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Unformatted text preview: Models of Choice Reaction Time & Motor Skills Brian Bailey Announcements • Homework1 assigned • Reserve last 10 min to form teams • Group information forms due next week Models in HCI • Simplified abstractions of reality • Explain or predict observed behavior – accepted model is best explanation to date – may be modified or rejected – difficult or impossible to fully verify • Inputs, outputs, and assumptions Hicks Law  Choice Reaction Time • Models reaction time under uncertainty • Decision time T increases with uncertainty about the judgment or decision to be made – T = a + k*H, where H is the entropy of the decision; a and k are constants. – H = log 2 (N + 1), if probabilities are equal – H= ∑ = + 1 2 ) 1 / 1 ( log i i i p p Menu Design • Use a broad shallow or a narrow deep structure? Derive from Hicks Law • T ~= a + k*log 2 N – N = total items to choose from – a and k are coefficients of the regression line – b = menu branching factor (items per menu) • If we assume that a=0, k=1, then • T ~= (menus to choose from) * (time per menu) • T ~= (log b N) * (log 2 b) • T ~= log 2 N Is This True? • Suppose 64 menu items (N = 64) • Case b = 4: – T = (log 4 64)*(log 2 4) = 6 • Case b = 8: – T = (log 8 64)*(log 2 8) = 6 • Make either fewer choices in more submenus or more choices in fewer submenus But… • constants not typically a=0 and k=1, thus • T ~= (log b N) * (a + k*log 2 b) • T ~= a*log b N + k*log b N*log 2 b • T ~= a*log b N + k*log 2 N • T ~= k*log 2 N + a*log b N Use Broad Shallow...
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 Fall '08
 Karahalios,K
 Motor control, Menu bar, Steering law

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