As artificial intelligence (AI) grows in popularity as an emerging technology within the eLearning industry, some organizations are implementing AI “hackathons” to explore real-world uses for generative AI (formerly called “AI art”).

Examples of generative AI include: using AI to automatically create media content, such as artwork, videos, animations, voiceovers, written content (e.g.,, and more.

One example is Media.monks, which organized a full day where their entire remote workforce was divided into teams of ~5 people each, then worked together to explore various AI tools with the goal of solving a specific client problem. Each team used its chosen AI tool(s) to rapidly prototype iterations. At the end of the day, they presented their prototypes and everyone voted for their favorite idea. The same sort of AI “hackathon” activity would work well in a higher education setting.

The main way that I could envision AI art being utilized in education is for rapid iteration, ideation, or prototyping. The AI often comes up with ideas that I wouldn’t have otherwise considered, and I’ve heard this sentiment from other AI artists, too. For instance, in a university program for Digital Storytelling or Film and Cinema, one might imagine all the ways that AI art can rapidly create imagery, storyboards, sets, or even plans for CGI, character designs, and more. People are already using AI art to create entire music videos, graphic novels, and website designs. It’s possible to convert these AI illustrations to NFTs, then include the NFTs within your course; raffle them off to students as part of a gamification initiative; or incorporate them into an eLearning game.

In my profession (creating code bootcamps and STEM courses), AI prompts can be useful for teaching computational thinking skills. For example, there are specific ways that you must structure your generative AI prompt to achieve the best results. By thinking like a robot, you can structure your prompt in ways that are more successful… and this opens the door to other logical forms of thinking that are also useful in computer science and coding. I could see myself using this activity as an icebreaker before teaching a beginner-level JavaScript or Python lesson. Likewise, some of the generative AI options that exist today require light Python coding for installation and implementation, which could tie directly into the course material.

Here’s another example of how to use AI and social media to create a community-driven story, which is told in the form of AI-generated micro-videos.

Imagine the implications for eLearning. For example, a digital storytelling class could partner students together in groups to collaborate to tell a story. Or an entire class could work together to write their own fantasy/sci-fi story by voting on what they want the character to do next. Then, the class could hold an AI hackathon to use emerging technologies to bring their vision to life. With a little creativity, the possibilities are endless…