Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 3 of 3
Full-Text Articles in Education
Covid Learning Loss: A Call To Action, Nathan D. Grawe
Covid Learning Loss: A Call To Action, Nathan D. Grawe
Numeracy
The COVID-19 pandemic and policy responses designed to mitigate transmission have caused deep and persistent mathematics learning loss among K–12 students. While initial data might have been read optimistically as a blip that would reverse once schools returned to normal, 2023 data from the National Assessment of Educational Progress (NAEP) show that losses persist. While the NAEP does not directly measure quantitative reasoning (QR), the data present a disturbing picture for QR instruction and call for new lines of research that inform QR pedagogical response.
Confidence Intervals Of Covid-19 Vaccine Efficacy Rates, Frank Wang
Confidence Intervals Of Covid-19 Vaccine Efficacy Rates, Frank Wang
Numeracy
This tutorial uses publicly available data from drug makers and the Food and Drug Administration to guide learners to estimate the confidence intervals of COVID-19 vaccine efficacy rates with a Bayesian framework. Under the classical approach, there is no probability associated with a parameter, and the meaning of confidence intervals can be misconstrued by inexperienced students. With Bayesian statistics, one can find the posterior probability distribution of an unknown parameter, and state the probability of vaccine efficacy rate, which makes the communication of uncertainty more flexible. We use a hypothetical example and a real baseball example to guide readers to …
Factors In The Probability Of Covid-19 Transmission In University Classrooms, Charles Connor
Factors In The Probability Of Covid-19 Transmission In University Classrooms, Charles Connor
Numeracy
University students and faculty members need an effective strategy to evaluate and reduce the probability that an individual will become infected with COVID-19 as a result of classroom interactions. Models are developed here that consider the probability an individual will become infected as a function of: prevalence of the disease in the university community, number of students in class, number of class meetings, and transmission rate in the classroom given the presence of an infected individual. Absolute probabilities that an individual will become infected in a classroom environment cannot be calculated because some of these factors have unknown values. Nevertheless, …