Human Performance Modeling

From CS2610 Fall 2014
Jump to: navigation, search






Reading Critiques

phuongpham 21:42:08 9/12/2014

"Beating" Fitts' law: virtual enhancements for pointing facilitation: this paper surveys research projects which attempt to help users gaining better performance better than Fitts' law limits. Eventhough 3 main approaches still cannot give the perfect solution which outperforms the Fitts' law limits, the paper still points out important findings and hopes for improvements. For example, when increasing W by area cursors, we can override the approach's weakness by domain adapting. This means each application can employ different cursor types depend on its characteristic. However, this domain adaptation raises another challenge for designers in order to integrate different cursor into a single system (OS) without raising extra confusion. The target prediction would also be improved with intelligent OS which can leverage user history activities. Remember that the paper has been published in 2004 and machine learning techniques have been improved since then. Another interesting point I get from the paper is the Fitts' law. It has become a status quo in the community and give in-depth analysis for researchers. I have been appriciated the MacOSX "dock" function because I "feel" it is easy to user. However, after reading the paper, I have been able to conclude that the "dock" has a good solution because it increase the target's width, which is an important factor in the Fitts' model. Last but not least, the authors raised a warning about controlled experiment and how to evaluate qualititative measure of an approach. In NLP area, researchers can apply satisfied post questionaire. I wonder if in HCI area there are similar methods or not. ***Beyond Fitts' Law: Models for Trajectory-Based HCI Tasks: this paper proposed a variant of Fitts' law applied for trajectory tasks. This can be considered as a domain adaptation project. The authors have done several tasks to estimate the model. Even the experiment tasks are varied, I wonder if the tasks are really practical. The authors argued that users will steer around the screen. However, general computer usage may not need that, unless the OS support file browsing by steering. Therefore, even the model has been built for stylus in such cases, the application has not been convinced me much. However, this paper has shown that new task would need new models in order to avoid obvious limitations of design

Yanbing Xue 20:31:02 9/13/2014

The first paper is about different techniques for improving pointing performance in graphical user interfaces. The location of targets such as icons, menus, drop down lists, and button can substantially impact user productivity. Giving another view of Fitts' law in the virtual world, it's quite meaningful to HCI in computer science area, since most of our application built are on virtual platform. It focuses on two points: one is to decrease D and the other is to increase W. There exists another method, improving both D and W at the same time. However, changes in D and W could be carried out either within the motor space, or within the visual space. These techniques are particularly promising, none of them has yet to be demonstrated to work uniformly well. I see that author chose top-down approach to presents his survey. Firstly, the background of problem was provided as an introduction to theoretical fundamental of new techniques for facilitating pointing. Based on Fitts’ law, different techniques had different approaches but they all develop from an original problem, just trying to improve one of its parameters. Then techniques were presented sequentially and grouping into different categories. Main ideas of techniques were discussed along with strong and weak points, how the latter developed from the former. Reader can have not only general view on background of pointing task, difficulty of the problem but also good review on each technique and remaining of the problem that not be solved yet. The authors admit multiple times that the pointing device is significant in determining how much of an effect that pointing enhancements may have. Given that it seems likey that interfaces may soon incorporate things like audio and video recognition hardware/software, I feel that research that is specific to typical physical pointing devices will soon become less relevant than it currently is. This isn't to say that pointing research in general will not be important, but just that conclusions, both positive and negative, gleaned from previous work may need to be evaluated once more.

Yanbing Xue 21:29:05 9/13/2014

In the second paper, the authors models users' performance in trajectory-based tasks which could not be modeled by typical Fitts' law. In specific, they took several experiments in order to derive and validate quantitative relationships between completion time and movement constraints. Their experiments started with a simple case of going from one line to another, in a strait path. Fitt's law projected this time well. However, when they added the concept of navigating a tunnel, they found a more general law . They added the idea of making the path constrained by “walls” that users could not touch, and by adding curvature to the path. The error rate for all of the experiments performed by Accot and Zhai were higher than those typically found in Fitts’ law studies. However, the tasks that are being performed are arguably more difficult. In all cases, they found that these tasks could be modeled by simple mathematical laws. Interestingly, in the base case of a single tunnel with one goal at each end, Fitts' law itself still provided an appropriate model for the movement. It also turns out that more complex motions such as those involving multiple or even infinite goals can be modeled by Fitts' law, although the law does need to have appropriate mathematics applied to it to allow for these adjustments. I think the authors should add another section about the evaluation of the model. Otherwise, this model seems a bit unpersuasive.

Vivek Punjabi 16:32:20 9/14/2014

Beating Fitts' Law: Virtual enhancements for pointing facilitation The author provides a detailed survey of different techniques of pointing facilitation developed till date. He has provided a good amount of background where he explains the standards of Pointing facilitation techniques i.e. Fitts' Law which helps us to relate every other research on common terms. The survey is pretty much fascinating as it provides the evolution of the most common user interface object, the mouse. The examples along with the illustrations are very helpful in understanding the concepts. Among the given techniques, the Drag-and-pop looked pretty amazing and new to me as we have never it in action these days, but looks like a promising method. Also, the technique of expanding targets seems very user-friendly these days and I would vote on that too. Finally, it gives a strong motivation to develop more ideas and research in this topic along with a need to create more standardized approach to compare and relate these techniques. However, the topic of control-display gain seemed a bit confusing. I think that topic required a bit more of a background to get to the detailed techniques. Beyond Fitts' Law: Models for Trajectory-Bases HCI Tasks The paper describes the the models for trajectory-based HCI tasks where Fitts' law becomes inapplicable. The paper initially describes the Fitts' Law and its importance but says that it isn't applicable to the modern day HCI tasks. So it tries to develop a better equation similar to Fitts' Law with the help of steering tasks. It considers various models each with different constraints and parameters like straight, narrowing and spiral tunnels. An experiment is performed on each of the models and the results are shown in the form of equations and graphs. The author has considered ample amount of models and ideas, and presented the results in much comparative ways. It has compared the results with Fitts' Law and provided analysis of the same. Their motivation and future plans is well defined which makes the paper a much structured approach towards the research. At some places, the equations were too direct without much calculations and evidences which felt confusing. According to me, the content and derivations of the equations lacked at some places. Though the intentions are clearly evident but some strong and detailed calculations would help most of the audience to understand the derivations.

zhong zhuang 4:16:27 9/15/2014

This paper discusses varies ways to improve pointing and selecting targets in graphic user interface, all of its suggestions are based on Fitt’s law, basically, it provides three ways to archive the goal, reducing D(distance between pointer and target), enlarging W(the width of target) and mixture of both. It examines three suggestions of reducing D, first is designing widgets that minimize D, for example the pie menu has much more smaller distance than the list menu, second is to temporarily bring targets closer to pointer, but this one has a major drawback when many targets densely distributed, the third one is to removing empty pixels, it suggests an object pointer technique where cursors will jump from one target to another by jumping empty spaces between them, this method is not optimized when empty spaces are also potential targets, like word editing. It then examines two suggestions of enlarging W, first is to use an area cursor, which is larger than the traditional cursor so the target can be selected when any part of the cursor is in the target rather than wait for the center of the cursor is in the target. This approach is not optimized when over clusters of targets like toolbar. The second approach is expanding the target size when cursor is closed to the target, this technique is widely used in MacOX system. Finally it discusses the possibility of both reducing D and enlarging W. The most important concept in this approach is C-D gain or Control-Display gain, by dynamically change the C-D gain according to the knowledge of the target can have significant performance improvement.

Bhavin Modi 11:18:37 9/15/2014

Reading Critique on “Beating” Fitts’ Law: Virtual Enhancements for Pointing Facilitation A discussion on the all the techniques and approaches to interface design aimed at beating Fitts’ law, in simple terms decrease the interaction time taken by users to select a particular object. There are many avenues of discussions in this paper based on the researches of many individuals over the past two decades. It starts with the basic explanation of the Fitts’ law, the effect of distance and width of the target on the movement time, this d and w has been referenced in terms of motor and visual spaces. The human selection motion remains the same throughout, a single initial impulse slinging the limb towards the target and a closed loop feedback, i.e., short impulse corrective movement. The various techniques in terms of decreasing d are using hotkeys, scrolling wheels, use of proxy images and the most promising was by Guiard et al., Object Pointing. In terms of decreasing width we have area cursors and expanding targets, area cursors were actually effective. In terms of both d and w, the C-D gain manipulation was the most promising. All in all, they seem to have the same problem, when faced with densely populated displays, in case of C-D gain it is the presence of intervening objects, which again is due to densely populated displays. These techniques have been compared to Fitts’ law, in order to find improvements, but there is no direct comparison between these techniques which makes it difficult to say which is better. Reading this paper really helps to realize the work done on this topic, it is much like a summary of everyone’s research. It is a useful paper, a must read, if you plan on research in this field. Some ideas that I could come up with after reading were a combination of the various techniques, also suggested by the author. The first one is auto-correction, meaning you do not have to be over the object, being in the vicinity should redirect you to your target. The problem here is also dense population and some much like the c-d gain problems. So let us think of a screen with a docking system like mac, on the four sides of the screen, not only the bottom. So there will be no icons on the screen, keeping your workspace clean. I propose combining proxy images, expanding tiles, C-D gain and object jumping to create this. The working is as follows, the dock will be comprised of slots, accessible via hotkeys, reducing the use of pointers. On using pointers we will use object jumping to reach the icons in the direction of motion, not the icon specifically but a point just at the beginning of the dock. The problem with expanding tiles is that selection becomes difficult when moving to the next object. So on reaching the point specified by the dock, we use proxy images to display the objects in that vicinity, directed circularly around the pointer toward the centre of the screen. The object displayed will be transparent so as to not interfere with the display beneath. The question arises of limited slots in docks, but this is helpful because having too many objects increases response time, as the user searches for the target in a densely populated display. Having a scrolling dock is another solution, scrolling is faster than movement, as it involves just the fingers, no movement of the hands. --------------------------------------------------------------------------------------------------------- Reading Critique on Beyond Fitts’ Law: Models for Trajectory-Based HCI Tasks The paper explores the robust regularities in movement tasks, specifically trajectory based tasks or goal-passing tasks. The derivation of a global and local law, to identify the relation between time taken and the velocity of movement with the width of the path. Highlights of the paper, where the experiments conducted in order to model trajectory-based tasks, for which Fitts’ law is not sufficient, from pointing to steering. The experiments conducted were the goal passing, goal passing with increased constraints, narrowing tunnel, and spiral tunnel. Each was conduction to view the change in movement time w.r.t amplitude and width of a trajectory task. The conclusions made were that as the width decreases the error rate increase also time increases, all the experiments showed them to linearly dependent on the index of difficulty. A simple linear relationship between movement time and tunnel width, all experiments showed correlations greater than 0.96 for steering tasks. We start thinking of drawing tasks, moving in 3D worlds as they are becoming more coming in today’s world, and as a result understanding relations beyond Fitts’ law is important. The findings provided by the authors are only accurate up to an upper bound limit on the width for which the laws correctly model the relation. The design implications of these findings are shown in menu selection, and how we can measure time in that case which depends on the vertical or horizontal motions, the number of items and the width of the menu. The human motion does not depend only the width, is something I would like to contradict. One should take into account, the pointer width, speed, the C-D gain and its effects on trajectory tasks while selecting as they take focus more on pointing. The speed is responsible for most of the errors, rather than width while the length indicates only the time taken. Concluding, there is scope for a lot more experimentation in the field as mentioned by the authors too. The paper is clearly signifies the importance of moving from pointing to steering tasks, and derives laws to show that the movement time and velocity dependence on path width in such conditions.

Nick Katsipoulakis 20:34:38 9/15/2014

“Beating” Fitts’ law: virtual enhancements for pointing facilitation: This text presents a survey on research for improving Fitts’ law. Three dominating approaches are presented which follow different paths by: (a) decrease the distance to the target, (b) increase the size of the target, and (c) do both at the same time. All of the approaches revolve around three models used to define motor control models (iterative corrections, impulse variability, and optimized initial impulse). The main point made from those three is that a quick and far movement can’t be accurate at the same time. Also, each approach to improve Fitts’ law is better synthesized by the motor space, the visual space and the control-display function. Many approaches have been proposed for lowering distance in Fitts’ law. Initially, linear and pie menus succeed in considerably lowering distance, but they require drastic changes in the User Interface. Temporary movement of targets closer to the cursor has also been proposed as a potential solution. Unfortunately, it has been studied that the latter approach works best for sparse virtual desktops. Object pointing is another approach in which the cursor can “jump” from one selectable object to another. However, this technique does not solve the problem because “free” spaces serve a purpose, selectable objects are tiled, and visual jumps may become annoying in real-life usage. Turning to approaches aiming to increase the width, a first attempt was the proposal of area cursors (a cursor covered more than one pixel). This approach had two major problems: obscurity of underlying data and difficulty in selecting targets that were grouped together. Another approach is the one that expands targets. Even though experimentation has shown significant benefits on that work, the problem of occluded objects close to the target remains. The third type of approach was mainly driven by the C-D gain, which is the ratio of the amount of movement of an input device and the controlled objects. No conclusions have been reached on whether the gain should be increased or decreased. In practice, dynamic C-D gain achieves better results. However, the need for semantically aware varying C-D gain has been proved to be essential. -----------------END OF FIRST CRITIQUE------------------------------------------------ Beyond Fitts’ law: Models for Trajectory-Based HCI Tasks : In this paper, the authors present a new law for modelling human performance, through a series of experiments. Initially, the paper starts by explaining the major contributions of Fitts’ law in HCI, and the way it motivated them for their own experiments. They concentrate on the "steering” ability of a user by devising a task involving moving a cursor from one point to another. After coming up with a formula for measuring time and accuracy, they expand their experiment on having different checkpoints. Next, they present their users with a narrowing tunnel and come up with a linear relationship that relates the difficulty and the successful trials. Finally, spiral tunnels are presented to users in order to come up with a global law for the steering ability (or difficulty). The global law is generalized as a design metric for measuring complexity of tasks that users may have to complete in a GUI design (i.e. interactions with menus). Overall, this paper presents an extension to Fitts’ law which aims to produce a general model for measuring the difficulty of tasks in UIs.

Qihang Chen 21:28:21 9/15/2014

The paper Beating Fitts' law surveys the recent researches in developing, analyzing and evaluating new techniques for artificially enhancing pointing performances in graphical user interfaces. The authors first introduce the Fitt’s law, discuss the difference between the real and virtual world and classifies the pointing facilitation techniques into three categories: decrease D, increase W and both decrease D and increase W. Before the introduction of each category, the underlying control models and three likely explanations are presented. Based on the explanation, the three major factors are summarized including motor or control space, visual or display space and the control-display (C-D) transfer function. Next, the authors spread the categorized techniques: first, reducing D for which techniques include (a) designing widgets, (b) temporarily bringing potential targets to the cursor and (c) removing empty space between the cursor and targets. Among these, (a) is the most simple one whose typical example is menus layout; (b) is able to quicken the operation speed, but it is difficult to design the interaction and predict the users' intention; (c)'s representative is object pointing whose performance is ruined under the case selectable objects are tiled together. Then, the techniques increasing W are talked about which covers area cursors and expanding targets. The authors point out that further enhancements are needed to make the cursor work in a facile manner in real interfaces. And, for expanding targets, extra factors of the pointer should be taken into account. After this, the technique dynamically changing the control-display design, both decreasing D and increasing W, is illustrated. Contentions exist on the relationship between the C-D gain and performance. While target aware C-D gain adaption improves pointing performance for single isolated targets, problems arise when multiple targets are present. In the final, the authors conclude the techniques, related problems and the new directions. With the widely used of smart mobile devices like iPad and iPhone, the pointing techniques gradually becomes the main input and thus it is important to have a summary of the recent techniques and locate the existing problems to evolve new techniques to solve which are exactly the main contribution of this paper. Though I don't think there are serious flaws in this survey, I do believe it is much better to provide some new possible designs beyond the brief words in the last part. For instance, I may try combining two or more existing techniques to tell the readers that it is possible to improve the performance. -------------------------------------------------------------------------------------------- An Error Model for Pointing Based on Fitts' Law: In this paper, the authors develop and evaluate an error prediction model for object pointing tightly based on Fitts' Law. Regression analysis of their model's predicted vs. actual error rates yields a strong (~96%) correlation. Interestingly, they find that target size (W) is much more useful in error prediction than target distance (D - which they refer to as A). The findings of this paper are significant for two main reasons. First, the error model generated is the first accurate model developed based on Fitts' Law paramaters. Given the pervasiveness of Fitts' Law in pointing research, this is somewhat of a surprising result. Second, the results show that the effect of object size on error rate is much more significant than the effect of object distance. This is significant because Fitts' Law maintains that these parameters contribute proportionally to the index of difficulty. One of the strengths of this paper is the empirical, per-user derivation of the a and b constants that affect the predicitive model. Far too often user studies lump large sets of users into categories, the act of which effectively claims that all users are the same. While it may be true that Fitts' Law is an upper bound on user performance, it's unlikely that all users actually will exhibit the same error rate. Per-user experimentation has the effect of tuning the predictive model appropriately. In my opinion, there is one big shortcoming in this work. The results would be much more convincing if the authors would have conducted real-world experiments in addition to the tightly controlled experiments that they ran. As we saw in the first reading for today, many results from tightly controlled studies do not carry over into the real-world.

Eric Gratta 21:54:09 9/15/2014

Beating Fitts’ Law: virtual enhancements for pointing facilitation Ravin Balakrishnan The primary argument for attempting to “beat” Fitts’ law (really, take advantage of our understanding of it) is that pointing and clicking is an extremely common task in the age of graphical user interfaces, thus any small enhancement in the speed of that action could theoretically result in huge gains in user productivity. The authors argue against the common conclusion that since mouse pointing is as good as physical pointing, it must be optimal in its current form. They suggest that since virtual pointing is not under the limitations of the physical world, there may be ways to enhance mouse performance and reduce movement time. The authors introduce a model of the motor control models behind pointing called the “optimized initial impulse” model (Rosenbaum), describing the process of pointing as one initial movement toward a target, followed by smaller corrective movements if the target is missed. The key component of the model is an equation for standard deviation of the endpoint, S = k(D/T), where D is distance and T is duration of the movement or time. A distinction was made between motor distance and virtual distance, which I found interesting. An example of where this distinction is important is in the addition shortcuts on input devices (keyboard macros for buttons, mouse scroll wheels for scroll bars) that eliminate motor distance while virtual distance still exists between the cursor and the target (icons or scroll bars). The methods surveyed that only focused on reducing virtual component distance were disappointing. I felt like all of them were disruptive to the aesthetic of the interface and impractical/unusable. The exploration of width-focused methods were, on the other hand, really interesting, and features I have witnessed in practical user interfaces. After the survey of those W-focused methods, the authors concluded that the use of the dynamic properties of the cursor has a strong potential to enhance design interaction techniques. The overall conclusions made by the authors at the end of the paper were actually quite inconclusive in comparison. One thing I found surprising was how little attention was given to C-D gain adaptation in response to mouse acceleration, given that it’s a common feature in modern pointing input devices (e.g. mouse, trackpad), although this is a decade after the writing of the paper. It was considered a limited approach by the authors, who introduced it but immediately moved on to how it could be enhanced by knowledge of the objects on screen and users’ intended target. The authors focused very much on new techniques and only in the conclusion addressed the issue of user acceptance of the techniques. Many of the techniques involving gravitating the cursor toward nearby objects struck me as something that would feel disorienting and take away a sense of control. In general, I also felt that methods for reducing movement time focused only on reducing distance seemed extremely disruptive to the visual aesthetic of the interface, making them of limited practical use. ------------------------------------------------------------------------- Beyond Fitts’ Law: Models for Trajectory-Based HCI Tasks (1997) Jonny Accot, Shumin Zhai This paper set the lofty goal of trying to expand the body of quantitative methods that can be applied to measuring performance in interfaces on input devices. I was amazed at how much complexity was condensed into this paper in describing what they accomplished and contributed to future HCI research. The premise for the research was that Fitts’ law was one of the only quantitative methods for evaluating interface design, and it only modeled tasks involving moving over a single, straight-line distance to reach a target. What was accomplished was the discovery of a simple model for “steering through tunnels,” the authors’ analogy to trajectory-based navigation in both 2D and 3D, that was derived more or less from the principles of Fitts’ law. As much as I was amazed by the paper, I thought it was off to a weak start. They chose the two parameters amplitude and variability as inputs to a model of movement time when steering an input device between two boundaries. Although the concepts were very well explained, I thought that these were awful names for the parameters. I think the word “variability” describes more accurately what was called amplitude (I relate amplitude to the amplitude of a wave and imagine it as tangential to the direction of motion). If trying to describe the width of the tunnel (presumably without using the word width since it would conflict with Fitts’ law), why not a word like height or diameter to fit the analogy? If the desire was also to avoid the term distance, why not length or, even more accurately, displacement? Does it make sense to describe the diameter of the tunnel as “variability” even when it is not conceptually a rate of variation? Frustrating the reader further, the variable W was used for width (instead of V for variability === width) in their subsequent equations, and so there was inconsistency. The new models that resulted from their experiments were the magic of the paper. The authors discovered that multiple consecutive movement tasks could still be modeled correctly with Fitts’ law. They applied mathematical induction to generalize to the case of infinite discrete movement tasks, which is interpreted as the drawing of a path. They used further experiments to justify models for navigating through straight tunnels that changed in size, curved tunnels, and spiral tunnels. An interesting property of these models is that the index of difficulty is linearly, rather than logarithmically, related to A/W (“amplitude”/width) in all of the cases. That is, the discovered model for trajectory-based movement was MT = a + b(A/W).

Andrew Menzies 23:39:51 9/15/2014

‘‘Beating’’ Fitts’ law: virtual enhancements for pointing facilitation by Ravin Balakrishnan Research has proven consistently that people’s performance using mice follow Fitts’ Law, so the current design of mice is theoretically optimal. However, software tricks such as cursors that cover a large area and interface elements that respond to the cursor’s proximity may allow interface designers to attain better user performance, as these changes decrease the movement distance or increase the target width. One important result from this paper is that some of these techniques can produce performance exceeding that predicted by Fitts’ Law, but only in situations where many clickable items are not close together. It may actually be more efficient, therefore, to intentionally insert distance between clickable items, resulting in increasing the “W” parameter to the Fitts’ Law expression, rather than try to minimize this distance and decrease the “D” parameter. Perhaps interface designers should consider likely sources and destinations for the cursor, and choose distances between elements in order to minimize the expression. One factor the article does not mention much is how these changes affect the probability of clicking an incorrect item as opposed to just missing the correct item and clicking a non-functional part of the visual interface. In nearly all programs, clicking a non-functional part of the interface costs much less time than accidentally clicking another clickable item, an action that usually requires at least another click to correct. The article does mention that the interface with resizing buttons that move other buttons out of the way added more difficulty, but it does not clarify whether it just meant more time to choose the correct item or also more clicks on the wrong item. Beyond Fitts’ Law: Models for Trajectory-Based HCI Tasks by Johnny Accot and Shumin Zhai This work reports the results of experiments where users had to move a cursor to a specific destination while keeping the cursor inside a path of fixed width. According to the results of the experiments, the time taken for these tasks follows a rule similar to Fitts’ Law, but the tasks are harder as the time depends directly on the goal distance divided by path width rather than the logarithm of this quotient. As the paper explains, these results are relevant because they describe some of the difficulty with using multi-tiered menus. Often, these menus are set up so that hovering over a menu item causes a sub-menu to appear. Hovering over a different menu item in the main menu causes a different sub-menu to appear. The task of navigating to a sub-menu item involves two trajectory-based tasks. First, the user must point to the main menu item that creates the correct sub-menu, and move to the sub-menu without moving up or down to a different main menu item. Second, the user must keep the cursor within the sub-menu until reaching the correct sub-menu item. (Moving out of the sub-menu often causes it to disappear.) Another trajectory-based movement task, one that the article does not bring up, is selecting text on a single line in a word processor. The user must drag the cursor from one side of the line to the other without moving it into the line above or below, as that will change the selection. The paper describes experiments several different types of trajectory-based tasks, including ones with straight-line, curved, and spiral paths. In each case, the authors’ hypothesized expression for expected time based on distance and path width correlated closely with the results. The experiments did leave some room for further research. It would be interesting, for example, to see the effects of adding some type of fault tolerance to the path. One type of fault tolerance could be a path whose width is actually slightly larger than what is displayed. Another could be an experiment where the cursor must remain outside the path for at least a specific (short) time period, rather than for any nonzero amount of time, for the trial to be considered an error. If these changes significantly improve movement times, perhaps interface designers could implement these fault tolerance mechanisms in their elements. Tiered menus could be made to, if the cursor has hovered over a particular menu item for a long time, not move to an adjacent menu item immediately if it is moused over, since this mouse-over might be an outside-the-path error as the user tries to move the cursor to the open sub-menu.

Wei Guo 23:48:31 9/15/2014

Reading Critique for Beating Fitts’ law Wei Guo There are still some possibilities to facilitate pointing in virtual world. Fitts’ Law is based on physical world. The virtual world is a little bit different. There are some possibilities to improve Fitt’s Law in virtual world in order to facilitate pointing. In virtual world, there are motor and virtual kinds of distance and width. There are three basic categories to facilitating pointing: reducing distance, increasing width, and both. To reduce distance, changing displaying shape, temporarily bringing potential targets into a small area, or jumping through the space between two potential targets are all good method. These methods also have their own drawbacks. To increase width, expanding targets are often used in interface currently. Besides that, an area cursor is also a possible solution. To simultaneously reduce distance and increase width, it is possible for us to changing the control-display gain. That is, we can make the encouraged target more attractive, while making the other targets less attractive. Our first assignment is: to design a virtual keyboard, to let user slide on keyboard to have words. This paper has a lot of good ideas for us to think when designing our keyboard. Also, when the potential words are generated, how can we help the user to find the target faster?   Reading Critique for Beyond Fitts’ Law Wei Guo This paper is mainly introduce a steering law for trajectory-based task. Fitts’ Law can be only applied to pointing tasks. The authors use 3 experiments to reveal the relationship between completion time and movement constraints in steering trajectory-based task. By using the 3 types of experiments, a global law that predicts to total time to perform a steering task is generated. Velocity is in proportion to the width of tunnel, and is inversely proportional to time constant. In my opinion, the device we choose to input also plays an important role in performing the task. For me, it is impossible to draw a pretty smooth line by using a mouse. I can do so by using an input pen drawing on an input pad. However, some tasks which are pointing dots is much easier by using mouse. Nowadays, touch-screen technology is widely used on a lot of things. To me, a touch screen is better to be implemented on a phone-size-screen or smaller screen, but not a laptop size or we say TV-size-screen. My point is: each interface should have a matched device. We can suggest user by using a kind of device when doing tasks on one interface.

SenhuaChang 23:51:01 9/15/2014

Beating Fitts' law: Virtual enhancements for pointing facilitation The first article introduce the Fitt law firstly (asserts that the movement time MT to acquire a target of width which lies at a distance D is governed by the relationship). This article try to beat the Fitts’ law by artificially reducing the target distance, increasing the target width or a combination. Several different directions along with their advantages and limitation have been represented elaborately. We can conclude three ways to facilitating pointing based on the article; the author gives us a lot of example to support his point. And both example points out that there are some disadvantage, it doesn't work when the targets are close with each other. Based on this article, I’ve known so many of the interesting techniques, and some of the techniques can be improved by nowadays tech. &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& Beyond Fitts' Law: Models for Trajectory-Based HCI Tasks This paper basically do a survey of various tech which tried to reduce the amount of time when user target an object, and the conclusion totally tell us how and what the result is .Three main tech is to reduce the distance to the target and increase the width of the target, and do both of the thing. The experiments are convincible. In experiment 1, it showed that when A is very large, there is a Fitt’s law, and that’s quite intuitive. Most of the experiment are reasonable, with the picture and the formula, readers can easily understand what this paper want to say without fully understanding the equation. To sum up, I have to say this paper is a good paper, with the survey and the tech it provide, and, last but not the least, the good architecture and conclusion.

Nathan Ong (nro5) 0:26:19 9/16/2014

Review of "'Beating' Fitts' Law: Virtual Enhancements for Pointing Facilitation" by Ravin Balakrishnan Surveying the recent literature regarding Fitts' law, Balakrishnan presents multiple papers containing methods of reducing the movement-to-target time of graphical interfaces by decreasing the distance to the target, increasing the target size, or both. The papers surveyed are all experimental papers, with new designs of interfaces tested by user studies, and ends by making recommendations on where to move in terms of research to continue reducing the movement time. Balakrishnan presents a good survey of recent papers. Given a specific topic, namely Fitts' law, Balakrishnan sets out to present the recent research regarding the speedup of movement time. The author is quick to note that speedup can only occur by changing two variables, either decreasing the distance to the target (D), or increasing the target size (W), or both. By categorizing papers in this manner, we see the different approaches that researchers have taken in the attempt to reduce the movement time. It is also easy to compare the different approaches within their respective categories, and attempt to compare across categories. I think Balakrishnan does a good job of taking all of the papers and suggesting new directions for research. While surveys are meant to bring together a set of papers that have something in common, I also think it is important for a survey to use the knowledge that the authors have gained and suggest new directions for research. In Balakrishnan's case, he believes the next form of research needs to be in finding a universal solution that is better than the current state of consumer technology that will be accepted by consumers, which may be found by combining multiple methods from the papers. In addition, he notes the difficulty in selection in a special case where many selectable targets are close together, which is highly relevant in mobile technology with small screens and large fingers. These are good observations and new research can hopefully be done more efficiently.   Review of "Beyond Fitts' Law: Models for Trajectory-Based HCI Tasks" by Johnny Accot and Shumin Zhai Accot and Zhai notes one limitation of Fitts' Law by using the "steering through tunnels" example. Aside from finding the limitation, they suggest their own law to tackle the example and derive it. The way they structured the paper is quite interesting. They presented four experimental setups that they used to enhance Fitts' law, and their hypothesized new formulas seemed to agree. Based on these results, they presented the new "steering law" to account for the added obstacle of "path steering" (i.e. narrow paths for a cursor to move on to get to the desired target), and provide an example of a design that would use the new steering law. Unfortunately, they did not have the space to be able to discuss the other design implications. While they provided the menu example, it would have been nice to see other examples of applications of the steering law. I found it difficult to follow the math they provided. The authors seemed to require a stronger background in mathematics for readers, specifically in their evaluation choices and skipping steps. Understandably, it is difficult to fit all of that in a paper, but I feel those that organize conferences should have the expectation that the math reasoning should not be a barrier to understanding, and the math should be easily replicated in order to quickly verify the soundness of the proofs. It may have been better to split this paper into two papers, one for the experiments, and one for the proof of the steering law.

Wenchen Wang 0:38:37 9/16/2014

Beyond Fitt’s Law: Summary: This paper explored a quantitative trajectory-based movement task, steering law, in spirit of Fitt’s Law. The steering law is obtained by four experiments. Paper Review: Fitt’s law is a model of human movement, predicting that the time required to rapidly move to a target area. The very spirit of Fitt’s Law is quantitative relationships between task constraint and movement speed. This paper proposes steering law, which is a trajectory-based tasks and to measure the steering between boundaries. The steering law they proposed is v(s) = kp(s)W(s), according to four experiments. The steering time is linearly related to the index of difficulty and related to path width. Beating Fitts' law: Virtual enhancements for pointing facilitation Summary: This survey introduces new techniques for artificially facilitating pointing at targets in graphical user interfaces, by reducing the target distance, increasing the target width or both. Paper review: There are several ways to facilitate pointing according to Fitt’s law. First approach is to minimize distance between targets and cursor. For example, users could temporarily drag potential targets to the curser. In real life, I usually put the icons of folders that I often use to the left of desktop. Second approach is to increase width of cursor or the target. One real life example is apple desktop icons locating in the bottom. When user’s curser is on one icon, the icon will be enlarged. The third approach is the hybrid of the above two approaches, which is to both decrease distance and increase width. For example, for facebook iphone application, when a user is browsing the news, the upper part of the interface becomes thinner and the content of the news becomes bigger.

changsheng liu 0:40:04 9/16/2014

<“Beating” Fitts’ law: virtual enhancements for pointing facilitation> surveyed new techniques that could make pointing much more efficient. In virtual environment, we don’t have the physical constraints, so we can use Fitts’ law to facilitate pointing either by decreasing distance or increasing width. Regarding to facilitating pointing by reducing distance, a simple idea is to move target close to the cursor, for example, a pie menu. Another idea is that we can calculate the potential target sets by the current context and directly reduce the distance between cursor and the targets. In term of increasing W, an area cursor is much more preferable than a point cursor. However, it’s not so accurate if the targets are too close . One simple idea is to enlarge the target to increase W. Finally, the paper pointed out we can decrease D and increase W at the same time. As it mentioned in the paper, these new techniques might not work well if multiple targets are too closed. <Beyond> Fitts’s Law: Models for Trajectory-Based HCI Tasks> tried to explore the possible existence of robust regularities in trajectory-based tasks, such as navigating through nested-menus, drawing curves, which are much more complicated than pointing task. Fitts’s law is suitable for modeling pointing, not for spatial interaction, since it involved more constraints, such as Boundaries. The authors took several experimental steps to derive and validate quantitative relationship between completion time and movement constraints in trajectory-based tasks. First, the authors designed a simple goal passing task to establish the new model. Then a tunnel steering task is designed based on the new model. Two more tasks are designed with complexity increased to derive the final model. I think this paper is inspiring and it extends Fitts’ law in a reasonable way. Also, it’s very useful in the design of interaction in Virtual Reality, which tends to have multiple trajectory based tasks.

Mengsi Lou 0:59:52 9/16/2014

Reading Critique 9.16.2014 ----------These two papers state a interesting thing in common that they all expand the traditional Fitts’ law in some extend. Fitts’ law asserts that the movement time of reach a target is determined by the width W of target, and the distance D between current location and the target. ////////////////////////////////////// The first paper, “Beating’’ Fitts’ law: virtual enhancements for pointing facilitation, demonstrates that the virtual world is different from the real world, and may not have to abide by Fitts’ law. So the author introduce the topic from three perspectives: 1. reducing D, 2. increasing W, or 3. both. ----------There are three ways to reduce D: 1.1 we can design widgets with the minimize D. The typical models are pop-up liner layout and pie-menus circle layout. 1.2 Temporarily bring potential targets to the cursor. This is a recent implement without redesigning the basic behavior. The layout is called drag-and-pop technique that will bring a virtual proxy towards the cursor. The user can manipulate the proxy icons with closer distance. 1.3 Removing empty space between the cursor and targets. The research indicates that a large proportion of pixels are only for display with no certain usage. So here comes the object pointing. That skips the empty space and jumps from one selectable target to another. While the distance of motor reduced, the distance of virtual view remains unchanged. This method seems like promising, however, three weaknesses should also be taken into consideration. First, the empty space makes interaction more facilitate, such as select and manipulate individual pixel or groups of pixels. Second, many situations have already constructed in such a way that objects are tiled together so that the object pointing has no benefit. Third, the fact that eye gaze precedes hand movements make the visual discontinuous will bring bad user experience. ----------For increasing W, two ways are applicable: 2.1 Area cursors. This method takes use of a larger area called active area or hot spot that changes the width of cursor instead of the width of target. 2.2 Expanding targets. This technique makes the size of widgets change dynamically in order to make users focus on the point with a larger target area. I have experienced this feature in the ‘dock’ of Mac OS. Personally, I choose to turn it off, because other notices, such as the change of icons’ color and the notice text, are enough for me to focus on. ----------The last solution is to combine both D and W with dynamically changing the control-display gain. Although the results are still inconclusive, the efficiency can be obtained based on input device speed. ----------Here, I have some ideas about improvements regarding to the Fitts’ law after reading this paper. As said in the paper, Fitts’ law only considers W and D. A possible element that can be measured for user experience is the direction of mouse’s moving path. For instance, people are used to use mouse with left hand so that it is more convenient to move mouse from upper right corner to the lower left corner, but not the direction from upper left corner to lower right. ///////////////////////////////////// The second paper, Beyond Fitts’ Law: Models for Trajectory-Based HCI Tasks, states that Fitts’ law is not fit for the trajectory-based interactions. The author explore some possible robust rules in trajectory-based tasks and make their ‘steering law’. The paper makes four experiments with different constraints that finally comes out ‘general law’ and ‘local law’ of the time to perform a steering task.

Longhao Li 1:41:59 9/16/2014

Critique for “Beating” Fitts’ law: virtual enhancements for pointing facilitation In general, this paper talked about how to speed up users’ operation in graphical interface based on Fitts’ law. Increase target width and decrease moving distance is the basic idea that guides the paper. During this age, graphical interface has become very important in the operation of computers. The goal of graphical interface is try to help people to use computer easier and faster. Thus, Enhance the design of graphical interface is needed. This paper gave us the way to improve the design. It systematically introduced the key points that we need to care about when designing the graphical interface. We need to decrease the moving distance to target on the graphical interface to make the movement between targets faster. We need to increase the size of target to make sure we can reach it easily. There are a lot of methods that we can use to help achieve this in the paper. Designers can enhance their graphical interface a lot by just guided by this paper. Thus, I think that this paper is very important to read and also even treat it as a reference when doing designing work on graphical interface. In the real life, some of the method that introduced in the paper is used. Apple make their dock of application icons in Mac OS be expendable. When mouse reach it, corresponding icon will expend so that user will be easy to click the icon that they want to click. Also in the car used computer graphical interfaces, the idea also works. Lexus have the graphical interface that based on mouse operation. It is faster than touch screen since people need to do more physical movement to do the action, because the screen is hard to reach when they are driving. Also to make the operation easier, they enhanced the mouse operation by magnetically attract the mouse to the icon that near it. User just need to moving mouse one step to another target. It definitely makes the operation faster, and by doing this, it make the operation of computer during driving safer. Critique for Beyond Fitts’ Law: Models for Trajectory-Based HCI Tasks This article mainly talked about a new understanding related to Fitts’ Law. It points out the liner relationship between time for moving from one point to another and width of the space that can move in. Based on experiment, the author find out that in some case that Fitts’ law are not working, in which that when people are drawing lines in a tunnel liked space from one point to another. In this situation, based on the author’s analysis, a liner relationship between width and moving time has been detected. But this relationship has limitation that when the width of the tunnel expend to some level, the relationship will be no loner exist. By using this idea, we can guide the design of the graphical interface to make sure that people can moving to their target as fast as they can. Instead of Fitts’ law, it will be more accurate in this certain situation. There is a lot of area that we need to use this law when doing designing work. When we are designing the scrolling bar, we may need to consider the size to help user to easily point on certain position. It is the same story when design the timeline of media player. The iPod used to have the donut shape touching pad to adjust volume, brightness and also fast forward and backward by draw circle on it. The width of the pad is important. Small pad may need user to do scrolling carefully and bigger size pad may need a bigger device size so that this study maybe helpful for the designers of iPod to make their touch pad on the right size for users to use, and I think they did a good job on that.

Brandon Jennings 1:48:52 9/16/2014

Beyond Fitt’s Law This paper discusses the limitation of Fitt’s Law in that it only addresses pointing movement. The paper introduces a paradigm that attempts to model trajectory-based tasks as mathematical equations, similarly to Fitt’s Law. One thing I liked about this paper is that they used different experiments to define equations to address what Fitt’s Law could not. I think the authors designed experiments to address the different common variations of typical trajectory human interaction. What makes this paper important is that Fitt’s law was a notion when technology was limited to point interfaces. This paper breaks into a new category of interfaces and attempts to mathematically describe them such that they can be optimized to make the user’s experience better. Some applications can interact using handwriting and some can use drawn pictures and symbols. The systems are becoming more interactive via new techniques and this paper represents how to model such techniques. This paper applies to technology today, especially in the field of mobile applications. When I think about the evolution of applications, I can see significant improvements in the interfaces of different applications. In the beginning it was a lot of taps (pointing). Then applications began including slide and swipe features in their applications to bring up new menu options or to move from page to page. Beating Fitt’s Law This paper describes how to improve Fitt’s Law. It analyzes research in the field that attempts to improve pointing performance by modifying parameters of Fitt’s Law. I found the optimization techniques interesting. I appreciated the investigation into the more influential paramters. In fact I have seen many of the techniques described in the paper. Expanding targets to increase W has been implemented by Apple in their Mac OS toolbar. Reducing D by brining targets to the cursor has been a technique I have seen on Windows machines, where the mouse automatically goes to a common button (automatically goes to the “OK” button on message displays). Of course combining the two, increase of W and decrease of D would be the optimal solution. Though there is a downside of these techniques for when choosing one of multiple targets close together. The downside to this paper is that it is talks about optimizing Fitt’s Law. It is good to address how to improve the formula, but the problem is that Fitt’s Law is only for pointing interfaces. There is more to human computer interfaces than just simple pointing movements. The other paper, which is an older paper, discusses trajectory-based interfaces and how to analyze them mathematically, as Fitt’s Law does not apply as well. I admire the approach of adjusting the parameters to optimize the law but it would be more productive and beneficial to formulate a law that covers both point interfaces and other techniques as well, i.e. trajectory-based.

Yingjie Tang 1:50:06 9/16/2014

The article ‘‘Beating’’ Fitts’ law: virtual enhancements for pointing facilitation is a survey which discusses the difficulties and challenges in user graphical interface. How to enhance the performance of pointing in user interface is the main problem that has been discussed. According to Fitts’ law, there are three ways to enhance the performance of pointing, reduce the distance between the cursor and the icon, make the width of the icon bigger, or apply them at the same time. Dynamic width of the icons is very useful in enhancing the pointing performance. Apple OS has applied it in it’s system and the dock is a line of icons that provide the shortcut for users. When the number of icons become bigger, the size of the icons will be reduced automatically. Consequently, there are two main advantages by applying it. 1st is that it largely minimize the blank space so that users can point to the target more efficiently, when the number of the icons reduces, the size of the icons will become bigger and the moving time for user to get to the target will be reduced. 2nd is that it prevent the situation that icons group together when there are more icons on the dock. Although the dynamic icon width is very useful theoretically, but the excessive use of it will affect the arithmetic of the design in graphical interface.———————————————————————————————————— The article Beyond Fitts’ Law: Models for Trajectory-Based HCI Tasks mainly analyzes the drawback of Fitts’ Law and carried Fitts’ Law a step forward. Fitts’ Law is a law in human-computer interaction that measures the performance of the techniques. However, based on the time and the history it was carried out, although it is very useful in graphical interface analysis, it can not be applied to some new input and output relations of human computer interaction. For example, 3D inputs and the electronic helmet which give the users the feeling of reality. The article explored the possible existence of some robust regularities in movement tasks, so that we can generate some mathematical relations in new inputs like Fitts’ Law to solve this problem. In my point of view, this may be useful in some circumstance, but it is not vital in the measurement of some interface design. Because the way of human computer interaction is too diverse and it is changing drastically. Like the mobile devices, the spirits of Fitts’ Law can seldom be used in the assessment of mobile computing because there is not any mouse for the controller and it’s just gestures. So there is meaningless to discuss the extension of Fitts’ Law.

Yubo Feng 2:14:13 9/16/2014

After reading the both passage, I find something interesting: it seems that the importance of Fitt's law is far beyond what I thought: Authors try to use experiment to design and to figure out what is it that where is the limit of human's reaction speed, and when people try to pointing at in virtual world, what is the hot area and in which model people's reaction could be described as accurate as they can. Different from command line interface, graphic interface is more complicated, especially when we try to use psychology to measure them, it connected to a lot of things that is too tiny to be noticed but according to authors' dedicated experience, they could be measured and that is what I should learn and most interested in.

Xiaoyu Ge 2:36:54 9/16/2014

“Beating” Fitts’s law: virtual enhancements for pointing facilitation This paper did a survey on the technology for pointing at targets in graphical user interface. The paper stated that the parameters affect the performance of the virtual pointing by decreasing D and increasing W. Author listed several technologies in order to increase pointing performance. For reducing D, author introduced Design widgets, bring potential targets to the cursor, and removing empty space between cursors and target. For increasing W, the paper introduced Area cursor. Expanding targets. As for decreasing D and increasing W at same time, which suppose to provide the best performance. But after using the method dynamically changes control-display gain, the result is still inconclusive. Moreover no other effective suggestions are introduced in this paper. The survey concluded that some technical difficulties such as increase W do not scale well to perform multi-task selection and technology limitations such as lacking of technology solutions to accurately predict cursor trajectory. Author concluded that none of the technologies works well on all conditions, so the further research can direct to combine these technologies. And author stated that technology should be evaluated base on end-user experience rather than purely quantitative performance measures itself. I agree with most of points in the paper, for example the evaluation should include the aspect of end-users. And the method of combine the technology as further research. An Error Model for Pointing Based on Fitts’ Law Error Model is very useful in analytical quantities assessment to evaluate and provides good error-rate prediction. The paper’s mean idea is to show that Fitts’ law is the most prevalent of law of HCI. But the author also mentioned about “However, Fitts’ law is centrally concerned with movement- time prediction, not the prediction of error rates. In this work, we “round out” the theory by deriving an error model for pointing that is strongly implied by Fitts’ law. The model holds over a range of target sizes, target distances, and movement times, although discontinuities with Fitts’ law emerge concerning the role of target size. Researchers, modelers, designers, and usability experts may benefit from quantitative models such as ours, which provide input for design and support rigorous evaluation of interactive systems.” And I agree to above claim. I think this paper has a great influence on HCI and the quantitative models introduced in this certainly will benefited me a lot. Beyond Fitts`s Law: Models for Trajectory-Base HCI Tasks In this paper the author introduced the concept of robust regularities in trajectory-Based tasks- Steering through tunnels. This paper took experiments to derive and validate the quantitative relationships between completion time and movement constraints in trajectory-based task. The first experiment shows that a steering task with constrains on two goals have a logarithmic relationship. In second experiment there is strong correlation between the hypothesized model and data collected but the error rate is considerably higher. And the third experiment shows that the completion time of the successful trials and index of difficulty forms a linear relationship again for the narrowing tunnel steering task with a high error rate. As for the spiral tunnel model the prediction of difficulty of steering tasks is also valid for complex task. The paper further explored the possible existence of other robus regularities in movement tasks. The paper is useful for the further development of quantitative assessment of user interface. And author builds these models by expending the classic Fitts` law since it have already applied to pointing task and can be extend to trajectory-based task. The paper have a good research direction and the expending law introduced is beneficial and can also be extend for further research and use for quantity assessment.

yeq1 5:46:55 9/16/2014

Beating Fitts' law: Virtual enhancements for pointing facilitation In this survey, the author summarized some existing literatures on why Fitz law holds, why this might not be true in virtual world, and what are some of the past attempts to make pointing performance better than suggested by Fitz law. The techniques such as pie and linear menus, bringing targets to cursors, expanding targets, and finding the right C-D ratios are all the techniques that utilizes the advantages that the virtual interfaces can be metamorphic. I think the author has correctly identified why the techniques could allow pointing performance to be better than stated by Fitt’s law. I also agree that there’s a lack of literature that directly compares one technique with the other, instead of with the baseline. However, I think in trying to find some of the shortcomings of the existing techniques, the authors seems to only try to argue based on human’s physiology, and seems to have completely ignored cognitive science and other disciplines. Other than the pie menu, most of the other techniques described had been used sparingly today. In fact, I have seen many of these techniques being adopted by mouse drivers and some specialized applications. I can also list a bunch of other techniques that the authors did not mention that would fit into this category: automatically move mouse over the default buttons in the dialog box, sensitivity switch, and automatic sensitivity adjustment based on number of objects selectable, etc. etc. Few of them had become part of the standard interface. This is not because these techniques has failed in identifying limits of human’s physiology. But they have failed for many other reasons. For example: while pie menu further reduces the distance to target, but it only works better than linear menu when the targets are predictable. (I’ll leave the “why” to the readers, since it is part of the design of our assignment.) Object pointing distracts the user when they have to focus between the pointer and the next object several inches away, even if dynamic preview is enabled. Similarly, I have found out the hard way that enabling auto mouse over increases my error rate since dialog boxes often pops up sometimes when I don’t expect them. Automatic sensitivity adjustment is problematic due to sometimes unable to form relationships between number of items in screen and number of objects, and the number of objects are sometimes unpredictable (when I load a new web page, for example). Similarly, I found displaying invalid selections in smaller text is almost as bad as having them disappear entirely: both of them would not allow me to form automations on context menu selections. This perhaps shows that in some of the HCI research, the researchers often try to focus on one and only one performance measurement, and ignores other important metrics. Indeed, one thing that makes the virtual interface different from the real interface is the ability to dynamically adjust the interface dynamically. However, I would argue it is very easy to mislead the user into forming an incorrect conceptual model when this distinction is being used as a way to improve the performance. Instead, I think while it is true that Fitts’ law can be beaten this way, I do not think it is right for designers to continue to pursue ways that requires the users to think differently when interacting with machines than they interact with other real world objects. I still think Fitts’ law can be beaten, but I think it can be beaten in ways that does not require the user to make an extra effort. The authors have limited their visions in thinking pointing should be done 2D with a pointing device like a mouse, but advances in technology may allow us to interact with the computer in different ways. We can, for example, select and point the objects by looking at them. Helmet tracking had seen wide adaptations in Air Force of U.S. Russia. The new CCIP (Common Configuration Implementation Program) retrofits the aircrafts with some advanced technologies. For example: HMD (helmet mounted display), HMSD (helmet mounted sight & display), and the new BAE system from U.K. (See how it works, what it does, and the design & testing processes with videos: ) allows the aircraft to sense the elevation, azimuth, and tilt of the pilot’s head relative to the aircraft so it can correctly aim the boresight, and use it as POI for guided weapons and sensors. It also allows the pilot to glance at vital information about the aircraft without having juggle between searching for POI and looking at the instruments. Similar technologies had also started to appear in recent commercial products as well, though they are still less advanced than the military counterpart (such as the amazon’s 6 camera device). Furthermore, there had also been studies on how to capture human thoughts. Unlike the techniques mentioned in the paper, these technologies can beat the Fitts’ law without having to force users to make any extra effort. I think these techniques are promising directions that would potentially allow us to revolutionize target selection tasks in the future. Beyond Fitts' Law: Models for Trajectory-Based HCI Tasks In this paper, the authors are basically trying to answer two questions: to what extend does Fitts’ law hold when the target selection consists of more than one target in order, and how we should model target selection with more than one target. The authors have used some math learned in typical college level calculus courses and found out that selection in a tunnel of the same width is strongly correlated to the limit of the Fitts’ law, when it is applied N times as N approaches infinity. The shape of the tunnel can be characterized by taking vector integral on the width. The authors had found a strong correlation between this and the experiment as well. I think this paper is a great example of how to do graduate level research. Often we don’t have unlimited amount of time or resources, and being able to come up with a workable idea is important. In this example, I think the hardest work the authors did was coming up with the idea of trying out Fitts’ law in tunnel selection tasks. Once the authors had decided to do this, the rest of the materials are pretty much there to grab. The theory they’re using makes so much sense I almost don’t even need to look at the experiment results. In fact, this is not the only paper I have seen that’s revolved on such as simple idea. Things like multi-key encryption relying on high school algebra (polynomial, and the paper is exactly 2 pages long…) continues to impress me about once a month.

Xiyao Yin 7:47:12 9/16/2014

‘‘Beating’ Fitts’ law: virtual enhancements for pointing facilitation ’ mainly discusses with new techniques for pointing at targets in graphical user interfaces. It provide an important idea that in contrast to pointing to physical objects in the real world, virtual pointing is easier than its physical counterpart. Those techniques mainly focus on two possible approaches for further optimization, reduce D or increase W. Although some improvements have been found in each technique, all of them still have their own problems. Those techniques can be divided into three groups: decrease D(including Designing widgets that minimize D, Temporarily bringing potential targets to the cursor and Removing empty space between the cursor and targets), increase W(including Area cursors and Expanding targets) and both decrease D and increase W(Dynamically changing the control-display again). Although none of those techniques has yet to be demonstrated to work uniformly well in all situations encountered in typical graphical user interfaces, this paper still brings us a significant conclusion. One common problems appears in many of the techniques is that difficulties arise when they are used for selecting one of multiple targets that are spatially close together and this may be a fundamentally intractable problem. In my opinion, combinations of the various techniques should be an improvement in all these techniques, so future design may need to focus on this. ‘Beyond Fitts’ law: Models for Trajectory-Based HCI Tasks ’ firstly shows the main idea of Fitts’ law and then carries the spirit of Fitts’ law a step forward and explores the possible existence of other robust regularities in movement tasks. It uses several experiments to derive and validate quantitative relationships between completion time and movement constraints in trajectory-based tasks. Fitts’ law is used to translate performance scores into a performance index that is independent of those experimental details. However, it is obvious that Fitts’ law addresses only one type of movement. This paper tries to address trajectory-based tasks beyond Fitts’ law, using these following experiments. Goal passing shows that a steering task with constraints on both two goals follows the same logarithmic law as Fitts’ tapping task. Increasing constraints finds a strong correlation between the hypothesized model and the data collected. Narrowing tunnel test if the method could be applied to linear trajectories but with a non-constant path width and Spiral tunnel test the method for complex paths. These experiments all use carefully prove(step by step) through mathematical logic, and then include them into new formulas. This is an extremely important in researching.

Jose Michael Joseph 8:07:38 9/16/2014

Beyond Fitts’ Law: Model for Trajectory Based HCI Tasks This paper talks about the various experiments that led to their formation of equations that can predict the time taken by a user to move the mouse in a predefined trajectory. The main argument of this paper is that the simple tapping tasks of Fitts’ law were insufficient to predict the time taken for things like user drawn trajectories which are increasingly becoming common in the current user’s level of interaction. A simple example would be to draw things in MS Paint or any such software. Since such interactions are becoming common there is a growing need to understand the time taken by such user driven activities so that we can devise models that are more efficient and can reduce this time. Currently in the field of HCI there are very few quantitative tools like definite equations available, the most prominent one is the Fitts’ Law and most research is based on it. While Fitts’ Law is excellent in itself it often proves to be insufficient to measure more complex tasks. As an example of Fitts’ Law’s insufficiency the author has pointed out that although in practice the user feels a significant difference between writing with a mouse and writing with a stylus, formal Fitts’ Law studies show that there is no significant performance difference. While the example may be partially true about the nature of the accuracy of Fitts’ Law in predicting all aspects of the human interaction one must also think why the performance is similar even though the users say they feel a tremendous difference is using both the devices. Thus we question the author’s claim which questions Fitts’ Law’s accuracy. The author has stumbled upon a notion that “the larger the amplitude the less precise the result is” and it seems to intuitively fit with the various circumstances that humans have to deal with in day to day life like driving on a narrow road. The author conducted four experiments to derive the equation that can be used to predict the time taken for a trajectory. Although it is a remarkable task we must question the precise setting and results of his experiment. His first experiment had the same results as what Fitts’ Law predicted which would show to an extent that Fitts’ Law is not entirely wrong in itself in predicting user interaction. Another problem is the fact that the author gave sufficient time during each experiment for the users to first have a practice round. This decreases the efficacy of the experiment as the results change drastically for any given human interaction experiment once the test subjects are familiar with the settings. Another point of contention was that most of the author’s experiments had a high error rate, much higher than that reported by subjects in Fitts’ Law’s experiments. Such a result need to be clearly studied to understand whether the equation the author has provided indeed is sufficient as many times if the trajectory is wrong (example drawing something in Paint) the user has to start the process all over again. Thus a high error rate would equate with a longer time in performing the overall task. In addition to what the author has already done, something more that I would’ve done would have been to use the equation that has been derived in this paper and try it on the various menus in the various operating systems currently being used. This would have given the reads a good practical idea about which systems are more efficient for trajectory based tasks. By only providing an equation the authors have left the results that this equation could have potentially provided to the imagination of the readers.

Jose Michael Joseph 8:08:05 9/16/2014

“Beating” Fittss’ law: virtual enhancements for pointing facilitation This article surveys the various ways designers and scientists have tried to beat the Fitts’ Law which asserts that the movement time to acquire a target is governed by an equation which uses the width W and distance D. While there have been numerous attempts to get past the limitation of this law, as the author states none of these techniques are fool proof and often have a particular area where they fail. Most difficulties arise when they are used for selecting multiple targets that are spatially close to each other. Thus it becomes hard to predict the target that the user intended is. The only sure way to solve this problem would be to find a way to accurately predict the cursor’s trajectory. The three most common approaches taken by various computer scientists are to either reduce the distance between the target and the cursor, increase the width of the target or do both. Out of all methods the technique that looks most promising is technique that changes the control display transfer function. By dynamically varying the C-D gain based on input device speed we obtain mouse acceleration which reduces the distance between the target and the cursor. A further modification produces the semantic pointing which uses mouse acceleration along with knowledge about the relative location of the targets thus increasing the speed of the cursor when the targets are sparse and separated and decreasing when they are nearer to each other. I believe adding this functionality with the technique of expanding targets can greatly improve the speed as it would simultaneously decrease the distance and increase the width of the target. One major drawback of the various techniques that have been analyzed in the paper is that they do not take user satisfaction into account. Even though a particular design modification results in increased accessibility of the various targets on the screen if it decreases or hampers user aesthetics then such a modification would be unfavorable amongst the users. User satisfaction is of utmost importance when deciding changes in the graphical user interface as the only changes it actually makes to the system are its perception and accessibility. An approach that current designers have taken to solve this problem is by introducing features such as “tiles” in Windows 8 which are large widgets that are placed close to each other. This reduces the distance that the cursor has to travel while simultaneously increasing the width of the target. Although such a technique greatly increases accessibility, its public reception has been mixed with many users opting out as they are displeased by the aesthetics, further exhibiting the importance of user acceptance of changes in graphical interface. The reason the results of this paper are not too admissible is because the various systems that were surveyed by the paper were tested on various environments. To fully understand the strengths and drawbacks of each system, ideally all of them should have been tested on one common standardized environment. A lack of such an environment raises doubts in the results produced by comparing the various techniques. Although the author questions the necessity for research into pointing devices in the current age where touch and haptic feedback systems are the ones being predominantly introduced in newer machines, the continuing persistence of the mouse and the human affection for such a pointing device is reason enough to warrant further research into this field to produce a more efficient pointing device if possible.

Qiao Zhang 9:01:00 9/16/2014

Beating Fitts' law: Virtual enhancements for pointing facilitation This paper surveys different pointing facilitation techniques under virtual environment in three directions with regards to the Fitts' Law: 1) Reducing the target distance; 2) Increasing the target width; 3) Both. The authors find that problems arise when multiple targets are spatially close together. Moreover, the choice of input device significantly affects the result. The background part introduces several models of human movement. Standard deviation is a measure of precision. In Meyer's model, the standard deviation of a movement can be modeled by the distance over the duration, multiplied by a constant. It tells us that in order to precisely target an object, one needs to perform shorter movement in a longer time. Coincidentally, we wanted to use pie menu for our virtual keyboard project. The reason is exactly as described in this article: to reduce the distance of the target object. However, we find it infeasible because 1) Text may be too long to display in a circular ring; extending texts outside of the range will cause visual clutter. 2) People are not used to read texts in a circular fashion. But in my opinion, pie menu has great potential in game industry, where icons are more frequently used rather than texts. The drag-and-pop approach does not seem good to me, because when I want to drag a document towards a position, I would have a mental model inside and I know where I should move my mouse to. If the positions change, it actually forces me to reconstruct my mental model of target position. For modern computers, the DPI of devices can be easily changed. This idea does not suit the situation today. The jumping motion method is not applicable in real life because it uses a completely different paradigm which violates the users' mental model. However as the article suggests, it might be useful in some special cases, for example, industrial machine manipulation. Expanding the cursor size or the target size is widely adapted today. The study highlights the importance of careful interaction design, and the importance of not relying solely on the results of controlled experiments that look at only one aspect of a new pointing technique's performance. It is interesting to see how research trends shift during these decades. Today researchers are worrying about the big fingers, while in the 90s they are curious about moving a pointer across a large screen. ============================================== Beyond Fitts' Law: Models for Trajectory-Based HCI Tasks Because the Fitts' Law does not directly apply to trajectory dependent movements, the authors take Fitts’ law a step forward and explored the possible existence of other robust regularities in movement tasks. In this study, the researchers design four experiments to construct models to predict the difficulties of different tasks. They first demonstrated that the logarithmic relationship between movement time and tangential width of target in a tapping task also exists between movement time and normal width of the target in a “goal passing” task. A thought experiment of placing infinite numbers of goals along a movement trajectory lead us to hypothesize that there is a simple linear relationship between movement time and the “tunnel” width in steering tasks. They then confirmed such a relationship in three types of “tunnels”: straight, narrowing, and spiral. One interesting thing is that the tunnel experiment reminds me of an old game back in the days of my elementary school. In that game, the user has to go through a maze-like tunnel within certain time. It is exactly the same idea of one of the experiment conducted. I am wondering if the game designer borrowed any ideas from this paper. The main contribution of this study is that the researchers find a linear model that generalizes the Fitts' law to predict the difficulty i.e. a human's performanceof a trajectory task.