Year: 2024
Type: article
Abstract: Anyone teaching science is facing a rising tide of online misinformation, and students are often ill-equipped to judge the reliability of what they see online. A project is described to use machine learning to detect and flag misinformation, based on initial training by science undergraduates. The neural networks are 95% reliable when applied to an initial testbed of articles on evolution and climate change. The technology will be released as a web browser extension and eventually as a smartphone app.
Source: Astronomy Education Journal
Author: Chris Impey
Institution: University of Arizona
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W4403384381