As instructors find ways to integrate generative AI into their assignments, practical tools are needed for evaluating how students are engaging with AI throughout the process. Information literacy provides a useful framework for teaching and evaluating students’ critical thinking while using AI for disciplinary assignments. Presenters will introduce the AAC&U Information Literacy VALUE Rubric, describe how it is relevant to AI-assisted workflows, and demonstrate how it can be adapted to specific course assignments with emphasis on assignment-specific evaluation questions. The rubric's utility and insight will be demonstrated with findings from an application in a first-year engineering programming course. Then, following a backwards-design framework, participants will consider information-literacy learning objectives relevant to an AI-integrated assignment in their own course, and will start to develop their own evaluation questions. At the end of the session, participants will generate a list of next steps to begin assessing AI workflows in their courses.
With all the enthusiasm and trepidation about the use of AI in academics, our value as educators might feel threatened. However, a key scene in the James Bond movie Skyfall can provide reassurance about the things we do better than AI, qualities that reflect our continuing value and demonstrate the deeper purpose that drives us.
Composition programs around generative AI often center on refusal, foregrounding instructors’ anxiety in front of AI as an emerging tool that is both disturbing and hard to harness. This session offers an alternative perspective by exploring how composition teachers might approach AI use with less certainty and more curiosity. In Spring 2026, I asked students in a first-year writing course to submit a form titled “Declaration of the Use of GenAI & Labor Statement” along with each major assignment. This form aligned classroom practice with UofL’s “Code of Student Rights and Responsibilities,” invited students to reflect ethically on their AI use, fostered mutual trust rather than surveillance, and made visible the student labor involved in their writing processes. In this session, I will share the form’s design and its rationale, and present an analysis of students’ disclosures.
Designing learning activities that develop students' self-awareness, critical thinking, and interpersonal skills can be particularly challenging in online asynchronous environments. Blackboard Ultra's AI tools, including Socratic reasoning and persona role play assignments, provide online instructors with avenues for developing students' critical thinking and interpersonal skills. In this demonstration, two AI assignments are shared that were developed for a coaching and talent development course. In the first AI assignment, students are asked to share their “facilitative coaching philosophy” with an AI persona who uses a Socratic questioning method to surface students’ underlying assumptions and motivations for coaching. The second AI assignment is a role play activity where each student interacts in the role of “facilitative coach” with an AI-persona “client” to help the client become aware of, and commit to self-generated SMART coaching goals. Learnings from student and instructor feedback regarding what worked well, and opportunities for assignment adjustments, are shared.
Business Communication choices have expanded in this new age of AI. It has never been easier to generate an email, report, or other professional document. However, human competency in business communication (Lucas & Rawlins, 2015) still requires being concise, clear, professional, evidence-driven and persuasive. AI messaging struggles to achieve these competencies in some ways and excels in others. This session will provide a working definition of AI communication competence in terms of authenticity, ownership, and relationship using on-going research from the Business Communication program in the Department of Management & Entrepreneurship. Additionally, we will suggest methods for implementation of these competencies in a classroom.
In a mid-level undergraduate history course, I asked students to reflect on what remains distinctly human about doing history alongside AI. Students encountered AI-generated interpretations of a piece of historical scholarship. They described the output as generic, overly confident, and less useful than reading, peer discussion, and sitting with uncertainty. Yet their own responses revealed a further tension: they did not always read AI-generated text to the same close, critical analysis they brought to assigned sources. My feedback sometimes mirrored their own critiques of AI, pointing to claims that were too general or insufficiently grounded in the text. Based on those responses, I redesigned a later assignment to ask not whether AI could interpret for students, but whether it could support narrower historical tasks without displacing human judgment. This session reflects on that trajectory in light of the American Historical Association’s emphasis on AI literacy and disciplinary judgment.
