Laws of UX
Information theory
Hick's law
Zipfian distribution
Quantitative analysis
Controlled experiment
Lab study
Literature survey
2017-2020
Hick's law is a key quantitative law in Psychology that relates reaction time to the logarithm of the number of stimulus-response alternatives in a task. Its application to HCI is controversial: Some believe that the law does not apply to HCI tasks, others regard it as the cornerstone of interface design. It appears in design books and numerous on-line articles discussing how understanding Hick's law can improve interface design. It has been claimed to apply to a large number of contexts, including menu design, device settings and road signs. Essentially, when faced with a set of choices, designers are guided by this "Hick-based" design principle with the concept less is better, i.e. it is better to split the set of choices into smaller categories, instead of overwhelming users with all choices at once.
The law, however, is often misunderstood. We review the choice-reaction time literature and argue that: (1) Hick's law speaks against, not for, the popular principle that 'less is better'; (2) logarithmic growth of observed temporal data is not necessarily interpretable in terms of Hick's law; (3) the stimulus-response paradigm is rarely relevant to HCI tasks, where choice-reaction time can often be assumed to be constant; and (4) for user interface design, a detailed examination of the effects on choice-reaction time of psychological processes such as visual search and decision making is more fruitful than a mere reference to Hick's law.
During my Ph.D. thesis, I have also used Information-theoretic principles to analyze human performance in command selection tasks.
Wanyu Liu, Julien Gori, Olivier Rioul, Michel Beaudouin-Lafon, and Yves Guiard. 2020. How Relevant is Hick's Law for HCI? In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI '20). Association for Computing Machinery, New York, NY, USA, 1–11. DOI:https://doi.org/10.1145/3313831.3376878
Wanyu Liu, Gilles Bailly, and Andrew Howes. 2017. Effects of Frequency Distribution on Linear Menu Performance. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI '17). Association for Computing Machinery, New York, NY, USA, 1307–1312. DOI:https://doi.org/10.1145/3025453.3025707
Wanyu Liu, Olivier Rioul, Michel Beaudouin-Lafon, and Yves Guiard. "Information-Theoretic Analysis of Human Performance for Command Selection." In IFIP Conference on Human-Computer Interaction, pp. 515-524. Springer, Cham, 2017.