This seminar explores responsible AI as a practical research skill for scholars who use AI in their research practices, including searching, summarizing, coding, analyzing, writing, reviewing, translation, translation, and research administration.
Abstract
This seminar explores responsible AI as a practical research skill for scholars who use AI in their research practices, including searching, summarizing, coding, analyzing, writing, reviewing, translation, and research administration. It provides an evidence-informed framework for preserving validity, accountability, ownership, privacy, and trust across academic research workflows.
Practical recommendations—from modeling ethical AI use to using AI as a thought partner in inquiry design—help teachers integrate artificial intelligence in ways that strengthen student inquiry.
John Lee, Jordan McGaughey, The C3 Teachers Leadership Academy AI Working· Social Education· 0 citations
It is argued that researchers and institutions can position generative AI both as a tool for epistemic reflexivity and as an object that must be examined reflexively.
Panayiota Kendeou, G. Veletsianos, Clay Whetung· Communications Psychology· 0 citations
Artificial Intelligence (AI) is transforming academic writing and scholarly publishing, offering new efficiencies while raising significant ethical and regulatory challenges. This study critically examines AI’s dual role as both a productivity catalyst and a source of risks to originality, fairness, and credibility. Tw...
Michael Ndonye· Editon Consortium journal of...· 0 citations
Generative artificial intelligence (AI) is transforming graduate research and academic work; however, increased use does not necessarily lead to critical evaluation or responsible engagement. This study examines the gap between graduate students’ AI use and their evaluative, ethical, and rhetorical engagement with AI-g...
Marina Falasca· American Journal of STEM Edu...· 0 citations
The rapid adoption of large language models is accelerating scientific output faster than expert attention can scale, placing growing pressure on the scholarly communication system. This perspective examines how artificial intelligence (AI) is reshaping research and scholarly communication, from knowledge discovery to...
