Steven Levy’s book, In the Plex, quotes Tim Armstrong, Google’s top sales executive in New York as saying, “[Our job was] bringing science to the art of advertising and being able to scale the art of advertising through science.” SlideSpeech aims to take the same concepts and apply them to learning: bringing science to the art of learning and being able to scale the art of learning through science.
In search, Google tapped into our fundamental need for answers. When we have some idea what we want, Google can help us to find it. The focus at Google is getting that match right, fast. Unfortunately, learning has two characteristics which prevent search answers from being learning solutions: one is the meta-problem of knowing what to ask and the other is the importance of learning from mistakes.
The traditional educational system, like the traditional system of advertising before Google, actually depends on ignorance about what works and what doesn’t work to justify the prices charged. A “good” school does not necessarily offer measurably more learning; quality is gauged by reputation. In advertising, Google found very effective ways to measure and price the actual desired results of an ad: sales of the advertised product. In learning, we need to build equally sophisticated systems to measure and price the desired results from a learning experience: increased knowledge and skills.
The keys to success here are scale and data. Learners own their knowledge. Learning should be an investment with a future payoff. Yet most people lack data about the extent and value of the things they know. The extent or amount of knowledge is currently measured using the extraordinarily coarse-grained metric of the diploma or degree. Meanwhile, the cost of a degree has gone up significantly relative to the return from having a degree in terms of earnings. Student loan debt is a huge problem.
Google determines the value of an ad using an auction. Advertisers bid for the opportunity to attract customers to their product. Simultaneously, consumers vote (via click-through) for the advertisements and products they find most attractive. Thus Google’s system helps make connections between what consumers want to buy and what advertisers have to sell. The effectiveness of each ad is measurable at the end of the process when there is a conversion, or sale.
The traditional educational system, like the traditional system of advertising before Google, involves pre-payments. This puts all the risk on the buyer. If the knowledge acquired turns out to be worthless or the advertisement fails to attract customers, the schools or media channels keep the money while the students or the advertisers take the loss. SlideSpeech aims to put payment where it belongs to align everyone’s incentives toward maximizing learning effectiveness: at the end.
Learners need meta-data about their learning: what they know, what they need to learn next and the value of having specific knowledge. This data can be organized in a system which includes fine-grained progress tracking, visualized connections from the current state of knowledge to possible future states, and the cumulative price paid by learners who previously reached each future state. Knowledge has time value. Given the speed with which knowledge advances, the value in learning new knowledge comes from learning it sooner and faster. Thus, the first learners of something new should pay the most, while everyone else who comes later should pay less. This aligns with the reality of internet distribution: once content is created, it can be distributed globally at scale.
Teachers in the SlideSpeech system are paid for completions. Students must pay for their completions to have their progress tracked. This is the restaurant model, where you pay for what you eat after you eat it. In a restaurant, you might go in the back and wash dishes if you can’t pay your bill. SlideSpeech offers a similar option: create content for other learners and earn out the amount owed to get the completion credit. Thus SlideSpeech becomes a collaborative, crowd sourced platform for learning materials like Wikipedia, but monetized at the point of progress tracking.
