Everyone says they want humans “in the loop" when it comes to AI. But where should humans be in that loop? Circling around an AI nexus in the center, or sitting in the center ourselves? In this presentation, I argue for the latter. I explain how TCSG's and AI-ALOE's collaborative work in AI research is leading with a people-first approach that improves existing practices rather than disrupting them unnecessarily. This presentation discusses AI technologies developed in collaboration between TCSG professors and AI-ALOE's NSF-funded researchers and sets up our students and teachers alike for success, not stress, in the AI-powered future.
Could badging for AI skills be possible at your institution? Learn how we began, evolved, and scaled our AI badging program to help students develop important perspectives and skills while maintaining a sustainable workflow and ultimately including broader faculty participation and buy-in. We'll share our method for combining the power of our learning management system, BoodleBox, and Padlet to deliver a synchronous learning experience that results in the awarding of the badge. Hear the real truth about the ups and downs and lessons learned along the way, and what's next for our program.
When students need sources, many go straight to AI, and it's easy to see why. It summarizes, it cites, and it always sounds like it knows what it's talking about. The problem is not that students are using AI for research. The problem is that they often don't know how to push back on it. Instead of asking whether students should use AI for research, this session asks how we teach them to do it thoughtfully. Through Mike Caulfield's SIFT method applied directly to AI-generated content, we'll explore practical critical AI literacy strategies that help students use these tools to find and evaluate sources while recognizing misinformation and avoiding over-reliance on text that may sound authoritative but can't always be trusted. Grounded in English composition but adaptable across disciplines, this session offers a framework, a few open questions, and materials you can take back to your own classroom or library. #InformationLiteracy #CriticalAIUse #Writing
Broader adoption of chat reference tools has led to increased access to unstructured data, revealing patron needs and question trends. To utilize this information to the fullest requires careful analysis of the transcripts - from navigating privacy concerns to identifying user themes. This workshop will walk through the process of how we developed a custom-built, offline, AI-powered tool to help with transcript analysis. We begin by comparing our solution to a baseline, human analysis of our text followed by a side by side comparison to pre-built LLMs such as Gemini, to determine which method was most effective.
While generative AI rapidly expands its educational reach, writing instructors remain the most cautious and at times resistant adopters, due to concerns about authorship, plagiarism, and cognitive offloading. In response, the AI Literacy module was designed for the English 102 Composition course to frame generative AI tools as process-oriented research partners rather than a text-producing shortcut. NotebookLM is used as a constrained research environment for a research workflow in which students' original thinking precedes AI interaction. The framework demonstrates pedagogically grounded AI use that supports transparency, metacognition, and ethical research practices, thereby strengthening rhetorical awareness, ensuring authorial control, and minimizing plagiarism (#AI-Literacy #AI-assisted-research #metacognition).
