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International audience; The rationale for Fitts’ law is that pointing tasks have the information-theoretic analogy of sending a signal over a noisy channel, thereby matching Shannon’s capacity formula. Yet, the currently received analysis is incomplete and unsatisfactory: There is no explicit communication model for pointing; there is a confusion between central concepts of capacity (a mathematical limit), throughput (an average performance measure), and bandwidth (a physical quantity); and there is also a confusion between source and channel coding so that Shannon’s Theorem 17 can be misinterpreted. We develop an information-theoretic model for pointing tasks where the index of difficulty (ID) is the expression of both a source entropy and a zero-error channel capacity. Then, we extend the model to include misses at rate ε and prove that ID should be adjusted to (1 − ε)ID. Finally, we reflect on Shannon’s channel coding theorem and argue that only minimum movement times, not performance averages, should be considered.

This article was submitted to the ACM CHI conference in September 2017, and rejected in December 2017. It is currently under revision.; Input techniques serving, quite literally, to allow users to send information to the computer, the information theoretic approach seems tailor-made for their quantitative evaluation. Shannon's framework makes it straightforward to measure the performance of any technique as an effective information transmission rate, in bits/s. Apart from pointing, however, evaluators of input techniques have generally ignored Shannon, contenting themselves with less rigorous methods of speed and accuracy measurements borrowed from psychology. We plead for a serious consideration in HCI of Shannon's information theory as a tool for the evaluation of all sorts of input techniques. We start with a primer on Shannon's basic quantities and the theoretical entities of his communication model. We then discuss how the concepts should be applied to the input techniques evaluation problem. Finally we outline two concrete methodologies, one focused on the discrete timing and the other on the continuous time course of information gain by the computer.

This is the nearly final version of an article presented at HCI 2012 People and Computers XXVI, an annual conference of the British Computer Society held on September 12-14, 2012 in Birmingham (UK). The article appears on pp 119-126 of the conference proceedings. The paper having obtained the conference's Best full-paper award, it will be republished as such in the December 2012 issue of INTERFACES, the award winning magazine of the British Computer Society http://www.bcs.org/content/ConWebDoc/3; International audience; Fitts' law states that movement time varies linearly with the index of difficulty or, equivalently, that throughput (TP) is conserved across variations of the speed/accuracy strategy. Replicating a recent study by MacKenzie and Isokoski (2008), we tested the throughput invariance hypothesis with some fresh data and found the TP to be systematically affected by the strategy. This result, we suggest, pleads against the currently popular definition of the TP inherited from Fitts (1954), namely TP = ID/MT, which we recall is incompatible with the Shannon equation. We also show that the statistical elaboration of the TP suffers from a problematic amount of uncontrolled variability due to the multiple inadvertent impact of Jensen's inequality.