3 AI-Related Questions for Notre Dame’s Sonia Howell

We last checked in with Sonia Howell, director of ND Learning’s Office of Digital Learning at Notre Dame, back in 2023. Since we last spoke, the AI tsunami has hit our universities. I was curious about how Sonia is thinking about AI and learning. She graciously agreed to answer my questions.

Q: How is AI changing the work you and your team do in the Office of Digital Learning?

A: Thanks for having me back, Josh.

In short, AI is changing everything and nothing about what we do. Digital learning teams have long accompanied faculty in navigating the affordances and challenges that new tools, platforms and modalities present for teaching and learning.

The work requires pedagogical and technological expertise that is mobilized through a design-thinking approach deeply grounded in empathy. AI asks us to bring our core competencies to another moment of technology-driven change and to help faculty work through where AI may support a learning experience, where it may introduce risks and where it may not belong. In all cases, the focus should be building on established learning design theories and thinking intentionally about whether the technology supports students’ learning and, if so, how and where it is most fruitfully deployed.

To support faculty and the broader campus community through AI-related change, digital learning teams must have dedicated time, space and support to build their own fluency with the technology. In Notre Dame’s Office of Digital Learning, we have been intentional about creating opportunities for team members to develop their AI proficiency through initiatives like internal AI challenges that provide a safe space for focused experimentation on AI applications in different learning contexts. The team is also actively experimenting with if/how AI can fit into or redesign their workflows while retaining the deeply relational nature of the work that we do.

Because of their expertise, the Office of Digital Learning team contributes to and collaborates with campuswide AI initiatives, like ND Learning’s Lab for AI in Teaching and Learning, OIT’s AI Enablement team, and the Data, AI and Computing Initiative. These collaborations have led to everything ranging from co-hosted workshops to the design and development of a Notre Dame-focused AI primer for all incoming first-year undergraduates.

Q: Looking specifically at online learning, how do you see AI changing the landscape for the development, teaching and marketing of online programs (degree and nondegree)?

A: Online course development is time- and resource-intensive for both the faculty and the digital learning team supporting these efforts. For institutions engaged in online learning at scale, AI will create efficiencies and improvements in the development, marketing and delivery of online programs (as SNHU’s Scott Pulsipher detailed in his recent interview for IHE). Those capacities are worth exploring, especially when they make courses more responsive to learners and market needs and can help drive down the cost of tuition.

At the same time, a pressing challenge for online (and residential) learning is ensuring the integrity of the learning experiences we are delivering. Put differently, in a world where generative AI is becoming ubiquitous, we must find ways to push our learners to embrace the productive friction that necessitates learning and in so doing realize the value of the programs we offer, including the critical thinking skills fostered by a liberal arts education.

For Notre Dame, a university with a relatively small online learning portfolio, preserving the relationships and rigor for which the university is known has always been central to our approach to online course design. Our Summer Online program is our largest online offering, with over 60 bi-chronous (combining asynchronous and synchronous forms of learning) courses running each year. Since ChatGPT was launched in 2022, our digital learning team has worked closely with our online instructors to revisit, revise and often redesign their assessments. Approaches range from oral exams to online proctoring to doubling down on classroom community and live conversations. In many cases, the instructors bring their redesigned assessment strategies back into their in-person teaching.

Q: What about the future of AI in teaching and learning are you most excited about, and what keeps you up at night?

A: As I think about where and how AI can positively impact teaching and learning, I am reminded of Justin Reich’s important and insightful book, Failure to Disrupt: Why Technology Alone Can’t Transform Education (2022), wherein he argues, “New technologies are rarely as transformative as we might hope (or as evangelists might promise), but to critique them for bringing only incremental change is not to diminish (all of) their value.”

Personally, I have yet to see compelling evidence demonstrating large gains in teaching and learning brought about by AI. Some studies have suggested potential benefits of AI in teaching and learning, while others have presented the negative impacts thereof (e.g. Rischman et al.’s forthcoming paper), so I think it is premature to know if, how and where AI will have a net positive impact. What I am excited by are the important conversations that AI is giving rise to around the value of liberal arts education, the role of higher education and its relationship to industry, and the importance of applied learning. These are all topics that are shaping teaching and learning in person and online.

The thing that keeps me up at night is the ubiquitous temptation of cognitive surrender (Shaw and Nave, 2026) across all learning modalities and learners at a wide variety of stages. This is a wicked problem that will require humility, creativity and collaboration among administrators, faculty, staff and students. It will also require experimentation. Recognizing this, this fall, the Office of Digital Learning in collaboration with colleagues in our Kaneb Center for Teaching Excellence will launch a grant series called Reimagining Class Time, the goal of which is to provide faculty with the support and incentives to redesign their residential courses to support student learning in the age of AI.

At a moment when our campus communities are navigating how to teach and how to learn in the face of this new technology, I can’t think of a more important application of the skills of digital learning teams than addressing when to create AI-free spaces, how to embrace the technology in the learning process when we do and in what ways can we help students discern the best approach for their learning when faced with either option.