. Psychological Science, 25(1), 7-29.) over conventional null hypothesis significance testing (NHST) raises the question of appropriate material coverage in undergraduate statistics courses.…
Descriptors: Undergraduate Students, Teaching Methods, Statistics Education, Effect Size
Palacios Mena, Nancy; Ariza Bulla, John Fredy – Quality in Higher Education, 2023
This article studies the relationship between the socioeconomic conditions of higher education students in Colombia and their academic performance during the pandemic. The household's socioeconomic conditions are approximated by the education level of the parents, their occupation and the possession of assets. A multiple regression model tests the…
Descriptors: Socioeconomic Status, Academic Achievement, College Students, Foreign Countries
Kaplan, David; Chen, Jianshen; Lyu, Weicong; Yavuz, Sinan – Large-scale Assessments in Education, 2023
The purpose of this paper is to extend and evaluate methods of "Bayesian historical borrowing" applied to longitudinal data with a focus on parameter recovery and predictive performance. Bayesian historical borrowing allows researchers to utilize information from previous data sources and to adjust the extent of borrowing based on the…
Descriptors: Bayesian Statistics, Longitudinal Studies, Children, Surveys
Taback, Nathan; Gibbs, Alison L. – Journal of Statistics and Data Science Education, 2023
Can a "nudge" toward engaging, fun, and useful material improve student attitudes toward statistics? We report on the results of a randomized study to assess the effect of a "nudge" delivered via a weekly E-mail digest on the attitudes of students enrolled in a large introductory statistics course taught in both flipped and…
Descriptors: Student Attitudes, Statistics Education, Electronic Mail, Introductory Courses
Matchett, Andrew – PRIMUS, 2023
This article describes five elementary statistics projects involving the COVID-19 data made available to the public in csv files by the Centers for Disease Control and Prevention. The first project examined data available at the beginning of the COVID surge in New York City in spring, 2020, and used the correlation coefficient to estimate the…
Descriptors: Statistics Education, Student Projects, COVID-19, Pandemics
He, Xiuling; Fang, Jing; Cheng, Hercy N. H.; Men, Qibin; Li, Yangyang – Education and Information Technologies, 2023
A deep understanding of the learning level of online learners is a critical factor in promoting the success of online learning. Using knowledge structures as a way to understand learning can help analyze online students' learning levels. The study used concept maps and clustering analysis to investigate online learners' knowledge structures in a…
Descriptors: Electronic Learning, Cognitive Structures, Concept Mapping, Learning Processes
Rao, V. N. V.; Legacy, Chelsey; Zieffler, Andrew; delMas, Robert – Teaching Statistics: An International Journal for Teachers, 2023
Our complex world requires multivariate reasoning to make sense of reality. Within this paper, we offer a sequence of activities designed to develop multivariate reasoning by explicitly connecting data and visualization. The activities were designed based on a hypothetical learning trajectory we conjectured for students with limited experience…
Descriptors: Statistics Education, Visual Aids, Data Analysis, Faculty Development
Burnham, Ella M.; Blankenship, Erin E.; Brown, Sydney E. – Journal of Statistics and Data Science Education, 2023
We designed an asynchronous undergraduate introductory statistics course that focuses on simulation-based inference at the University of Nebraska-Lincoln. In this article, we describe the process we used to design the course and the structure of the course. We also discuss feedback and comments we received from students on the course evaluations,…
Descriptors: Instructional Design, Introductory Courses, Statistics Education, Online Courses

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