Matching Items (3)
Filtering by
- All Subjects: Crowdsourcing
- Creators: Wilkerson, Kelly
- Creators: Beerman, Eric Christopher
- Creators: Chavez-Echeagaray, Maria Elena
- Member of: Theses and Dissertations
- Status: Published
Description
Crowdsourcing has become a popular method for collecting information from a large group of people at a low cost. This thesis looks at whether crowdsourcing is viable to collect data for Human Computer Interaction research and comparing collaborative crowdsourcing with individual crowdsourcing. It was hypothesized that collaborative crowdsourcing would provide higher quality results than individual crowdsourcing due to intrinsic motivation. The research draws upon the use of three things: top 10 usability problems, heuristic evaluation and WAMMI survey to measure the two groups. The two groups used these tools to analyze the website: Phoenix.Craigslist.com. The results were compared against each other and against a heuristic evaluation score given by an HCI researcher to determine their accuracy. The results of the experiment failed to confirm this hypothesis. In the end, both groups provided accurate results and were only marginally different from each other.
ContributorsGupta, Kartik (Author) / Atkinson, Robert (Thesis director) / Chavez-Echeagaray, Maria Elena (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The area of real-time baseball statistics presents several challenges that can be addressed using mobile devices. In order to accurately record real-time statistics, it is necessary to present the user with a concise interface that can be used to quickly record the necessary data during in-game events. In this project, we use a mobile application to address this by separating out the required input into pre-game and in-game inputs. We also explore the use of a mobile application to leverage crowd sourcing techniques, which address the challenge of accuracy and precision in subjective real-time statistics.
ContributorsVan Egmond, Eric David (Author) / Tadayon-Navabi, Farideh (Thesis director) / Wilkerson, Kelly (Committee member) / Gorla, Mark (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-05
Description
Due to its difficult nature, organic chemistry is receiving much research attention across the nation to develop more efficient and effective means to teach it. As part of that, Dr. Ian Gould at ASU is developing an online organic chemistry educational website that provides help to students, adapts to their responses, and collects data about their performance. This thesis creative project addresses the design and implementation of an input parser for organic chemistry reagent questions, to appear on his website. After students used the form to submit questions throughout the Spring 2013 semester in Dr. Gould's organic chemistry class, the data gathered from their usage was analyzed, and feedback was collected. The feedback obtained from students was positive, and suggested that the input parser accomplished the educational goals that it sought to meet.
ContributorsBeerman, Eric Christopher (Author) / Gould, Ian (Thesis director) / Wilkerson, Kelly (Committee member) / Mosca, Vince (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-05