About The Study: In this modeling study, economic favorability of COVID-19 vaccination varied by age. Cost-effectiveness results for individuals in the 2 older age groups were favorable and generally robust to changes in parameter inputs, while results for the younger age group were sensitive to parameter input changes. As the evidence base for COVID-19 vaccination and burden of illness evolves, it may be important to continue to update and revise the economic evaluation of vaccination. The Advisory Committee on Immunization Practices considered these results in its decision to recommend vaccination with the 2023 to 2024 COVID-19 mRNA vaccines.

A new study combines eye tracking and artificial intelligence to identify the exact moments in an educational video that matter for learning in children. The study could also predict how much children understood from the video based on their eye movements while they were watching it.

Large language models such as ChatGPT recognise widespread myths about the human brain better than many educators. However, if false assumptions are embedded into a lesson scenario, artificial intelligence (AI) does not reliably correct them. These were the findings of an international study that included psychologists from Martin Luther University Halle-Wittenberg (MLU). The researchers attribute this behaviour to the fundamental nature of AI models: they act as people pleasers. However, this problem can be solved by a simple trick. The study was published in the journal “Trends in Neuroscience and Education”.

Mount Sinai researchers have demonstrated the effectiveness of teaching surgical trainees a difficult procedure using artificial intelligence (AI) algorithms and an extended-reality headset without the presence of an instructor. All of the 17 trainees in the study achieved surgical success. The novel study, published in Journal of Medical Extended Reality, drew highly favorable reviews from student participants who tested the deep learning model. The results carry significant implications for future training of residents and surgeons, as well as for the even broader field of autonomous learning within medicine.

University of Phoenix College of General Studies announces the publication of a new peer-reviewed study in the journal Wild, co-authored by Jacquelyn Kelly, Ph.D., associate dean, and faculty Dianna Gielstra, Ph.D. and Tomáš J. Oberding, Ph.D., along with a multidisciplinary team of researchers from institutions across the U.S. The article, titled “Exploring Zoogeomorphological Landscapes: Enhancing Learning Through Virtual Field Experiences of Beaver Ponds Along the Red Eagle Trail, Glacier National Park, Montana, USA,” highlights how immersive virtual field experiences can help online learners better understand the ecological and geomorphic impacts in real-world environments.

Researchers at The University of Texas at Arlington are launching a two-year study to explore whether data from everyday fitness trackers can help predict a person’s risk of developing cardiovascular disease. Backed by a $400,000 grant from the Texas Higher Education Coordinating Board, the study officially started on Aug. 1 and will use commercially available wearable devices to monitor physical activity, sleep and blood pressure.