Interact: web and android-based backchannel system to aggregate student feedback

Goh Si Hao, Soumyadeb Chowdhury, Sam Loh, Junqi Zou

Research output: Chapter in Book/Published conference outputConference publication


This paper presents, 'Interact', an interactive backchannel system providing an array of features to both the students and instructors. It allows the students to post comments, ask questions, and rate their understanding of various concepts (prepopulated by the instructor), taught in a lecture session. Additionally, the system employs text analytics using Latent Dirichlet allocation (LDA), to extract topics from the comments, and aggregate sentiments for each topic using AFINN-165 wordlist. The instructors can view: (1) top-ranked 'm' topics discussed in 'n' lectures; (2) sentiment trends for 'm' topics, and 'n' lectures, including positive and negative words; (3) popular questions asked in 'n' lectures. A user-study was conducted with 40 students and 10 academics were interviewed to understand their perception towards the system. Additionally, a crowdsource study examined the effectiveness of aggregation techniques. We believe that Interact will help to improve teaching and develop effective learning, with the aid of automatic processing, summarization and visualization of student feedback obtained through comments, questions and rating concepts.

Original languageEnglish
Title of host publicationOZCHI '17 Proceedings of the 29th Australian Conference on Computer-Human Interaction
Number of pages5
ISBN (Electronic)9781450353793
Publication statusPublished - 28 Nov 2017
Event29th Australian Computer-Human Interaction Conference, OzCHI 2017 - Brisbane, Australia
Duration: 28 Nov 20171 Dec 2017


Conference29th Australian Computer-Human Interaction Conference, OzCHI 2017


  • Backchannel
  • Sentiment
  • User-study
  • Visualization


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