In her article, “Four reasons I am excited about tech in learning,” author Jenny Anderson explores the complex intersection of educational technology and its proper role in the classroom. While she acknowledges the significant risks posed by “Big Tech” incentives, she argues that with careful management, edtech (including AI) can be a tool for meaningful learning in K-12 classrooms.
The Core Challenge: Misaligned Incentives
Anderson begins by cautioning that commercial tech companies like Meta and OpenAI prioritize user engagement and market share over a child’s developmental needs.
- Avoidance of Struggle: AI tools can allow students to bypass “uncomfortable thinking” to get quick answers, which may hinder the development of essential skills like writing and problem-solving.
- The Literacy Mandate: Despite these risks, 66% of leaders state they would not hire someone without AI literacy, making it essential to prepare students for an AI-integrated future.
Four Reasons for Optimism in Education
1. Increased Vigilance and Awareness
Unlike the early days of social media, educators and parents are no longer “asleep at the switch”.
- There is a growing understanding that dosage matters and that human connection is the foundation of a flourishing classroom.
- Society is getting better at distinguishing between tech that aids learning (e.g., graphing software) and tech that merely “tranquilizes” students.
2. A Catalyst for Systemic Reform
Education systems in the U.S. face high rates of chronic absenteeism and student boredom. A quarter of kids in this country are chronically absent from school.
- Anderson suggests the “existential threat” of AI may finally force schools to rethink outdated models.
- This reform must protect “struggle” and “friction” as essential components of the learning process.
3. The Shift to “Precision Learning”
Anderson highlights a shift from “personalized learning”—which she notes has largely been a “bust”—to Precision Learning.
- Diagnosis: Like precision medicine, AI can help educators diagnose specific learning gaps with high specificity.
- Targeted Intervention: AI can recommend evidence-based actions for teachers to take, moving away from “educating to the average”.
4. Student Agency and the Desire for Rigor
Early research suggests that when students are trained on AI that uses Socratic questioning (forcing them to work harder) rather than just providing answers, they often choose the more rigorous path.
- Mastery over Ease: Students are often willing to do “hard things” if they feel they have the support to master them.
- Gen Z Skepticism: Interestingly, 80% of Gen Zers worry that relying on AI will make learning more difficult in the future, suggesting they have the agency to use the tool critically rather than blindly.
Anderson concludes by advocating for “marginal gains”—the economic idea of committing to small, daily improvements rather than seeking a single “silver bullet” solution. She encourages educators to lean into the opportunities of tech while rebuilding the “muscles of real life” and human connection.
Note: This summary covers the highlights, but the full article contains deeper insights into student psychology and specific project recommendations. You are encouraged to read the full piece at howtobebrave.substack.com.
