Thesis
Learnability through adaptive discovery tools in voice user interfaces
Master of Science (M.S.), Drexel University
May 2017
DOI:
https://doi.org/10.17918/etd-7358
Abstract
The invisible nature of VUIs has been attributed to challenging discoverability of VUIs. When discoverability is challenging, learnability can be compromised. Some researchers have designed visual tools for VUIs to help users learn as they go. However, few have used adaptation to ensure that learnability with the help of these tools extends beyond initial use. We create DiscoverCal, a calendar application designed using an adaptive discovery tool to improve learnability in VUIs. DiscoverCal is created using Api.ai enabled wall mounted display at home. We identify characteristics of discovery tools created by researchers and extend their work by designing a system that adapts based on contextual relevance and user performance, in order to extend learnability beyond initial use. We find that an adaptive approach is slightly more favorable for learnability. However, further iterations to our design of adaptivity are necessary.
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Details
- Title
- Learnability through adaptive discovery tools in voice user interfaces
- Creators
- Anushay Furqan - DU
- Contributors
- Jichen Zhu (Advisor) - Drexel University (1970-)
- Awarding Institution
- Drexel University
- Degree Awarded
- Master of Science (M.S.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Number of pages
- vi, 34 pages
- Resource Type
- Thesis
- Language
- English
- Academic Unit
- Digital Media; Drexel University; Antoinette Westphal College of Media Arts and Design
- Other Identifier
- 7358; 991014632406604721