Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Challenges and Opportunities for the Web 3.0 Metaverse Turn in Education

The metaverse, along with its various Web 3.0 sub-domains, represents a ground-breaking extension of the physical and digital worlds. In this emerging landscape, real and virtual worlds are being integrated in ways that facilitate interaction and create immersive experiences. This transformation has significant implications for diverse fields, particularly in reshaping both online and traditional education methods. By analyzing 417 comprehensive white papers released in 2022 and 2023 from leading consulting firms and think tanks, and incorporating insights from canonical academic articles, the authors extract key information about how metaverse technologies are influencing education. This investigation unveils some of the key impacts of metaverse technologies on the educational landscape, thereby contributing to a more profound understanding of its transformative effects. The present study provides a holistic perspective on the advantages and disadvantages associated with metaverse education, offering in-depth insights on the challenges involved in a potentially seamless integration with conventional practices. In sum, this research highlights the challenges and opportunities presented by the metaverse and its impact on new educational paradigms