In this episode we’re joined by Ed Buckley and Marlee Strawn, co-founders of Scholar Education, to discuss the challenges and opportunities of implementing AI in education, a traditionally slow-to-change field. Marlee shares her “lightbulb” moment when her high school teachers came to her with concerns about students using ChatGPT to write essays. This led her to discover the power of generative AI and prompt engineering. The discussion covers their unique “go-to-market” strategy, which involved self-funding an initial pilot to co-design the platform with teachers and students. This approach was critical to building a solution that addressed user fears, earned trust, and delivered significant value, providing a blueprint for successful AI adoption in highly regulated fields.

Ed and Marlee introduce their platform’s two AI agents: Pawfessor Bruce, the teacher-facing AI that helps with lesson planning and provides actionable insights, and BaxterBot, the student-facing AI that acts as a personalized tutor. They explain how these agents address the diverse needs of students, including those with special education requirements or who speak different languages. This level of personalization, previously impossible for a single teacher to manage, is a core value proposition of their product. The adoption curve for this technology was driven by teachers realizing the value of the platform, not by students using AI to cheat.

The conversation draws parallels to other industries, such as healthcare, to discuss the future of AI in the classroom. The founders believe the evolution of education will move from digitizing processes to automating them, and eventually to enabling entirely new capabilities like ambient listening and personalized lifelong tutoring. They address sensitive topics such as data privacy and consent, arguing that the adoption of these technologies will accelerate when the value they provide—like protecting a teacher from a false accusation—significantly outweighs the perceived problems. This forward-looking perspective positions Scholar Education as a trustworthy guide for the next generation of teaching and learning.

Key Takeaways:

• The initial fear of students using AI to cheat led to the creation of an AI solution that empowers teachers and personalizes learning.
• The “go-to-market” strategy for an edtech company involved self-funding a pilot to co-design the product with teachers and students, ensuring the solution was built with their needs in mind.
• Teacher-facing AI (Professor Bruce) helps generate lesson plans or works with existing ones, while student-facing AI (BaxterBot) provides personalized, on-the-spot tutoring.
• BaxterBot can be personalized to a student’s learning profile, including their reading level or accommodations for special education, enabling a level of support that was previously unattainable.
• The initial skepticism from teachers was overcome when they saw how AI could reduce their workload and provide actionable insights into student performance.
• The evolution of AI in education will move from digitizing existing processes to automating them, and then ultimately to enabling entirely new capabilities that weren’t possible before.
• The adoption of new technologies, such as ambient listening, will accelerate when the value of the technology significantly outweighs the perceived problems or friction.
  The future of education could include an AI that acts as a student’s lifelong tutor, retaining a consistent memory of their entire K-12 career and adapting to their needs over time.
• The widespread use of AI in the classroom hinges on navigating sensitive debates around data ownership, privacy, and consent, especially for students who cannot directly consent.
• Past experiences with tech mandates, like Electronic Medical Records, show that a fragmented industry with competing interests can hinder data flow, a lesson that is being applied to the AI education space.

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