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Generative AI and Research

This guide is designed to support faculty and instructors as they navigate research and information literacy concerns caused by the rise of generative AI technology.

Generative AI tools are an opportunity to rethink what is valued in research assignments.

Instructors can take the opportunity to reevaluate the disciplinary research skills that they want students to gain. Drawing on information literacy concepts and seeking support from librarians are ways to make this process less overwhelming.

Information Literacy and Generative AI

The  ACRL Framework for Information Literacy in Higher Education is helpful for identifying the disciplinary research practices students will need to develop to participate in their field. The influence of Generative AI may change the pathway to learning these research skills, but the underlying concepts remain relevant:

  • Authority Is Constructed and Contextual examples: considering a variety of source types representing diverse authors and perspectives; evaluating the quality of content for accuracy, reliability, usefulness, and bias
  • Information Creation as a Process examples: choosing sources appropriate for a specific need/context; understanding that the way sources are created and packaged influences quality and type of information a source offers
  • Information Has Value examples: developing a critical awareness of information privilege, privacy, and intellectual property; crediting and incorporating the ideas of others into their own work ethically
  • Research as Inquiry examples: developing questions/topics specific enough for academic research; assessing gaps in literature; navigating conflicting or divergent information; finding a balance between curiosity and skepticism
  • Scholarship as Conversation examples: synthesizing, and responding to ideas from multiple sources; finding and understanding scholarly disciplinary literature
  • Searching as Strategic Exploration examples: brainstorming and experimenting with keywords--search terms and prompt language--that return expected, useful results; practicing persistence in the face of research challenges

Reflection Questions for Designing Assignments

Reflection questions for instructors evaluating and revising assignments and learning outcomes:

  • Do my outcomes or assessment strategy reward curiosity over "the" answer?
    • Why: Generative AI tools are great at giving answers, but interrogating AI output, experimenting with different methodologies, and engaging in authentic inquiry require human cognition. 
  • What opportunities are there for students to demonstrate their research process at various scaffolded steps?
    • Why: scaffolding larger assignments and offering lots of low-stakes assessments sustains student engagement, makes the learning process more visible throughout the semester, and creates feedback checkpoints for guiding students' appropriate use of AI tools. 
  • How can I ask students to connect their work to unique personal or shared classroom experiences?
    • Why: LLMs that are used to train popular generative AI tools will not have deep information about students' lives or their day-to-day class activities. Having students connect their research to personal experiences may make it challenging for learners to turn in fully-AI generated work. 
  • What knowledge/skills/support do I need as an instructor to guide students’ ethical use of generative AI technology in this assignment/course/discipline?
    • Why: Using Generative AI technology raises a variety privacy, humanitarian, environmental, and intellectual property-related concerns. Staying informed and utilizing campus resources will help you create a safe and meaningful learning experience for your students.

Don't assume that you and your students are on the same page about the use of generative AI to complete assignments. Instead, get curious about students ideas and reasons for using AI and what limits they perceive. Having an open conversation with students will help you build community and encourage students to take ownership of their learning.

Review learning objectives with students, and guide them in an open conversation about appropriate use of Generative AI in your class/assignment. 

  • What are some uses of Gen AI that could help meet these learning goals?
  • What uses of Gen AI do you think are unfair or should be off-limits for this course/assignment? Why?
  • When and how should you indicate that you've used Gen AI to complete this assignment? 

Use the content and Questions for Students sections in the other pages of this guide to continue your conversations with students about Generative AI. 

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