System Design for Self-monitoring Sedentary Behaviors
System Design for Self-monitoring Sedentary Time and Working Behaviors
Co-authors: Jonathan Griffin, Thalia Otamendi
UBC CPSC 544 Human Computer Interaction (HCI)
Tools: Usability Heuristic Audits, Low / High Fidelity Prototyping
UBC's Designing for People (DFP) is a human-centered design cluster that integrates interdisciplinary research methods and teamwork to solve societal and technical problems (https://dfp.ubc.ca/). The CPSC 544 Human-Computer Interaction course is one of the required courses for the Design for People trainees.
College students spend a vast majority of their work/leisure time sitting and looking at screens. This frequency of sedentary behavior and high-volume screen time has shown to negatively affect physical and mental well-being. Most applications that focus on solving this issue do so by scheduling regular breaks for users, but do not necessarily prompt individuals to take meaningful breaks. Additionally, these apps rely on constant user interaction and there is no substantial evidence that users look away from their screens or get any exercise. As such, this project targets college students who are interested in (1) becoming more efficient with their work habits and (2) incorporating healthier habits into their work day. The research of the project adopted the five stages of the Research Thinking Life Cycle - Empathise, Define, Ideate, Prototype, and Test.
Affinity diagram.
One of the three personas.
My team and I developed three personas (primary persona, secondary persona, anti-persona) to support our design directions. To demarcate our personas, we focused on aspects where participants had strong or differing experiences or opinions. We used quotes to embrace the overall feel of different individuals. By concentrating on divergent and strong narratives, we identified eight behavioural characteristics shown on their profiles. We then developed use case scenarios and identified and prioritized a list of possible features that were crucial to our design. The features incorporate the main goals this project is trying to achieve: blocked distraction while working, forced breaks, and nudges toward non-sedentary breaks. The combination of these is essential to the overall objective, which is to enhance productivity while incorporating better overall wellbeing. The six main features to our design include: 1) a forced break option, 2) healthy break suggestions, 3) customizable notifications, 4) productivity detection, 5) a website/application blocker, and 6) a productivity report.
System interaction mapping.
Storyboard of user interaction patterns.
Low-fidelity prototype.
For the walkthrough test, we wanted to see how well our interface design and underlying conceptual model aligns with users’ mental models. We performed 6 walkthroughs. We used high-level directives only (i.e., pre-prepared steps that we asked the participants to perform, followed by expected system responses that we facilitated with our paper prototype). We conversed with the users throughout and answered their questions as they posed them. We also recorded users and our own written feedback based on these walkthrough. We then asked ourselves with the following four questions: (1) Will the user try to achieve the right action? (2) Will the user notice that the correct action is available? (3) Will the user associate the correct action with the effect that the user is trying to achieve? (4) If the correct action is performed, will the user see that progress is being made towards solution of the task?
Low-fidelity prototype - two interfaces of the system.
After designing the original system, we introduced an alternative interface that we will test for usefulness and usability vis-a-vis our original design. As suggested by Tohidi et al. (2006), alternative designs may allow for a more accurate comparative evaluation, so we evaluated usability and usefulness of the two interfaces. We compared the data and tried to determine whether our original interface or a new interface offers a performance benefit for scheduling a work/break session.
The following step was to conduct the experiment design. We did a mixed-methods 2 x 2 mixed factorial design: 2 levels of expertise (between subjects) x 2 interface designs (within-subjects), followed by open-ended questions. Our collected quantitative data includes two independent variables: A) Expertise with computers (2 levels: Computer Science students vs. non-Computer Science students); B) Interface (2 levels: Original Interface vs. Alternative Interface) and three dependent variables: A) Speed of entering a work session with a break in-between; B) Accuracy of entering a work session with a break in-between; C) Subjective satisfaction with the system. For the qualitative data, we collected the overall satisfaction marks for each of the two interfaces, as well as the text data in the given three open-ended questions.