Beyond the Hype: What will education look like when the AI dust settles?
And recommendations from an award-winning edtech consultant.
For over 40 years now, we have witnessed the rise and fall of many once-heralded “revolutions” in classroom technology. From the excitement over personal computers to the promises of the internet and social media, each wave of innovation has crested amidst predictions of transforming education, only to eventually settle into more measured realities.
We stand at a similar inflection point today with AI. The current hype cycle will peak and become better aligned with evidence. Based on my knowledge of past tech revolutions, I foresee AI taking its place as a supporting asset rather than a disruptor of quality human-centered pedagogy. Wise institutions will focus less on AI itself and more on how to integrate it into the broader teaching and learning ecosystem.
Previous educational technologies all followed similar hype cycles. Initial euphoria led to disappointment as limitations became apparent. Eventually, a balanced understanding emerged of how to strategically apply new tools.
The Computer Revolution
In the 1980s, computers entered classrooms to much fanfare. But early enthusiasm faded as usage focused on rote drill-and-practice. Lack of teacher training also hampered adoption. Eventually, studies like Larry Cuban’s found the key is incorporating computers in thoughtful ways aligned with curricular goals. Computers came to be viewed not as an automatic panacea, but as powerful learning aids when guided by skilled teachers.
The Internet Boom
As the internet spread in the 1990s, extravagant visions emerged of online courses replacing traditional learning. However, early distance learning brought high drop-out rates. Lack of human interaction was a key problem. Blended models combining online and in-person education brought better outcomes. Just as computers augmented classrooms, we found the internet’s power is best harnessed in moderation, not as a substitute.
Social Media
Next, social media entered schools heralded for its collaborative promise. However, issues like privacy, distraction and digital citizenship quickly surfaced. Studies, like Danah Boyd’s, revealed that proper policies and digital literacy training were prerequisites to balancing benefits and risks. Again, sound human judgment proved vital – not just technology alone.
Each wave of technology highlighted that implementation is everything. Realizing positive potential while avoiding pitfalls requires skillfully integrating new tools into thoughtful learning experiences. As we ride the swelling AI wave, here are three key strategies I would recommend that can help institutions stay afloat:
1. Take a Balanced View of AI
With any new technology, hype tends to inflate its capabilities and downplay limitations. The same proves true with AI. We must cut through the hype with a balanced, demystified view of what today’s AI can and cannot achieve.
No question, AI excels at certain computational capabilities. Machine learning algorithms can analyze huge datasets, identify patterns, make predictions and generate new content based on parameters and training data. However, AI still lacks robust general intelligence or anything close to human-level cognition.
Current AI cannot reproduce abilities that are core to learning - capacities like cross-disciplinary problem-solving, contextual adaptation, inference, creativity and emotional intelligence. As cognitive scientist Gary Marcus notes, “AI is neither conscious nor capable of thinking deeply about situations it hasn't seen before.” For the foreseeable future, human teachers will remain essential for imparting true knowledge, reasoning skills and mentorship.
Understanding AI's current limitations is crucial as we evaluate potential applications in education. Overestimating technical prowess while underestimating the irreplaceable human elements of learning could lead institutions down the wrong path. We must approach the implementation of any AI tools with eyes wide open, neither inflated hopes nor dire fears.
2. Prioritize Teacher Training and Support
Past educational technologies floundered due to inadequate teacher training and top-down implementation. The success of any technology hinges on how skilled teachers leverage it in locally suitable ways. Institutions must prioritize sufficient professional development and ongoing support systems as AI capabilities enter classrooms.
Insufficient teacher training was a main reason why educational technologies failed to realize their promise in the past. Teachers need extended guidance and workspace to incorporate new tools into their instructional design and curricula. I recommend collaborative design communities within schools where teachers can share best practices with new technologies.
Teachers themselves will be the ultimate determinants of how to best leverage AI in service of their students’ learning. Yet quick adoption of new technologies often outpaces sufficient teacher training. Institutions must place teacher development and empowerment at the center when integrating new tools. Providing structured opportunities for teachers to gain knowledge of emerging AI applications, experiment with integrating them into the curriculum, collaborate with peers on approaches, and guide each other through challenges is imperative for success.
At the same time, detailed mandates and scripts on exactly how teachers must use AI tools will inevitably backfire. Teachers are learning designers, not solely implementers. Allow creativity, discretion, and autonomy. The most exciting applications of AI in the classroom may emerge organically from empowered teachers, not administrations. Provide rich support structures, then trust teachers.
3. Focus on Human-Centered Learning
For all the promise of AI, learning remains fundamentally a human experience. The interpersonal relationships between student and teacher, and amongst peers, underpin the classroom environment. The most worthwhile applications of AI in education will enhance these relationships, not sideline them. Leaders should think of AI as tools to enable greater teacher attention and personalization, rather than as standalone solutions.
Technology should enable positive human learning experiences. John Dewey explained that education is a deeply human process of active inquiry and knowledge construction. Tools like AI can facilitate elements of that process, but the human experience must remain the organizing center.
Deci & Ryan’s self-determination theory underscores that human relationships and agency drive engagement and motivation. Technologies like AI should aim to enrich personalized human interactions - not isolate students. Maintain learner autonomy and community according to constructivist principles.
For example, chatbots might provide personalized vocabulary practice through conversational interfaces. But well-designed dialogue, captivating storylines and thoughtful feedback matter more than the AI component itself. Keep the focus on optimal interactions between teachers and students. Use AI to enhance, not replace, human presence.
In a nutshell
The key to riding each wave of new educational technology has been integrating it thoughtfully based on learning sciences and an appreciation of irreplaceable human elements. Rather than fixating on which AI applications to adopt, focus first on designing optimal learning experiences between teachers and students. Determine core objectives, then consider how AI tools can support those experiences in cost-effective, scalable ways. Keep the human learning experience at the center, not the technology.