Design of an Attention Monitoring Virtual Classroom, With Retraction Mechanism for Students’ Active Participation

Abstract

Using available intelligent virtual classroom systems in teaching a conventional Nigerian undergraduate program comes with a major challenge of managing and monitoring over populated students which gave rise to the development of the Interactive, Intelligent Virtual Classroom. Object-oriented analysis and design methodology (OOADM) was adopted for the study and five modules was developed to achieve the objectives of the design. An Artificial Intelligent model was trained to identify learners’ distraction using body posture, eye closure, mouth opening, and body presence. Captcha mechanism was used to confirm distraction while an automated phone call was used to retract distracted learners back to an ongoing class session. Chat GPT Large Language Model was used through its Application Programming Interface to reenforce learning, provide counselling and generate reports. A firebase real-time database was used to hold the data while a web application was developed for user interface.  The system was able to identify distraction and recall learners back to class. It was also able to interact with the distracted learners to gather more information as to the cause of their distraction which it further used to provide informed counselling.

Keywords: Attention Monitoring, Automated classroom phone-call, Intelligent Classroom, Learning Enforcement, Classroom Retraction, Virtual Classroom.