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Madison Fansher; Logan Walls; Chenxu Hao; Hari Subramonyam; Aysecan Boduroglu; Priti Shah; Jessica K. Witt – Cognitive Research: Principles and Implications, 2025
In contexts where people lack prior knowledge and risk awareness--such as the COVID-19 pandemic--even truthful visualizations of data can seem surprising. This can lead people to mistrust the veracity of the data and to discount it, leading to poor risk decisions. In this work, we illustrate how narrative visualizations can achieve a balance…
Descriptors: Visualization, Trust (Psychology), Data, Credibility
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Peter K. Dunn – International Journal of Mathematical Education in Science and Technology, 2024
The use of group work projects is common in introductory statistics courses, including projects where students collect their own data. However, the COVID-induced lockdown at the start of 2020 meant that data collection was compromised. In this study, we examine a situation where students were permitted to use artificial (made-up) data for their…
Descriptors: Student Projects, Undergraduate Students, Statistics Education, COVID-19
Nancy Smith; Claus von Zastrow – Education Commission of the States, 2022
When the COVID-19 pandemic drove schools online in March 2020, state education leaders were left without access to data needed to understand how best to support students. The pandemic revealed the strengths and limitations of state education data systems while inspiring new strategies for collecting, reporting and using data. In 2021, DataSmith…
Descriptors: State Departments of Education, Data, Data Collection, Pandemics
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Berg, Arthur; Hawila, Nour – Teaching Statistics: An International Journal for Teachers, 2021
This article is presented in two parts: in the first part we discuss the use of R and R-related tools when implementing a data science curriculum in the classroom and direct readers to helpful R resources in education, and in the second part, we demonstrate the use of R in exploring COVID-19 data. In particular, we explore ethnic/racial…
Descriptors: Data, Data Analysis, Programming Languages, COVID-19
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Syahrul Amin; Karen E. Rambo-Hernandez; Blaine A. Pedersen; Camille S. Burnett; Bimal P. Nepal; Noemi V. Mendoza Diaz – Cogent Education, 2024
This study examined the persistence of first-year engineering students at a Hispanic-Serving Institution (HSI) and a Historically Black College and University (HBCU) pre- and mid-COVID-19 interruptions and whether their characteristics (race/ethnicity, financial need status, first-generation status, SAT scores) predicted their persistence. Using…
Descriptors: College Freshmen, Engineering Education, Academic Persistence, COVID-19
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Andrew Pendola; David T. Marshall; Tim Pressley; Deja' Lynn Trammell – AERA Online Paper Repository, 2024
This project aims to gain insight into the mechanisms by which schools in highly challenging environments avoided learning loss--or even improved--during the pandemic. Using a unique dataset covering multiple levels of school, health, and environmental data, we examine which factors led schools to 'beat the odds' when it comes to learning…
Descriptors: COVID-19, Pandemics, Educational Practices, Economically Disadvantaged
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Radinsky, Josh; Tabak, Iris – British Journal of Educational Technology, 2022
How do people reason with data to make sense of the world? What implications might everyday practices hold for data literacy education? We leverage the unique context of the COVID-19 pandemic to shed light on these questions. COVID-19 has engendered a complex, multimodal ecology of information resources, with which people engage in high-stakes…
Descriptors: Information Literacy, Data, COVID-19, Pandemics
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Larry J. LeBlanc; Thomas A. Grossman; Michael R. Bartolacci – INFORMS Transactions on Education, 2024
The COVID-19 pandemic has forced the rapid adoption of remote teaching modalities including "hyflex" where students attend some class sessions in person and some online. Managing the hyflex course requires faculty to quickly generate several reports and to update these reports rapidly when the authorities adjust the rules, students…
Descriptors: Blended Learning, Scheduling, Spreadsheets, COVID-19
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Susan Bush-Mecenas; Jonathan D. Schweig; Megan Kuhfeld; Louis T. Mariano; Melissa K. Diliberti – Education Policy Analysis Archives, 2024
The COVID-19 pandemic caused tremendous upheaval in schooling. In addition to devasting effects on students, these disruptions had consequences for researchers conducting studies on education programs and policies. Given the likelihood of future large-scale disruptions, it is important for researchers to plan resilient studies and think critically…
Descriptors: Educational Research, COVID-19, Pandemics, Change
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Aidan C. Tan; Angela C. Webster; Sol Libesman; Zijing Yang; Rani R. Chand; Weber Liu; Talia Palacios; Kylie E. Hunter; Anna Lene Seidler – Research Synthesis Methods, 2024
Background: Data sharing improves the value, synthesis, and integrity of research, but rates are low. Data sharing might be improved if data sharing policies were prominent and actionable at every stage of research. We aimed to systematically describe the epidemiology of data sharing policies across the health research lifecycle. Methods: This was…
Descriptors: Information Dissemination, Data, Health, Medical Research
Susan Bush-Mecenas; Jonathan Schweig; Megan Kuhfeld; Louis T. Mariano; Melissa Kay Diliberti – Grantee Submission, 2023
The COVID-19 pandemic caused tremendous upheaval in schooling. In addition to its devasting effects on students' academic development, the disruptions to schooling had important consequences for researchers conducting effectiveness studies on educational programs during this era. Given the likelihood of future large-scale disruptions, it is…
Descriptors: Research Problems, Educational Research, COVID-19, Pandemics
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Bader Muteb Alsulami; Abdullah Baihan; Ahed Abugabah – Cogent Education, 2024
The COVID-19 pandemic precipitated an abrupt transition to online learning, impacting students with disabilities uniquely. This study examines the experiences of 62 such students in the new educational paradigm, employing a mixed-methods approach. Quantitative data were collected through surveys and questionnaires to assess privacy and security…
Descriptors: Students with Disabilities, Inclusion, Artificial Intelligence, Computer Security
Rebecca R. Skinner; Isobel Sorenson; Kyle D. Shohfi – Congressional Research Service, 2024
In response to the COVID-19 pandemic, Congress enacted several programs that provided federal funds specifically to prevent, prepare for, and respond to coronavirus in elementary and secondary education, or provided funds that could be used for that purpose. These programs include the Elementary and Secondary School Emergency Relief (ESSER) Fund,…
Descriptors: COVID-19, Pandemics, Elementary Secondary Education, Federal Aid
Plackner, Christie; Kim, Dong-In – Online Submission, 2022
The application of item response theory (IRT) is almost universal in the development, implementation, and maintenance of large-scale assessments. Therefore, establishing the fit of IRT models to data is essential as the viability of calibration and equating implementations depend on it. In a typical test administration situation, measurement…
Descriptors: COVID-19, Pandemics, Item Response Theory, Goodness of Fit
National Forum on Education Statistics, 2024
The Forum is pleased to present the "Forum Guide to Student Learning Data During Pandemic School Closures and Beyond." The purpose of this resource is to review how local education agencies (LEAs) and state education agencies (SEAs) changed their approaches to collecting and using student data during the pandemic and how they are working…
Descriptors: School Districts, State Departments of Education, Data, COVID-19
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