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Enhancing User Performance: Metrics and Methods for Evaluating Usability in New Interfaces

This document explores motivations and methods for evaluating user performance with new tools and interfaces. It emphasizes the importance of defining performance metrics, such as time, accuracy, recall, and satisfaction, when utilizing innovative user interfaces. By integrating principles from cognitive psychology and anthropology, we can conduct empirical studies that verify hypotheses regarding user task execution. Additionally, it discusses scenario-based usability tests and the significance of qualitative and quantitative analysis in reporting findings, ensuring that research leads to actionable insights for improved design.

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Enhancing User Performance: Metrics and Methods for Evaluating Usability in New Interfaces

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  1. Usability and Evaluation Motivations and Methods

  2. Motivations • Define a metric for performance of users when using new tools, interfaces, visualizations etc. • Verify scientific, innovative contributions. • Reduce cost of redesigning a new product.

  3. Ideal • Come up with theories like Fit’s Law so we won’t need to run user studies at all 

  4. Performance • New tools, user interfaces (graphical or not), visualizations require users to: • perceive, • interpret and • execute tasks. • Performance is measured in: • Time • Accuracy • Recall • Satisfaction

  5. Overlaps • Cognitive Psychology: the study of how people think, perceive, remember, speak and solve problems. Adopts a very empirical, scientific study method. • Cultural and Social Anthropology: investigates effects of social and cultural norms on individual behavior. Field studies is a common research method. • Schools of Information (iSchools), Graphic Design, Communications, Marketing

  6. Usability in HCI • Very empirical: carefully designed controlled experiments. Has to be designed to verify a hypothesis. Hypothesis: “Users will outperform in executing task T when they use technique A instead of technique B”

  7. Task • Thy your user ! • Thy your task ! • Most complicated tasks are a culmination of simple building block tasks. • Sorting documents: • Access individual documents (point, select, click) -> • read titles -> • categorize (re-label, change location etc)

  8. Scenario Based Usability Tests • Let users achieve identified tasks in a convincing scenario! • Hard to achieve: • Nature of the controlled experiment requires as minimum uncontrolled variables as possible whereas a convincing scenario requires complexity.

  9. Designing and Running an Experiment • Identify hypothesis • Identify tasks • Design your tool, interface, visualization after these stages or at least re-visit your initial design • Identify dependent and independent variables • Within vs between subjects designs • Randomization • Demographics

  10. Lab Study

  11. Evaluate the results of your evaluation  • Statistical analysis • ANOVA • Chi-square tests • Regression • …

  12. End of Controlled Studies • Limitations: how to measure enjoyment, creativity • “our tool let people discover new things … encourage them to try things that are not recommended by their friends…” • Alternatives: • Qualitative methods • Think-aloud protocols • Count a-ha! moments • Longitudinal studies • Interviews • Surveys • Focus Groups

  13. Analyzing Qualitative Data • Easier to collect, harder to interpret • Quantitative analysis applied to qualitative data • http://www.atlasti.com

  14. Reporting: Writing the Paper • Whatever you do, what is really important is how you present it. • A quantitative experiment is easier to report. • You have to make sure you don’t arrive at a “big” conclusion based on little evidence, little results. • On the other hand you have to emphasize importance of your findings.

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