Adaptive Tutoring in Digital Learning

This research delves into the intriguing realm of online learning and explores the challenges in tracking student engagement in virtual classrooms. As the pandemic prompted a rapid shift from traditional classrooms to digital learning, numerous e-learning platforms emerged, but understanding and measuring engagement became a significant concern.

Engagement is the compass that guides young minds through the digital landscape of learning.

  • In a traditional classroom setting, teachers can readily assess student engagement and adapt their teaching accordingly. However, virtual classrooms, especially in large settings, hinder teachers from individually monitoring each student's engagement while simultaneously conducting the class. Online engagement encompasses more than mere attendance; it involves attentiveness, interest, and emotional investment in the learning process. Determining these aspects in an online setup, where students learn at their own pace, presents difficulties in accurate measurement.

  • Nonetheless, online learning also introduces novel approaches to gauge engagement. E-learning platforms can track various indicators, such as login frequency, task completion time, assignment turnaround speed, and active participation in discussion forums. This data can aid teachers in refining their teaching methods and strategies to foster better engagement among students. Moreover, specialized tools, like eye trackers, system cameras, and EEG sensors, offer additional insights into students' focus and concentration levels during digital learning sessions.

  • Despite the challenges, the opportunity to accurately measure engagement in online learning is immense. Teachers can leverage data from e-learning platforms and employ specialized tools to adapt their teaching methods effectively. By combining quantitative data from the platforms with their qualitative understanding of student learning, educators can ensure students remain engaged in this new era of digital education.

Students : Deep Dwivedi (IIIT-Delhi)
Superviser : Dr Jainendra Shukla (IIIT-Delhi)
Co-Superviser : Dr Mukesh Mohania (IIIT-Delhi)