Abstract:
In this paper, we propose a multimedia framework to automatically profile student-teacher interaction during a lecture
using a mobile. We employ audio, video, and text analysis to
derive a subset of attributes that quantify student-teacher interaction. The profile thus created provides critical feedback
to the teachers to improve their pedagogy. In the literature,
there have been works on measuring the state of students in
a classroom, such as alertness level and interest; however, to
the best of our knowledge, there are no works on quantifying
student-teacher interaction. We have built a prototype system
to demonstrate the framework. Experimental results on real
classroom data demonstrate the efficacy of our method. This
is an important attempt towards building a complete profile to
automatically characterize lectures in school and colleges
