In Fall 2024, I launched an experimental course that approached artificial intelligence literacy from an unexpected angle: leisure and recreation. As the creator of “AI & the Future of Fun,” I aimed to demystify AI technology, specifically Generative AI (GenAI) by connecting it to something universally relatable – how we have fun. The course explored topics relating to entertainment and media, fitness and exercise, video games and eSports, travel and tourism, and hobbies from both the leisure consumption (personal) and leisure production (professional) sides. Here is how this innovative approach unfolded from multiple perspectives.

From an Educator’s Perspective: Designing for Engagement

When designing this course, I embraced Universal Design for Learning (UDL) principles to ensure the content would be accessible and engaging for all students. Instead of approaching AI from a place of anxiety, I chose to begin with joy, providing multiple means of engagement by connecting technology to students’ personal interests and leisure activities.

The course’s design aligned with the UDL framework of multiple means of:

Representation: I deliberately avoided traditional textbooks, instead offering content through diverse formats including current articles, media, guest panels, and hands-on experimentation. This multimodal approach ensured students could access the material in ways that best suited their learning preferences. As one student noted in their evaluation, “The course is organized in a way that helps me learn.”

Action and Expression: Students could demonstrate their understanding through various projects, from curating AI-themed playlists to creating multimedia presentations. This flexibility allowed students to leverage their strengths while developing new skills. Students had the choice to respond to weekly self-reflections by written, auditory, or visual submissions. Peer review of AI-related activities allowed students to engage in critical thinking skills to evaluate the content and process of the GenAI output.

Engagement: Most revolutionary was my “ungrading” philosophy. Rather than traditional assessments, students evaluated their own engagement, understanding, and growth. As one student noted in their evaluation, “I felt like there were a lot of tasks, but they weren’t busy work. I was able to notice my growth from the beginning to the end.” This approach reduced barriers to experimentation, encouraged risk-taking in learning, and diminished the fear of failure that often accompanies learning new technology. Guest panels featuring industry professionals created real-world connections that heightened relevance and authenticity.

From a Student’s Perspective: Learning Through Experience

The transformation in student attitudes toward AI was remarkable. One student’s reflection captured this journey perfectly: “I always viewed AI as cheating because of the stigma it has in education, but I’ve learned that it really is a tool that can be used to aid instead of doing the work for you.” Students felt the class environment and course topic of leisure relieved their pressure of being knowledgeable of the subject. Instead, they were discussing their own interests therefore making them the expert of the course topic. Add in the open use and encouragement of GenAI tools for completing various course tasks, and students felt they were able to gain confidence and competence in AI literacy.

Students engaged with AI through carefully designed projects that connected to their personal interests. The AI Playlist assignment had them curate media resources related to how AI will affect their preferred leisure activities. For example, several students discussed the future of fitness by finding articles, blogs, vlogs, and podcasts related to personal fitness coaches. This personalized approach immediately made the learning relevant and applicable. Another assignment was creating a multi-media representation of the future of their fun. Students created songs, videos, images, and presentations developed with GenAI tools, then presented their projects to peers for analysis and discussion.

By taking part in these activities, students became aware of the need for human interaction in the engagement with the rapidly changing technologies. A particularly insightful student observation highlighted the nuanced understanding they developed: “Art, at its core, is a medium that is shaped by human experiences. I am doubtful that music is a leisure activity that AI could fully encapsulate, but it definitely could be used in assistance.” This demonstrates the kind of critical thinking I aimed to cultivate – moving beyond binary perspectives of AI as either threat or savior while recognizing the ethical and responsible use of it.

From an Administrator’s Perspective: Institutional Impact

From an institutional standpoint, this course was a bold experiment in curriculum design. The feedback on the course evaluations were overwhelmingly positive. Students consistently rated the course organization and learning outcomes highly, with particularly strong scores for instructor feedback and respect for students. The design of the course utilizing UDL and ungrading principles speaks to the inclusive approach to support student learning.

The course structure proved that it is possible to integrate emerging technology responsibly while maintaining academic integrity. By focusing on ethical considerations and responsible use, I created a model that could be adapted across other departments and disciplines and within K-12 education, courses such as “AI and the Future of Healthcare,” or …Business, or …Marketing, or …fill in the blank.

The success of this approach is evident in the comprehensive understanding students developed. One student reflected: “This class, while it embraced heavy use of AI, taught a healthy balance between using AI and human thought. It made students aware of the strengths and weaknesses of AI and how people may capitalize on them to advance their ideas.” As one guest panelist said, “humans know how a strawberry tastes, it’s the human experience that can’t be replicated by a machine.” Students in this course are now able to identify when the use of a GenAI tool would be productive versus when human creation is needed.