A Systematic Approach for Automated Lecture Style Evaluation Using Biometric Features

An integrated system that provides automated lecture style evaluation, allowing teachers to get instant feedback related to the goodness of their lecturing style is presented. The proposed system aims to promote quality improvement of lecture delivery, that could upgrade the overall learning experience of students. The proposed application focuses on specific measurable biometric characteristics, such as facial expressions, body activity, speech rate and intonation, hand movement and facial pose, extracted through video and audio. Measurable biometric features extracted during a lecture are combined to provide teachers with a score reflecting lecture style quality both at frame rate and by providing quality metrics for the whole lecture. A pilot evaluation of the application was conducted with chief education officers, educators and students to obtain feedback on the proposed application. Initial results indicate that the proposed teacher evaluation system is innovative, and it has the potential to become an invaluable tool for educators who wish to maximize the impact of their lectures.