By: Esteban Sosnik
Most people working in education can agree that when personalization is done right it is extremely impactful on the learner. There is no better way to deliver personalization to learners at scale than with technology. In a recent article on the subject, my colleague and partner at Reach Capital, Jennifer Carolan, argued that “great teachers know that instruction designed around the individual ought not be isolating but engaging, purposeful and multi-modal.” Yet students are still spending copious amounts of time reading textbooks, which are inherently static, standardized, and unresponsive to different learning styles. Improving how students interact with such content and creating a learning experience that is more engaging and personalized could have an incredibly positive effect on students. Volley, our latest investment, takes a unique approach to doing just that.
Here’s how it works: imagine a student reading a textbook getting stuck on a concept; All she needs to do is snap a picture with Volley’s app of the textbook page she’s stuck on. Volley instantly performs a linguistic analysis of the page and extracts all the key concepts in order to deliver personalized resources from across the web. These resources are contextualized to what the student is learning to enhance the learning of those concepts. Our team at Reach sometimes calls Volley the “Shazam for learning”.
Volley’s founding team, comprised of Zaid Rahman, Carson Kahn, Ryan Orbuch, Adam Ashwal, started building Volley when they realized that the future of learning will be heavily mobile dependent. For evidence, simply observe how 14–22 year olds learn today. Their mobile devices are usually 5 inches away from their learning materials, and often used as a “tutor” to their problems while studying. Mobile is second nature to this new generation, so Volley is focusing on making this textbook to digital transition more satisfying and efficient.
When students use search engines to find resources, they’re overwhelmed with millions of resources per concept and lack a frame of reference for predicting whether a particular resource might be helpful and efficient. Google or other search engines lack the context of what the student is learning, and the results are generalized to the point of irrelevance. This is because most of the web is optimized for ad serving and not for learning. Volley offers an alternative.
Volley’s value is threefold: Firstly, as a study in the Journal of Higher Education found, more efficient study-time is predictive of learning efficacy and even graduation rates. Volley aims to cut the surrounding processes of finding relevant resources by delivering the most contextualized and highest quality content on the web. Secondly, Volley uses machine learning to computationally map the world’s knowledge. The implications of doing so are huge. You can now start delivering true personalized learning experiences, that can stitch together individual content units on the web to form a coherent learning experience. Finally, and more importantly, we are excited about Volley’s ability to combine this smart context-aware semantic search capability with the shared context students have with other students regardless of where they are. For example, Volley can statistically predict that if a resource was found useful by a student, it’s most likely going to be relevant to another student of similar academic background.
Volley is a great example of the kind of personalized learning we like to see. The product has an unconventional approach to delivering on the promise of personalized learning, while meeting students where they are: reading textbooks while using their phone as a tool to explore concepts, find better explanations, or dive deeper into an idea. At Reach, we look for tools that can marry traditional methods with cutting edge technology, in order to create ideal learning experiences for kids. We could not be happier to be partnering with Volley’s team, and supporting them as they launch this great service and build a company that could transform student learning.
*Originally posted in January 2016