About
An ERA-curated thematic profile exploring how researchers, educators, and academic institutions can evaluate the reliability of scholarly information. Sessions examine citation accuracy, evidence verification, source credibility, and the challenges of validating research in an environment increasingly influenced by generative AI.
Focus: Research verification, citation reliability, evidence validation, source credibility, research integrity, AI-generated references, and responsible scholarly practices.
Sessions
Verification Skills Every Researcher Now Needs
As AI makes information easier to generate and distribute, verifying scholarly claims becomes increasingly important. This session explores practical approaches to evaluating sources, checking citations, validating evidence, and maintaining confidence in research findings.
The Source Exists—but Does It Support the Claim?
Finding a legitimate source is only the first step in evaluating evidence. This session explores how researchers can determine whether cited material genuinely supports an argument, recognize misleading interpretations, and strengthen the connection between claims and evidence.
Can We Still Trust the Citation?
Citations can make academic work appear credible, but a reference does not automatically guarantee accuracy or reliability. This session explores the challenges of fabricated, inaccurate, and misleading citations, particularly in AI-assisted research, and what researchers should verify before trusting a reference.