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. 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.

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 r² scores. We also recommend investigating the use of stochastic sampling for D and W.

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.

In usual Fitts' law experiments the outcome of a pointing act can be either measured as an error, i.e., a distance from endpoint to target center, or categorized in an all-or-none way as a hit versus a miss. Information theory offers a useful distinction between transmission errors (the received symbol is wrong) and erasures (the received symbol is empty). Although Fitts' law research has been very much inspired by the information theoretic rationale, the error/erasure distinction has escaped attention so far: Target misses have always been treated as normally-distributed errors, through the effective index of difficulty IDe. The paper introduces a new index of difficulty based on the simple observation that a target miss conveys zero bit of information, i.e., it is an erasure. Not only is the new index more consistent with the fundamentals of information theory, it is much simpler to derive than the ISO-recommended IDe.

Physical Loci, a technique based on an ancient memory technique, allows users to quickly learn a large command set by leveraging spatial, object and verbal/semantic memory to create a cognitive link between individual commands and nearby physical objects in a room (called loci). We first report on an experiment that showed that for learning 25 items Physical Loci outperformed a mid-air Marking Menu baseline. A long-term retention experiment with 48 items then showed that recall was nearly perfect one week later and, surprisingly, independent of whether the command/locus mapping was one's own choice or somebody else's. A final study suggested that recall performance is robust to alterations of the learned mapping, whether systematic or random.

We present WatchIt, a prototype device that extends interaction beyond the watch surface to the wristband, and two interaction techniques for command selection and execution. Because the small screen of wristwatch computers suffers from visual occlusion and the fat finger problem, we investigated the use of the wristband as an available interaction resource. Not only does WatchIt use a cheap, energy efficient and invisible technology, but it involves simple, basic gestures that allow good performance after little training, as suggested by the results of a pilot study. We propose a novel gesture technique and an adaptation of an existing menu technique suitable for wristband interaction. In a user study, we investigated their usage in eyes-free contexts, finding that they perform well. Finally, we present techniques where the bracelet is used in addition to the screen to provide precise continuous control over list scrolling. We also report on a preliminary survey of traditional and digital jewelry that points to the high frequency of watches and bracelets in both genders and gives a sense of the tasks people feel like performing on such devices.

We propose Augmented Letters, a new technique aimed at augmenting gesture-based techniques such as Marking Menus [9] by giving them natural, mnemonic associations. Augmented Letters gestures consist of the initial of command names, sketched by hand in the Unistroke style, and affixed with a straight tail. We designed a tentative touch device interaction technique that supports fast interactions with large sets of commands, is easily discoverable, improves user's recall at no speed cost, and supports fluid transition from novice to expert mode. An experiment suggests that Augmented Letters outperform Marking Menu in terms of user recall.

We present Bezel-Tap Gestures, a novel family of interaction techniques for immediate interaction on handheld tablets regardless of whether the device is alive or in sleep mode. The technique rests on the close succession of two input events: first a bezel tap, whose detection by accelerometers will awake an idle tablet almost instantly, then a screen contact. Field studies confirmed that the probability of this input sequence occurring by chance is very low, excluding the accidental activation concern. One experiment examined the optimal size of the vocabulary of commands for all four regions of the bezel (top, bottom, left, right). Another experiment evaluated two variants of the technique which both allow two-level selection in a hierarchy of commands, the initial bezel tap being followed by either two screen taps or a screen slide. The data suggests that Bezel-Tap Gestures may serve to design large vocabularies of micro-interactions with a sleeping tablet.

The widely-held view that Fitts' law expresses a speed/accuracy trade-off is presumably correct, but it is vague. We outline a simple resource-allocation theory of Fitts' law in which movement time and error trade for each other. The theory accounts quite accurately for the data of Fitts' (1954) seminal study, as well as some fresh data of our own. In both data sets we found the time/error trade-off to obey a power law. Our data, which we could analyze more thoroughly than Fitts', are consistent with a square-root function with a single adjustable constant. We suggest that the resource-allocation framework should help combine information and energy considerations to allow a more complete account of Fitts' law.

This paper introduces JerkTilts, quick back-and-forth gestures that combine device pitch and roll. JerkTilts may serve as gestural self-delimited shortcuts for activating commands. Because they only depend on device acceleration and rely on a parallel and independent input channel, these gestures do not interfere with finger activity on the touch screen. Our experimental data suggest that recognition rates in an eight-choice selection task are as high with JerkTilts as with thumb slides on the touch screen. We also report data confirming that JerkTilts can be combined successfully with simple touch-screen operation. Data from a field study suggest that inadvertent JerkTilts are unlikely to occur in real-life contexts. We describe three illustrative implementations of JerkTilts, which show how the technique helps to simplify and shorten the sequence of actions to reach frequently used commands.

Interaction with TV sets, set-top boxes or media centers strongly differs from interaction with personal computers: not only does a typical remote control suffer strong form factor limitations but the user may well be slouching in a sofa. In the face of more and more data, features, and services made available on interactive televisions, we propose to exploit the new capabilities provided by gesture-aware remote controls. We report the data of three user studies that suggest some guidelines for the design of a gestural vocabulary and we propose five novel interaction techniques. Study 1 reports that users spontaneously perform pitch and yaw gestures as the first modality when interacting with a remote control. Study 2 indicates that users can accurately select up to 5 items with eyes-free roll gestures. Capitalizing on our findings, we designed five interaction techniques that use either device motion, or button-based interaction, or both. They all favor the transition from novice to expert usage for selecting favorites. Study 3 experimentally compares these techniques. It reveals that motion of the device in 3D space, associated with finger presses at the surface of the device, is achievable, fast and accurate. Finally, we discuss the integration of these techniques into a coherent multimedia menu system.

We propose Radial-Stroke and Finger-Count Shortcuts, two techniques aimed at augmenting the menubar on multi-touch surfaces. We designed these multi-finger two-handed interaction techniques in an attempt to overcome the limitations of direct pointing on interactive surfaces, while maintaining compatibility with traditional interaction techniques. While Radial-Stroke Shortcuts exploit the well-known advantages of Radial Strokes, Finger-Count Shortcuts exploit multi-touch by simply counting the number of fingers of each hand in contact with the surface. We report the results of an experimental evaluation of our technique, focusing on expert-mode performance. Finger-Count Shortcuts outperformed Radial-Stroke Shortcuts in terms of both easiness of learning and performance speed.

International audience

We present a novel method called motion-pointing for selecting a set of visual items such as push-buttons without actually pointing to them. Instead, each potential target displays a rhythmically animated point we call the driver. To select a specific item, the user only has to imitate the motion of its driver using the input device. Once the motion has been recognized by the system, the user can confirm the selection to trigger the action. We consider cyclic motions on an elliptic trajectory with a specific period, and study the most effective methods for real-time matching such a trajectory, as well as the range of parameters a human can reliably reproduce. We then show how to implement motion-pointing in real applications using an interaction technique we call move-and-stroke. Finally, we measure the throughput and error rate of move-and-stroke in a controlled experiment. We show that the selection time is linearly proportional to the number of input bits conveyed up to 6 bits, confirming that motion-pointing is a practical input method.

An intriguing anomaly of the usual way of designing Fitts' law experiments in experimental psychology and HCI is exposed: experiments are traditionally designed so as to carefully balance two ancillary factors, target distance D and target width W, but not task difficulty, the factor unanimously thought to be crucial. Troubling factor confounds and hence quantitative estimation errors result from this inconsistency. The problem, it is suggested, may be fixed if the equivocalness of the fractional expression D/W that appears on the right-hand side of Fitts' law equations is acknowledged. This two-degree-of-freedom expression can be taken to specify either D and W or the form F and the scale S of the movement task. The paper ends up with practical recommendations for the design of consistent Fitts' law experiments. In most cases eliminating one factor will allow a safer estimation of Fitts' law parameters, while simplifying the experimental work.

The input vocabulary for touch-screen interaction on handhelds is dramatically limited, especially when the thumb must be used. To enrich that vocabulary we propose to discriminate, among thumb gestures, those we call MicroRolls, characterized by zero tangential velocity of the skin relative to the screen surface. Combining four categories of thumb gestures, Drags, Swipes, Rubbings and MicroRolls, with other classification dimensions, we show that at least 16 elemental gestures can be automatically recognized. We also report the results of two experiments showing that the roll vs. slide distinction facilitates thumb input in a realistic copy and paste task, relative to existing interaction techniques.

This article pursues a two-fold goal. First we introduce degree of goal directedness (DGD), a novel quantitative dimension for the taxonomy of navigation tasks in general. As an attempt to operationalize the DGD concept in the context of electronic documents navigation, we introduce the serial target-acquisition (STA) experimental paradigm. We suggest that DGD and the STA paradigm may usefully enrich the conceptual toolkit of HCI research for the evaluation of navigation techniques. Our second goal is to illustrate the utility of the DGD concept by showing with a concrete example, Perspective Drag, the refinement it allows in evaluating navigation techniques. We report data obtained from two experiments with the STA paradigm that cast light on what Perspective Drag is specifically good for: it is particularly suitable in realistic task contexts where navigation is less than 100% directed by its terminal goal, that is, where the user wants not only to reach a particular item but also to pick up information from the document during document traversal.

Touchstone is an open-source experiment design platform designed to help establish a solid research foundation for HCI in the area of novel interaction techniques. Touchstone includes a design platform for exploring alternative designs of controlled laboratory experiments, a run platform for running subjects and a limited analysis platform for advice and access to on-line statistics packages. Designed for HCI researchers and their students, Touchstone facilitates the process of creating new experiments, as well as replicating and extending experiments in the research literature. We tested Touchstone by designing two controlled experiments. One illustrates how to create a new experiment from scratch. The other replicates and extends a previous study of multiscale pointing interaction techniques: OrthoZoom was fastest, followed by bi-manual Pan & Zoom; SDAZ and traditional Pan & Zoom were consistently slower.

The current GUI is like a flight simulator whose camera points fixedly at right angle to the document, thus preventing users from looking ahead while navigating. We argue that perspective viewing of usual planar documents can help navigation. We analyze the scale implosion problem that arises with tilted cameras and we report the data of a formal experiment on document navigation with perspective views.

Using a new taxonomy of pointing tasks which includes view pointing beside traditional cursor pointing, we introduce the concept of multi-scale pointing. Analyzing the impact of view size, we demonstrate theoretically and experimentally that (1) the time needed to reach a remotely located target in a multi-scale interface still obeys Fitts' law and (2) the bandwidth of the interaction (i.e., the inverse of Fitts' law slope) is proportional to view size, a relationship bounded by an early ceiling effect. We discuss these results with special reference to navigation in miniaturized and enlarged interfaces.

We introduce semantic pointing, a novel interaction technique that improves target acquisition in graphical user interfaces (GUIs). Semantic pointing uses two independent sizes for each potential target presented to the user: one size in motor space adapted to its importance for the manipulation, and one size in visual space adapted to the amount of information it conveys. This decoupling between visual and motor size is achieved by changing the control-to-display ratio according to cursor distance to nearby targets. We present a controlled experiment supporting our hypothesis that the performance of semantic pointing is given by Fitts' index of difficulty in motor rather than visual space. We apply semantic pointing to the redesign of traditional GUI widgets by taking advantage of the independent manipulation of motor and visual widget sizes.

McGuffin and Balakrishnan (M&B) have recently reported evidence that target expansion during a reaching movement reduces pointing time even if the expansion occurs as late as in the last 10% of the distance to be covered by the cursor. While M&B massed their static and expanding targets in separate blocks of trials, thus making expansion predictable for participants, we replicated their experiment with one new condition in which the target could unpredictably expand, shrink, or stay unchanged. Our results show that target expansion occurring as late as in M&B's experiment enhances pointing performance in the absence of expectation. We discuss these findings in terms of the basic human processes that underlie target-acquisition movements, and we address the implications for user interface design by introducing a revised design for the Mac OS X Dock.

Fitts pointing model has proven extremely useful for understanding basic selection in WIMP user interfaces. Yet todays interfaces involve more complex navigation within electronic environments. As navigation amounts to a form of multi-scale pointing, Fitts model can be applied to these more complex tasks. We report the results of a preliminary pointing experiment that shows that users can handle higher levels of task difficulty with two-scale rather than traditional one-scale pointing control. Also, in tasks with very high-precision hand movements, performance is higher with a stylus than with a mouse.