The Perils of Confounding Factors: How Fitts' Law Experiments can Lead to False Conclusions

Julien Gori 1, 2 Olivier Rioul 1, 2 Yves Guiard 3, 1 Michel Beaudouin-Lafon 4
3 HCC - LRI - Human-Centered Computing (LRI)
LRI - Laboratoire de Recherche en Informatique
4 EX-SITU - Extreme Interaction
LRI - Laboratoire de Recherche en Informatique, Inria Saclay - Ile de France
Abstract : The design of Fitts' historical reciprocal tapping experiment gravely confounds index of difficulty ID with target distance D: Summary statistics for the candidate Fitts model and a competing model may appear identical, and the validity of Fitts' model for some tasks can be legitimately questioned. We show that the contamination of ID by either target distance D or width W is due to the common practices of pooling and averaging data belonging to different distance-width (D,W) pairs for the same ID, and taking a geometric progression for values of D and W. We analyze a case study of the validation of Fitts' law in eye-gaze movements, where an unfortunate experimental design has misled researchers into believing that eye-gaze movements are not ballistic. We then provide simple guidelines to prevent confounds: Practitioners should carefully design the experimental conditions of (D,W), fully distinguish data acquired for different conditions, and put less emphasis on r 2 scores. We also recommend investigating the use of stochastic sampling for D and W.
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Julien Gori, Olivier Rioul, Yves Guiard, Michel Beaudouin-Lafon. The Perils of Confounding Factors: How Fitts' Law Experiments can Lead to False Conclusions. CHI' 18, Apr 2018, Montréal, Canada. ⟨10.1145/3173574.3173770⟩. ⟨hal-01690122⟩

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