VizScribe: A visual analytics approach to understand designer behavior. Issue 100 (April 2017)

• Record Type: Journal Article
• Authors: Chandrasegaran, Senthil; Badam, Sriram Karthik; Kisselburgh, Lorraine; Peppler, Kylie; Elmqvist, Niklas; Ramani, Karthik
• Is Part Of: International journal of human-computer studies. Issue 100(2017)
• Page Start: 66
• Page End: 80
• Publication Date: 2017-04
• Subjects: Protocol analysis -- Design research -- Design behavior -- Human-computer interaction -- Information visualization -- Visual analytics; Human-machine systems -- Periodicals; Systems engineering -- Periodicals; Human engineering -- Periodicals; Human engineering; Human-machine systems; Systems engineering; Periodicals; Electronic journals; 004.019
• DOI: 10.1016/j.ijhcs.2016.12.007
• Languages: English
• ISSNs: 1071-5819

Abstract

Abstract: Design protocol analysis is a technique to understand designers' cognitive processes by analyzing sequences of observations on their behavior. These observations typically use audio, video, and transcript data in order to gain insights into the designer's behavior and the design process. The recent availability of sophisticated sensing technology has made such data highly multimodal, requiring more flexible protocol analysis tools. To address this need, we present VizScribe, a visual analytics framework that employs multiple coordinated multiple views that enable the viewing of such data from different perspectives. VizScribe allows designers to create, customize, and extend interactive visualizations for design protocol data such as video, transcripts, sketches, sensor data, and user logs. User studies where design researchers used VizScribe for protocol analysis indicated that the linked views and interactive navigation offered by VizScribe afforded the researchers multiple, useful ways to approach and interpret such multimodal data. Abstract : Graphical abstract: Abstract : Highlights: VizScribe is a framework to represent multimodal design protocol data. VizScribe represents protocol data as interactive timeline and text visualizations. Links between protocol data are revealed through brushing & linking interactions. User studies show word cloud and sketch & transcript timelines are most versatile. The framework can be extended to represent new forms of protocol data.