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Enhancing colour-coded poll sheets using computer vision as a viable Audience Response System (ARS) in Africa

Audience Response Systems (ARS) give a facilitator accurate feedback on a question posed to the listeners. The most common form of ARS are clickers; Clickers are handheld response gadgets that act as a medium of communication between the students and facilitator. Clickers are prohibitively expensive...

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Main Author: Muchaneta, Irikidzai Zorodzai
Other Authors: Gain, James
Format: Thesis
Language:English
Published: Department of Computer Science 2018
Subjects:
Information Technology
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access_status_str Open Access
author Muchaneta, Irikidzai Zorodzai
author2 Gain, James
author_browse Gain, James
Muchaneta, Irikidzai Zorodzai
author_facet Gain, James
Muchaneta, Irikidzai Zorodzai
author_sort Muchaneta, Irikidzai Zorodzai
collection Thesis
description Audience Response Systems (ARS) give a facilitator accurate feedback on a question posed to the listeners. The most common form of ARS are clickers; Clickers are handheld response gadgets that act as a medium of communication between the students and facilitator. Clickers are prohibitively expensive creating a need to innovate low-cost alternatives with high accuracy. This study builds on earlier research by Gain (2013) which aims to show that computer vision and coloured poll sheets can be an alternative to clicker based ARS. This thesis examines a proposal to create an alternative to clickers applicable to the African context, where the main deterrent is cost. This thesis studies the computer vision structures of feature detection, extraction and recognition. In this research project, an experimental study was conducted using various lecture theatres with students ranging from 50 - 150. Python and OpenCV tools were used to analyze the photographs and document the performance as well as observing the different conditions in which to acquire results. The research had an average detection rate of 75% this points to a promising alternative audience response system as measured by time, cost and error rate. Further work on the capture of the poll sheet would significantly increase this result. With regards to cost, the computer vision coloured poll sheet alternative is significantly cheaper than clickers.
format Thesis
id oai:open.uct.ac.za:11427/27854
institution University of Cape Town (South Africa)
language eng
last_indexed 2026-06-10T12:31:45.395Z
license_str Not specified — see source repository
provenance_str_mv Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository
publishDate 2018
publishDateRange 2018
publishDateSort 2018
publisher Department of Computer Science
publisherStr Department of Computer Science
record_format dspace
source_str UCTD — University of Cape Town Open Access Repository
spelling oai:open.uct.ac.za:11427/27854 Enhancing colour-coded poll sheets using computer vision as a viable Audience Response System (ARS) in Africa Muchaneta, Irikidzai Zorodzai Gain, James Marais, Patrick Information Technology Audience Response Systems (ARS) give a facilitator accurate feedback on a question posed to the listeners. The most common form of ARS are clickers; Clickers are handheld response gadgets that act as a medium of communication between the students and facilitator. Clickers are prohibitively expensive creating a need to innovate low-cost alternatives with high accuracy. This study builds on earlier research by Gain (2013) which aims to show that computer vision and coloured poll sheets can be an alternative to clicker based ARS. This thesis examines a proposal to create an alternative to clickers applicable to the African context, where the main deterrent is cost. This thesis studies the computer vision structures of feature detection, extraction and recognition. In this research project, an experimental study was conducted using various lecture theatres with students ranging from 50 - 150. Python and OpenCV tools were used to analyze the photographs and document the performance as well as observing the different conditions in which to acquire results. The research had an average detection rate of 75% this points to a promising alternative audience response system as measured by time, cost and error rate. Further work on the capture of the poll sheet would significantly increase this result. With regards to cost, the computer vision coloured poll sheet alternative is significantly cheaper than clickers. 2018-04-24T14:01:51Z 2018-04-24T14:01:51Z 2018 Master Thesis Masters MSc http://hdl.handle.net/11427/27854 eng application/pdf Department of Computer Science Faculty of Science University of Cape Town
spellingShingle Information Technology
Muchaneta, Irikidzai Zorodzai
Enhancing colour-coded poll sheets using computer vision as a viable Audience Response System (ARS) in Africa
thesis_degree_str Master's
title Enhancing colour-coded poll sheets using computer vision as a viable Audience Response System (ARS) in Africa
title_full Enhancing colour-coded poll sheets using computer vision as a viable Audience Response System (ARS) in Africa
title_fullStr Enhancing colour-coded poll sheets using computer vision as a viable Audience Response System (ARS) in Africa
title_full_unstemmed Enhancing colour-coded poll sheets using computer vision as a viable Audience Response System (ARS) in Africa
title_short Enhancing colour-coded poll sheets using computer vision as a viable Audience Response System (ARS) in Africa
title_sort enhancing colour coded poll sheets using computer vision as a viable audience response system ars in africa
topic Information Technology
url http://hdl.handle.net/11427/27854
work_keys_str_mv AT muchanetairikidzaizorodzai enhancingcolourcodedpollsheetsusingcomputervisionasaviableaudienceresponsesystemarsinafrica

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