As learning becomes increasingly online, the more challenging it becomes to deliver engaging, high quality and impactful education for students. While attention lapses have been a regular occurrence in the traditional classroom, it has been found to occur with even greater frequency in online learning, where learners are prone to digital multitasking. 

In a typical classroom a teacher has the ability to detect and regain learner attention through various pedagogical approaches and thus gets the reassurance that the students have really understood the content.  But the absence of any feedback on learner engagement in online learning has kept the teachers in the dark.

While the education market has been a driver of growth for tech giants, it has almost unanimously been dissatisfied by features that limit learner feedback and inhibit reproduction of the best of classroom learning experiences.

BrainAlive’s FOCII is a comprehensive feedback solution that provides the teacher with the all necessary feedback on content engagement and learner engagement. It uses state of the art machine learning algorithms to report on the content relevance and engagement for the target learners.

Content Engagement

The successful performance of a content depends on how well the resource is designed and delivered. Equally important is the relevance of the content to the target audience. FOCII’s algorithms assess the verbal and non verbal components of the video to report the design and delivery appropriateness of content. Further, it also analyses learner response in real time to map the content relevance and thus the overall engagement level of the content.

Learner engagement

FOCII’s webcam based real-time learner engagement feedback system is designed to help facilitate and enhance staff – led live and blended instruction. FOCII’s advanced algorithms decodes user behavior through webcam and converts it into useful feedback on learner’s conduct and cognitive engagement. Conductive engagement feedback provides the information on how much adherence the learner exhibited while remotely engaging with the content. Just like that in a traditional classroom where the teacher gets the feedback on student interest through observing their posture, response behavior etc., in FOCII’s environment as well the teacher gets feedback on learner presence, their eye movements, facial response and more.

Cognitive engagement feedback collected through pupil fixation, aversions and divergence patterns provide information working memory utilizations while engaging in learning tasks.

For more advanced insights and analytics, FOCII also collects BCI data in real time to provide feedback on the user’s mental engagement with the content. Highly engaging resources have been found to excite the mental state of the users  resulting in elevated intent and improved learning outcomes.

The feedback on learner conduct and cognitive engagement is collectively used to let the teacher get a good understanding on whether the learner has understood the content or not. 

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