How Do We Measure That?! Quick Scale Development
Authors
Data science requires metrics. But how does a researcher measure constructs such as delight, immersion, or intention to use? It’s best to develop a suitable measure, rather than to just throw something together or use an inappropriate scale. This course presents seven simplified steps for developing a valid and reliable measure. The new scale can then be used to quantify and explain user behavior, make decisions and predictions, and build models. This half-day class is intended for anyone who desires a rapid but thorough overview of how to develop a measure, and it requires a modest understanding of statistics.
Research Questions / Practical Problems
Question signals indexed for this paper.
- 100%
How Relevant is Hick's Law for HCI?
CHI '20· Visualization Perception & Cognition +1
- 100%
False Positives vs. False Negatives: The Effects of Recovery Time and Cognitive Costs on Input Error Preference
UIST '21· Visualization Perception & Cognition +1
- 75%
How Do We Measure That?! Quick Scale Development
CHI '18· User Research Methods (Interviews, Surveys, Observation)
- 75%
Reading Between the Pixels: Investigating the Barriers to Visualization Literacy
CHI '24· Visualization Perception & Cognition
- 75%
Did You Misclick? Reversing 5-Point Satisfaction Scales Causes Unintended Responses
CHI '24· Visualization Perception & Cognition
- 75%
What is User Engagement?: A Systematic Review of 241 Research Articles in Human-Computer Interaction and Beyond
CHI '25· User Research Methods (Interviews, Surveys, Observation)
- 60%
TopoText: Context-Preserving Text Data Exploration Across Multiple Spatial Scales
CHI '18· Interactive Data Visualization +1
- 60%
Semi-Automated Coding for Qualitative Research: A User-Centered Inquiry and Initial Prototypes
CHI '18· User Research Methods (Interviews, Surveys, Observation) +1
- 60%
How Do We Measure That?! Quick Scale Development
CHI '18· User Research Methods (Interviews, Surveys, Observation) +1
- 60%
A Bermuda Triangle? - A Review of Method Application and Triangulation in User Experience Evaluation
CHI '18· User Research Methods (Interviews, Surveys, Observation) +1
Based on Jaccard similarity of research subtopics & professions (≥60%)