'Nestor,' a new piece of software from French education technology company LCA Learning, uses advanced facial recognition software to perform a task that teachers deal with constantly when conduct in-person classes. It takes a good teacher little more than a glance during a lesson or lecture to recognize whether students are engaged with the material -- facial expressions and body language go a long way in communicating interest. LCA Learning has taken that common sense and applied it to the digital world with Nestor.
Professors and teachers can use the Nestor platform to broadcast their lessons online. Not only does it stream the lecture and enabled mid-lesson quizzes to keep students engaged, but it uses facial recognition to register whether students are engaged with the material. This lets teachers gather metrics about the most and least engaging aspects of their lessons, and it gives students a gamified incentive to stay focused throughout.
Key Themes Behind This Trend
- Facial Recognition in Education
- The application of facial recognition software to evaluate student focus can be expanded to various educational platforms and institutions.
- Gamification of Learning
- Nestor's use of gamification through facial recognition tracking to encourage student engagement presents opportunities for other education-centered businesses.
- Remote Learning Engagement
- Nestor's facial recognition technology offers a solution for remote teaching with enhanced abilities to monitor student engagement compared to traditional online learning tools.
Where This Applies
- Education Technology
- The integration of facial recognition software in the edtech sector can provide a significant boost for various educational technology companies.
- Online Learning
- The use of Nestor technology presents unique opportunities for online learning platforms to increase student engagement, retention, and gamification.
- Education Analytics
- Nestor's facial recognition system offers education analytics software providers the ability to monitor student behavior and preferences more closely, leading to better insights for instructors.
