How did your education and previous professional experience shape your current work at MoxieReader?
Both of my parents were classroom educators, and I was working in schools before I finished high school, so you could say I’ve never not been a part of the education field. I wrote my honor’s thesis on the social impact of the introduction of the internet in Australia, and built the first education internet service provider and learning management system in Australia. That company grew to a 75-person staff and I later sold it before moving on to my next project: founding the National Schools Interoperability Program in Australia. My family and I later moved to the US and worked on state and not-for-profit projects before founding MoxieReader. MoxieReader is really the culmination of my work in edtech and my passion for education.
How do you hope your work at MoxieReader will change the way students approach reading and literacy?
My hope is that MoxieReader will be an example of leveraging edtech to achieve MoxieReader’s goals of getting students to read more and of helping them build that daily reading practice in a fun and engaging way. We also aim to extend the reach of classroom influence by engaging students with real-time team interactions and using electronic nudges to help parents to know when and how to help their children.
What broad trends do you think will have the most impact on learning in the years ahead?
For me, it’s utilizing machine learning to both excite teachers and impact student agency. It starts when we make the IT disappear into daily classroom practice. This gathering of data without impact can be used to enhance teacher capability by identifying and removing inefficient classroom practice, by giving guidance on how to provide differentiated instruction, and by saving teacher time and overhead, which opens up classroom time for more personalized instruction. However, the truly massive leap comes when we can use machine learning to provide feedback and guidance to students independent of one-on-one teacher instruction. Machine learning offers the promise of domain-specific guidance and feedback that takes the advanced learning pedagogies and classroom instructions which are only available to the highest fee-paying students and makes them available in almost every connected classroom on the planet.
What are your future plans, if any, for MoxieReader?
On the one hand, it’s pretty simple, actually. We plan to reach as many classrooms as we can to inspire kids to develop a daily reading practice. That's no small goal, as no other activity is so impactful and accessible as reading. On the other side of the coin, we have pretty technically sophisticated plans, too. Machine learning will form the backbone of how we predict and apply the suggestions, prompts, and interventions that can best assist learners. For example, our book review feature will grow into a full, guided, and reflective writing system that helps students from all points on the literacy spectrum.
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Image: Courtesy Dan Ingvarson