Term of Award

Spring 2020

Degree Name

Master of Science in Computer Science (M.S.)

Document Type and Release Option

Thesis (open access)

Copyright Statement / License for Reuse

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Department

Department of Computer Science

Committee Chair

Pradipta De

Committee Member 1

Andrew Allen

Committee Member 2

Mehdi Allahyari

Abstract

During a classroom session, an instructor performs several activities, such as writing on the board, speaking to the students, gestures to explain a concept. A record of the time spent in each of these activities could be valuable information for the instructors to virtually observe their own style of instruction. It can help in identifying activities that engage the students more, thereby enhancing teaching effectiveness and efficiency. In this work, we present a preliminary study on profiling multiple activities of an instructor in the classroom using smartwatch and smartphone sensor data. We use 2 benchmark datasets to test out the feasibility of classifying the activities. Comparing multiple machine learning techniques, we finally propose a hybrid deep recurrent neural network based approach that performs better than the other techniques.

OCLC Number

1158614770

Research Data and Supplementary Material

No

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