An Eye on the Students Face
While online learning has become a critical part of education, and training modules and new digital tools have made learning smarter and more efficient, one complaint is that traditional e-learning solutions lack the human touch. One way to bring the best out of the current generation of learners and to create a positive and attentive learning environment is to use Emotion AI. Simply put, this analyses faces in a live or recorded session and can help teachers better assess engagement levels such as boredom, confusion and frustration, delight, and neutrality and trigger additional next steps to identify students that need more attention.
Facial expression recognition is not just about catching expressions, but is designed to assess the emotional connect the students may or may not have with the content or trainer. Advanced facial recognition tools use convolutional neural networks to interpret expressions and provide insightful data on the learners’ patterns and progress.
Apart from imparting learning, live video paired with facial recognition technology help verify attendance and improve accuracy of remote testing and student access. Facial features can be matched with identity cards thus cutting off the possibility of asking another person to take the test. During the exam, Emotion AI tracks eye and head movement as well as attention span and sends red flags when possible cheating is detected. The technology can work in real time on any browser or any web or native app.
Engagement detection in online learning formats is a big challenge. Facial AI is an effective and crucial technology to address this challenge. It helps trainers mould their teaching methods and change strategies in virtual learning environments, according to the student’s emotions in real time. Integrating these tools with learning management systems can help develop an intelligent, cutting-edge e-learning approach that is learner centric, productive, and result oriented.