Online learning is more than just the future of education; it’s fast becoming the modern methodology for learning. Virtual learning platforms like Reading Plus, Aleks, IXL, and Khan Academy are implemented in school curriculums across the board. We know these tools work, and not only do they deliver potent lessons, but they allow for self-pacing. Once students are able to learn at their own pace without distraction, they can flourish as learners and reach their true potential without inhibition.

As robust as these programs are, there is always a question of how to make them better. It’s a tricky conundrum because feedback is hard to come by. Sure, we can ask students what they like and don’t like, but those answers aren’t necessarily pure. They can be clouded by a distaste for a particular subject or online instructor. Moreover, it is difficult to self-assess and truly distinguish between productive and problematic pieces of a program. In the world of video courses, I am faced with this challenge constantly. As content creators, what are we to do?

Someone has found an answer. Ross Jones, CEO of Emotuit, has pioneered a way to extract real-time data from students about engagement for e-learning products. Here’s the best part: students don’t have to do anything extra to submit feedback. Emotuit’s software is able to utilize the embedded camera in a computer to snap photos of a student’s face intermittently in order to gauge engagement. By analyzing this data, Emotuit can tell content makers what works and what doesn’t. This pure data is untainted by any sort of bias. As content makers are able to utilize this information, course production will be optimized in a whole new way.

To hear the full scoop on Emotuit, make sure to check out the entire podcast episode. For more information on Emotuit, go to