As a technologist, writer, and adjunct professor at the New School, I've always been fascinated by the potential of mobile app development to transform education. When I started using a smart indoor trainer in my garage, I stumbled upon a clever approach that could be applied to learning: adaptability. In this article, we'll explore how AI-powered training platforms can inform our understanding of education and lead us towards more effective, personalized approaches.
My first session on the Wahoo Kickr began with a ramp test, which simulated real-world terrain by adjusting pedaling resistance every 60 seconds. As I pedaled, my heart rate reached 166 beats per minute – redline for someone my age! The system estimated my "functional threshold power" (FTP), a dynamic baseline that adapted to my initial capacity and responded with precision and flexibility.
This experience sparked an idea: what if education worked like this? What if, instead of following a prescribed curriculum, teaching started with a learner's threshold and built a personalized path forward? This concept – adaptive threshold learning (ATL) – could revolutionize the way we approach education.
The United States is facing a crisis in education. According to the National Assessment of Educational Progress, American students are testing at historic lows across all K-12 levels. The Covid-19 lockdowns have exacerbated these issues, leaving many students struggling and disengaged. Against this backdrop, AI is being woven into learning and teaching in complex and rapidly evolving ways.
Students are already using tools like ChatGPT to draft essays, solve equations, and generate study guides – sometimes to deepen understanding, but often to reduce or eliminate the effort required to learn. Eighty-five percent of students acknowledge using generative AI to help them with coursework in the last year, according to an Inside Higher Ed survey. Teachers are also beginning to use AI tools to automate time-consuming tasks like drafting lesson plans and generating practice exercises.
However, there's a danger that AI could become a siren call, tempting educators to use algorithmic shortcuts for the demanding, human work of noticing, guiding, and inspiring students. Social media offers a cautionary tale here: platforms are populated with AI-generated influencers addressing AI-generated followers, a self-reinforcing feedback loop where authenticity vanishes.
The integration of AI into education is no longer hypothetical – it's well underway. In April, President Trump signed an executive order to bring AI into American classrooms, and major tech companies have pledged to support this mission. The question is not whether learning will be affected by AI, but how and to what ends. Left unguided or steered solely by tech companies pursuing their own interests, AI educational tools could magnify inequities and perpetuate the very problems they promise to solve.
With thoughtful design, however, AI educational tools could move us beyond rigid curricula toward adaptive systems that respond to individual learners. The decision before us – to let AI evolve haphazardly or to shape it deliberately with educators, students, and institutions at the center – will determine whether it deepens our crisis or becomes the foundation for a more flexible approach to education.
In conclusion, mobile app development has the potential to revolutionize education by applying the principles of adaptive threshold learning. By identifying each student's current limits and designing experiences to expand them, we can create personalized learning paths that cater to individual learners' needs. This approach could lead us towards a more effective, efficient, and enjoyable educational experience – one that's powered by AI and driven by human ingenuity.