Beyond the AI Moment: A Case for Teacher Learning

Every decade brings a new technology that schools are told they cannot afford to ignore. Radio, then television, then computers, then the internet, then smartphones, and now AI. Each wave arrives with the same promise of transformation and the same scramble of underfunded teacher training. Each one mostly lands on teachers who were already overworked and asked to figure it out as they go.

The story of AI in education is not new. The story of how we support the people doing the teaching is the one we keep failing to write differently.

That failure is most visible where the gap is widest. According to 2023-2025 World Bank and UNESCO data on sub-Saharan Africa teacher training and class sizes, the average primary school class holds more than 40 students, and only about a quarter of teachers in low-income countries have had any kind of ICT training. But the pattern travels. Across Europe, three quarters of teachers report receiving no AI training at all, even as their students use it daily (GoStudent, 2025). In the United States, most teachers feel comfortable using AI themselves, but only about half feel ready to teach students how to use it responsibly (Youngstown State University, 2026). Wherever you look, the pace of change in education has outrun the way teachers are supported to keep up.

AI gets the headlines, but it sits inside a wider wave that includes immersive learning, learning analytics, adaptive systems, climate disruption, and a global mental health crisis among young people. Teachers are absorbing all of this in real time. The profession has been quietly redefined. A teacher in Nairobi, Delhi, São Paulo, or Helsinki is being asked to do something the role didn't ask of them a decade ago: to model judgment about technologies that change faster than any textbook can keep up with.

This is where the deepest pedagogical traditions actually help. Paulo Freire (1970) taught that education is never neutral, and that learners come into their power by reading the world critically, not just consuming it. Renee Hobbs has spent decades extending that insight into the media age. In Digital and Media Literacy: A Plan of Action, she laid out a vision where literacy now means accessing, analyzing and evaluating, creating, reflecting, and acting on the messages around us. In Create to Learn, she argued that teachers grow most when they make things themselves, not when they sit through trainings about new tools. And across her work, she returns to a powerful idea: that real learning happens in cycles, with each round of practice deepening the last.

That's a very different model from the one-shot workshop most teachers are offered today. It's also a model that travels. Ghana's curriculum reforms, India's AI for All initiative, Taiwan's 108 Curriculum Guidelines, Estonia's AI Leap, and UNESCO's 2025 Santiago Consensus all point toward the same idea: teachers learn best when learning is sustained, collegial, rooted in their own context, and connected to questions of meaning, not just mechanics.

This is also the philosophy behind the professional development offered through the Media Education Lab. Programs like Teaching and Learning in an AI World, a K-12 program preparing teachers to bring media literacy into the age of AI, and Pause2MAP, a digital wellness initiative helping educators and students build healthier relationships with technology, are built on the principles the research keeps pointing to. 

They run over multiple sessions rather than a single afternoon. They invite educators to try ideas with their own students between meetings and bring what they notice back to the group. They use inquiry-based frameworks of critical questions about authors, messages, and representations that apply to any medium, from a 1950s newspaper to a generative AI tool released next month. And they treat the culminating output not as a quiz score but as a teacher-designed lesson or mini-unit ready for real classrooms. Educators have rated these experiences an average of 8.9 out of 10 against every other PD they've ever attended. That's what happens when teacher learning is structured to honor the profession.

So the case for serious PD isn't really about AI. It's about whether we treat teachers as technicians delivering whatever tool arrives next, or as professionals exercising judgment in a moment that demands it. The answer shapes what classrooms look like for the next generation of learners, in every part of the world.

References

Freire, P. (1970/2018). Pedagogy of the Oppressed. Bloomsbury Academic.

GoStudent. (2025). Future of Education Report.

Hobbs, R. (2010). Digital and Media Literacy: A Plan of Action. Aspen Institute and the John S. and James L. Knight Foundation.

Hobbs, R. (2017). Create to Learn: Introduction to Digital Literacy. Wiley-Blackwell.

UNESCO. (2025). Santiago Consensus on the Teaching Profession. First World Summit on Teachers.

World Bank and UNESCO data on teacher training and class sizes in sub-Saharan Africa (2023–2025).

Youngstown State University. (2026). Teachers and AI: A Study on Confidence Gaps and Challenges. YSU Online MSEd Program.