Software support for experience sampling
| dc.contributor.advisor | Mandryk, Regan | en_US |
| dc.contributor.advisor | Gutwin, Carl | en_US |
| dc.contributor.committeeMember | Deters, Ralph | en_US |
| dc.contributor.committeeMember | McQuillan, Ian | en_US |
| dc.contributor.committeeMember | Morrison, Todd | en_US |
| dc.creator | Lippold, Mike | en_US |
| dc.date.accessioned | 2011-01-07T13:09:01Z | en_US |
| dc.date.accessioned | 2013-01-04T04:23:29Z | |
| dc.date.available | 2012-02-25T08:00:00Z | en_US |
| dc.date.available | 2013-01-04T04:23:29Z | |
| dc.date.created | 2010-12 | en_US |
| dc.date.issued | 2010-12 | en_US |
| dc.date.submitted | December 2010 | en_US |
| dc.description.abstract | User interface design is becoming more reliant on user emotional states to improve usability, adapt to the user’s state, and allow greater expressiveness. Historically, usability has relied on performance metrics for evaluation, but user experience, with an emphasis on aesthetics and emotions, has become recognized as important for improving user interfaces. Research is ongoing into systems that automatically adapt to users’ states such as expertise or physical impairments and emotions are the next frontier for adaptive user interfaces. Improving the emotional expressiveness of computers adds a missing element that exists in human face-to-face interactions. The first step of incorporating users’ emotions into usability evaluation, adaptive interfaces, and expressive interfaces is to sense and gather the users’ emotional responses. Affective computing research has used predictive modeling to determine user emotional states, but studies are usually performed in controlled laboratory settings and lack realism. Field studies can be conducted to improve realism, but there are a number of logistical challenges with field studies: user activity data is difficult to gather, emotional state ground truth is difficult to collect, and relating the two is difficult. In this thesis, we describe a software solution that addresses the logistical issues of conducting affective computing field studies and we also describe an evaluation of the software using a field study. Based on the results of our study, we found that a software solution can reduce the logistical issues of conducting an affective computing field study and we provide some suggestions for future affective computing field studies. | en_US |
| dc.identifier.uri | http://hdl.handle.net/10388/etd-01072011-130901 | en_US |
| dc.language.iso | en_US | en_US |
| dc.subject | Mouse dynamics | en_US |
| dc.subject | Affective computing | en_US |
| dc.subject | Experience sampling | en_US |
| dc.title | Software support for experience sampling | en_US |
| dc.type.genre | Thesis | en_US |
| dc.type.material | text | en_US |
| thesis.degree.department | Computer Science | en_US |
| thesis.degree.discipline | Computer Science | en_US |
| thesis.degree.grantor | University of Saskatchewan | en_US |
| thesis.degree.level | Masters | en_US |
| thesis.degree.name | Master of Science (M.Sc.) | en_US |