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Full-Text Articles in Contemplative Education
Using Research-Focused Llms, David Farnsworth, Elizabeth Stone
Using Research-Focused Llms, David Farnsworth, Elizabeth Stone
Faculty Presentations on AI
This hands-on workshop introduces university faculty to practical AI tools that support the full academic research workflow, from initial discovery to synthesis and writing. Participants explore the “Big 5” research tools—Perplexity.ai, Scite.ai, Elicit.com, ResearchRabbit, and SciSpace.com—along with Google’s Gemini extensions and NotebookLM, a source-grounded AI designed to analyze uploaded documents while maintaining privacy and providing live citations. The session demonstrates how these tools can accelerate literature reviews, fact-checking, visual mapping of citations, and deep synthesis of complex sources. Faculty also learn strategies for integrating AI responsibly into teaching, including helping students manage bibliographies, using AI for rubric-based feedback, and creating …
Ai In The Classroom, Dr. Adrian E. Hinkle, Dr. Amanda Wilson, Dr. Jan H. R. Wörner
Ai In The Classroom, Dr. Adrian E. Hinkle, Dr. Amanda Wilson, Dr. Jan H. R. Wörner
Faculty Presentations on AI
This presentation examines how educators can thoughtfully integrate artificial intelligence into the classroom while upholding academic integrity, ethical engagement, and the core mission of education. It draws on historical parallels—from ancient concerns about writing to later fears surrounding typing—to frame AI as a double-edged sword that can offload routine cognitive tasks yet risks eroding the mental discipline and critical thinking essential for deep learning. Centered on the guiding question of what students truly need to learn and how technology can help them achieve it, the session offers practical assignment frameworks, such as designing an AI-supported ministry plan and developing a …
Ai In Scholarship, Dr. Tim Hart
Ai In Scholarship, Dr. Tim Hart
Faculty Presentations on AI
This presentation explores the appropriate role of artificial intelligence in scholarly work, distinguishing between uses that support academic rigor and those that undermine intellectual responsibility. While cautioning against reliance on AI for original argumentation, unverified literature reviews, data interpretation, and normative judgments, it highlights practical applications across the research lifecycle, including ideation, literature exploration, argument refinement, structural analysis, reviewer simulation, and manuscript preparation.