The Impact of AI on Learning: Navigating Challenges and Opportunities
Recent findings about the negative impact of AI on learning may spark a national debate, but they are not surprising to learning scientists. In fact, these results highlight a long-standing trend in the United States of using what “feels right” or “sounds good” rather than following established educational research.
The Current Landscape: A Study from MIT
A recent study from the Massachusetts Institute of Technology shows that students’ overreliance on technology in general, and AI in particular, ignores essential learning processes at crucial stages of cognitive development in childhood and adolescence. There are numerous examples of technology interfering with the development of critical thinking skills. This includes replacing handwriting with keyboarding, reducing the importance of students automatically retrieving basic knowledge, and providing students with answers before engaging in productive combat.
Balancing AI and Learning Science
AI should undoubtedly play a role in supporting learning, but it must be done in a way that enhances rather than detracts from the core principles of the science of learning. The responsible and effective use of AI requires sound data and oversight. When AI is based on a complete, accurate view of each student, educators can quickly make lessons more contextual and provide practice within each student’s zone of next development. In this way, AI becomes a tool that deepens thinking, supports personalization, and accelerates meaningful academic growth.
Comparative Insights: Declining Test Scores
However, to see the consequences of our failure to use technology in a way that follows evidence-based guidelines rather than circumventing them, one need only look at our students’ declining test scores. Not only are the scores lower in absolute terms, but they are also lower when compared to our Asian and European counterparts who have managed the use of technology wisely, particularly among younger students.
Learning from Success: The Mississippi Miracle
One notable exception to our collective national dissonance with the learning sciences is the widespread adoption of reading science requirements in more than 40 states since 2019. While this recent success is a glimmer of hope, the entire story is far more complex and leaves much uncertainty about how schools will respond to AI.
The “Mississippi Miracle” launched the science of reading movement when Mississippi essentially went from worst in the country to top 10 in NAEP fourth-grade reading scores in just six years. What is less well known is that Mississippi’s implementation came 20 years after the National Reading Panel report, which left little debate about how best to teach students to read.
Even then, Mississippi’s spectacular performance wasn’t enough. Rather, it was the groundswell of parental outrage, based on their firsthand experiences during the pandemic and spurred by the 2022 podcast “Sold a Story,” that led to a near-national mandate for evidence-based reading practices.
Preparing for the Future: Embracing Science Learning
It’s unclear what spark might ignite a national mandate around AI and learning science. It could be a family pushback against the $30 billion market for devices in schools. Or professional health advice on AI and adolescent well-being.
Leadership and Change: The Workers Behind the “Miracle”
To be clear: The Mississippi Miracle was not a miracle. It was created by courageous leaders who were willing to abandon wishful thinking about technology and instead turn to the science — and the hard work that comes with it — of making systemic changes to teach children to read properly.
A glimmer of this courage shines from organizations that highlight the most essential elements of effective learning, address ethical considerations in the use of AI, and highlight the complexity of human thought that integrates emotions, context, nuance, and embodied experience. For example, the Collaborative for Academic, Social, and Emotional Learning recently devoted several conference sessions to the connections between social-emotional learning and AI.
At the state and local levels, legislators and education leaders in Mississippi took on the work on the ground. They changed their literacy policies, implemented comprehensive strategies, introduced new standards, hired additional literacy coaches, and spent years refining communications and persuading families and educators to give the evidence-based approach time to make an impact.
The Path Forward: Ensuring Effective AI Integration
The real question is not what works in education. The science of learning has already provided an answer to this. The question is whether we have the collective will to ensure that AI in schools is informed by the same insights – and based on the kind of complete, high-quality student data that allows it to truly support learning.
Strong AI will only emerge from strong data that is based on learning science findings and used in a targeted manner. Without it, we risk repeating the very mistakes we are trying to solve.
Nancy Weinstein, MindPrint Learning & Otus
Nancy Weinstein is the founder and CEO of MindPrint Learning and Chief Innovation Officer at Otus.
Latest posts from eSchool media contributors (view all)
For more information, visit Here.
“`
