Evaluation Controlled experiments Natural settings Any setting not involving users (expert reviews) Expert Reviews Design experts Visualization experts Usability experts Domain experts Types of Expert Reviews Heuristic evaluation (golden rules) Guidelines review Consistency inspection Cognitive walkthrough Metaphors of human thinking Formal usability inspection (courtroom style) Accesibility inspection Eight Golden Rules of Design Strive for consistency Cater for universal usability Offer informative feedback Design dialogs to yield closure Prevent errors Permit easy reversal of actions Support internal locus of control Reduce short-term memory load Controlled Experiments Experiments in the lab Controlled confounding variables Measure one or more quantitative variablesUsability testing Living labs What to Measure? Time to learn Speed of performance Rate of errors Retention over time Subject satisfaction Variables Independent variables (causes) Dependent variables (effect) Extraneous variables (that can affect the experiment) Controlled Experiment example Tasks and conditions Kim, Y. and Heer, J. (2018), Assessing Effects of Task and Data Distribution on the Effectiveness of Visual Encodings. Computer Graphics Forum, 37: 157-167. doi:10.1111/cgf.13409 Controlling extraneous variables Kim, Y. and Heer, J. (2018), Assessing Effects of Task and Data Distribution on the Effectiveness of Visual Encodings. Computer Graphics Forum, 37: 157-167. doi:10.1111/cgf.13409 Tasks Kim, Y. and Heer, J. (2018), Assessing Effects of Task and Data Distribution on the Effectiveness of Visual Encodings. Computer Graphics Forum, 37: 157-167. doi:10.1111/cgf.13409 Results Kim, Y. and Heer, J. (2018), Assessing Effects of Task and Data Distribution on the Effectiveness of Visual Encodings. Computer Graphics Forum, 37: 157-167. doi:10.1111/cgf.13409 Usability Testing
Natural Settings Involving Users Observation Interviews Logging Triangulation Different researchers observe the same effect.
Interviews Unstructured Structured Semi-structured Focus group Telephone/online interviews Questionnaire Like interviews but without the researcher present
Likert Scale What do you think?
Strongly disagree Disagree Okay Agree Strongly agree More About Likert Scales Can be 3, 5, 7, or more responses Continuous or discrete Middle response is the balance Observation User's setting Can be direct or indirect Direct Observation in the Field Ethnography
Direct Observation in Controlled Environments Direct Observation: Tracking Users Diaries Interaction logs and web analytics MILCS Multi-dimensional In-depth Long-term Case studies Focus groups One researcher, many attendees
Prototyping Low vs. high fidelity? Read data Build scenarios, tell a story Running a Usability Study Validity Checks Earlier stages:Observe and interview target users (needs assessment) Design data abstraction/operation (data types, transformation, operations) Justify encoding/interaction design (design heuristics, perception research) Informal analysis/qualitative analysis of prototypes (task-based) Algorithm complexity analysis/evaluation Mid- and later stages:Qualitative analysis of system (task-based) Algorithm performance analysis Lab or crowdsourced user study Field study of the deployed system Formal Usability Study Goal: Does the visualization allow the user/analyst to perform key tasks? Task-Oriented Visual Insights Basic insights:Read a value Identify extrema Characterize distribution Describe correlation Comparative insights:Compare values Compare extrema Compare distribution Compare correlation Usability Study: Logistics You will need:Visualization with test data loaded Consent form (if required) Task list Protocol (study procedures and debrief questions) Surveys/interviews and any additional data-collection instruments Audio or video recorder, notepad How Many People Do You Need? "Lab" Doesn’t Need to Mean a Formal Lab Software for Collecting Audio/Video Video of user Screencapture of user actions Audio of entire session Online Tools Surveys Mouse tracking/navigation tracking You’ve Collected Data Task completion Time on task Notes Interview responses Survey responses ...Then what? How is the task completion recorded, does the analyst note it themsleves, do they write something down.
What is the Analyst’s Information Scent? A term originating from Peter Pirolli and Stuart Card PARC looking at meaning
Accounts for not just completion but also situating WHAT the person was doing, may wish to do think aloud as well. It’s not always obvious what leads to the challenge. Like a detective, not always obvious. Transating to design.
MoSCoW Prioritization Discuss brief history, came from the dynamic software development method.
Severity Ratings Not a real problem Cosmetic Minor usability issue Major usability issue Critical issue Limitations Ecological validity Are performance-oriented tasks the complete story? References Shneiderman, B. and Plaisant, C., 1987. Designing the user interface: Strategies for effective human-computer interaction Rogers, Y., Sharp, H., Preece, J. and Tepper, M., 2007. Interaction design: beyond human-computer interaction. Martin, D.W., 2007. Doing psychology experiments. Cengage Learning.