Resources
- Generative AI Library Guide: A high-level synopsis on GenAI and information for both faculty and students.
- Generative AI in Education taskforce report: Broad set of recommendations on responding to the emergence of GenAI technologies for faculty and academic leaders.
- Generative AI@NAU: For NAU faculty and staff, Microsoft Teams site to ask questions and contribute to the conversation.
- Syllabus statements: Sample syllabus statements for a course or individual assignments for example GenAI uses.
Authorship
- John Georgas, Senior Vice Provost for Academic Operations
- John Tingerthal, Chair for Faculty Senate Council on Learning
Generative Artificial Intelligence in Teaching and Learning
Generative artificial intelligence (GenAI) technologies have the ability to extrapolate from large scale data sets to create text and other types of content that appear unique. GenAI capabilities have already demonstrated the potential to significantly change the ways in which we teach and work—and are likely to continue doing so into the future.
We support the responsible and ethical use of GenAI technologies in helping us foster student learning and success, and we recognize the importance of embracing the role these technologies will play in our work and the professional futures of our graduates.
We encourage our faculty, staff, and students to remain current on the fast-paced developments in these technologies and engage in conversations that harness our community’s collective expertise to define the boundaries and expectations that are appropriate for each discipline and learning environment. By doing so, we are confident that we will continue to offer our students an excellent academic experience that prepares them for professional success in careers that will almost certainly include GenAI technologies as crucial additions.
Principles that shape action
Our work with GenAI technologies is aligned with larger principles about the role of higher education in preparing for the continued expansion of artificial intelligence capabilities. These principles are captured in the Higher education’s essential role in preparing humanity for the artificial intelligence revolution statement issued during the 18th annual United Nations lnternet Governance, held in October 2023 in Kyoto, Japan—and we are proud to have joined as signatories for this statement’s initial issue, represented by our University President José Luis Cruz Rivera.
We encourage everyone to review the complete statement, and share only its top-level principles here:
- People, not technology, must be at the center of our work;
- We should promote digital inclusion within and beyond our institutions;
- Digital and information literacy is an essential part of a core education;
- AI tools should enhance teaching and learning;
- Learning about technologies is an experiential, lifelong process; and
- AI research and development must be done responsibly.
Faculty guidelines
Building on the resources and policies shared earlier, the following guidelines offer initial guidance to faculty for the use of GenAI technologies at NAU:
- Communicate appropriate use to students
Provide and discuss clear syllabus policy statements that define permitted and prohibited use in your courses—developed in collaboration with our instructional designers, we offer sample syllabi statements to use as a starting point in offering guidance to students, which may be modified to fit specific course or assignment needs. Unauthorized uses of GenAI, as defined by the instructor, may constitute an academic integrity violation.
- Do not mandate student use
Accessibility, personal concerns regarding adoption, and other barriers may cause undue burden on students. Faculty should provide a non-GenAI option for students when incorporating these tools into student assignments.
- GenAI detection
Current GenAI detector technologies, including NAU’s industry-leading licensed solution Turnitin Originality, are imperfect and may return false positives and false negatives—be cognizant that results such detectors produce cannot be considered definitive evidence of an academic integrity violation.
- Protect confidential data
Grounded in our Data Classification and Handling policy, faculty should not enter data classified as Internal, Sensitive, or Highly Sensitive (Level 2 and above), including non-public research data and personally identifiable student information, into publicly-available GenAI tools. Information shared with GenAI tools using default settings is not private and could expose proprietary or sensitive information to unauthorized parties.
- Experiment with GenAI in courses
There are myriad possibilities: Explore using generative AI to outline schedules and topics for new modules or lessons, or generate variations of exam questions that assess student learning. Ask students to explore a high-level topic using GenAI chatbots and report their detailed findings, create their own practice exams by generating questions on key course topics, or create and refine outlines and first drafts of writing assignments.
- Include GenAI in curricular decisions
Applications of generative AI in professional practice abound, and these technologies have already augmented the standard toolkits in many occupations. Seek opportunities to make curricular changes that build on the changes you anticipate happening and better prepare students for the evolving professional landscape.
- Coordinating and communicating with academic leaders to ensure that information about GenAI is broadly disseminated to faculty and students and fostering awareness of these technologies across the institution;
- Equipping faculty with the necessary knowledge to effectively use these technologies through a commitment to regular updates of existing library guides and other resources with topics and content specific to GenAI technologies;
- Launching broad professional development efforts, coordinated through the Teaching and Learning Center, to offer faculty information about GenAI, support the integration of these technologies in classes, and offer advice on learning assessment techniques that are resilient to GenAI;
- Developing guidance on acceptable uses of GenAI in non-instructional work, such as work that faculty do in research, scholarship, and service or as part of university business processes;
- Developing new courses that offer students opportunities to learn more about GenAI, its capabilities and potential, and how they might be used professionally;
- Coordinating with our Career Development office to integrate GenAI in how we prepare students for career success; and
- Augmenting training offered to students and graduate teaching assistants to explicitly address GenAI considerations.
Looking ahead
Consensus within the higher education community for how to best integrate GenAI technologies in fostering student learning is still emerging, and these technologies are rapidly evolving. We’ll continue to support our institutional community, with efforts that include: