Benjamin J. Lafreniere

Community enhanced tutorials: improving tutorials with multiple demonstrations

Web-based tutorials are a popular help resource for learning how to perform unfamiliar tasks in complex software. However, in their current form, web tutorials are isolated from the applications that they support. In this paper we present FollowUs, a web-tutorial system that integrates a fully-featured application into a web-based tutorial. This novel architecture enables community enhanced tutorials, which continuously improve as more users work with them. FollowUs captures video demonstrations of users as they perform a tutorial. Subsequent users can use the original tutorial, or choose from a library of captured community demonstrations of each tutorial step. We conducted a user study to test the benefits of making multiple demonstrations available to users, and found that users perform significantly better using our system with a library of multiple demonstrations in comparison to its equivalent baseline system with only the original authored content.

AdaptableGIMP: designing a socially-adaptable interface

We introduce the concept of a socially-adaptable interface, an interface that provides instant access to task-specific interface customizations created, edited, and documented by the applications user community. We demonstrate this concept in AdaptableGIMP, a modified version of the GIMP image editor that we have developed.

Faster Command Selection on Touchscreen Watches

Small touchscreens worn on the wrist are becoming increasingly common, but standard interaction techniques for these devices can be slow, requiring a series of coarse swipes and taps to perform an action. To support faster command selection on watches, we investigate two related interaction techniques that exploit spatial memory. WristTap uses multitouch to allow selection in a single action, and TwoTap uses a rapid combination of two sequential taps. In three quantitative studies, we investigate the design and performance of these techniques in comparison to standard methods. Results indicate that both techniques are feasible, able to accommodate large numbers of commands, and fast users are able to quickly learn the techniques and reach performance of ~1.0 seconds per selection, which is approximately one-third of the time of standard commercial techniques. We also provide insights into the types of applications for which these techniques are well-suited, and discuss how the techniques could be extended.

HandMark Menus: Rapid Command Selection and Large Command Sets on Multi-Touch Displays

Command selection on large multi-touch surfaces can be difficult, because the large surface means that there are few landmarks to help users build up familiarity with controls. However, peoples hands and fingers are landmarks that are always present when interacting with a touch display. To explore the use of hands as landmarks, we designed two hand-centric techniques for multi-touch displays -- one allowing 42 commands, and one allowing 160 -- and tested them in an empirical comparison against standard tab widgets. We found that the small version (HandMark-Fingers) was significantly faster at all stages of use, and that the large version (HandMark-Multi) was slower at the start but equivalent to tabs after people gained experience with the technique. There was no difference in error rates, and participants strongly preferred both of the HandMark menus over tabs. We demonstrate that peoples intimate knowledge of their hands can be the basis for fast and feasible interaction techniques that can improve the performance and usability of interactive tables and other multi-touch systems.

Crowdsourced Fabrication

In recent years, extensive research in the HCI literature has explored interactive techniques for digital fabrication. However, little attention in this body of work has examined how to involve and guide human workers in fabricating larger-scale structures. We propose a novel model of crowdsourced fabrication, in which a large number of workers and volunteers are guided through the process of building a pre-designed structure. The process is facilitated by an intelligent construction space capable of guiding individual workers and coordinating the overall build process. More specifically, we explore the use of smartwatches, indoor location sensing, and instrumented construction materials to provide real-time guidance to workers, coordinated by a foreman engine that manages the overall build process. We report on a three day deployment of our system to construct a 12-tall bamboo pavilion with assistance from more than one hundred volunteer workers, and reflect on observations and feedback collected during the exhibit.

Task-centric interfaces for feature-rich software

Feature-rich software can be difficult to learn and use, and current approaches to organizing functionality do little to help users with performing unfamiliar tasks. In this paper, we investigate the potential for alternative task-centric interface designs that organize functionality around specific tasks. To understand the potential of this approach, we developed and studied Workflows, a prototype task-centric interface design. Our findings suggest that task-centric interfaces scaffold and guide the users exploration of a subset of application functionality, and thereby help them to avoid common difficulties and inefficiencies caused by self-directed exploration of the full interface. We also found evidence that task-centric interfaces enable a different kind of application learning, in which users associate tasks with relevant keywords as opposed to low-level commands and procedures. This has potential benefits for memorability, because the keywords themselves describe the task, and scalability, because a few keywords can map to an arbitrarily large procedure.

No Need to Stop What You’re Doing: Exploring No-Handed Smartwatch Interaction

Smartwatches have the potential to enable quick micro-interactions throughout daily life. However, because they require both hands to operate, their full potential is constrained, particularly in situations where the user is actively performing a task with their hands. We investigate the space of no-handed interaction with smartwatches in scenarios where one or both hands are not free. Specifically, we present a taxonomy of scenarios in which standard touchscreen interaction with smartwatches is not possible, and discuss the key constraints that limit such interaction. We then implement a set of interaction techniques and evaluate them via two user studies: one where participants viewed video clips of the techniques and another where participants used the techniques in simulated hand-constrained scenarios. Our results found a preference for foot-based interaction and reveal novel design considerations to be mindful of when designing for no-handed smartwatch interaction scenarios.

These Aren't the Commands You're Looking For : Addressing False Feedforward in Feature-Rich Software

The names, icons, and tooltips of commands in feature-rich software are an important source of guidance when locating and selecting amongst commands. Unfortunately, these cues can mislead users into believing that a command is appropriate for a given task, when another command would be more appropriate, resulting in wasted time and frustration. In this paper, we present command disambiguation techniques that inform the user of alternative commands before, during, and after an incorrect command has been executed. To inform the design of these techniques, we define categories of false-feedforward errors caused by misleading interface cues, and identify causes for each. Our techniques are the first designed explicitly to solve this problem in feature-rich software. A user study showed enthusiasm for the techniques, and revealed their potential to play a key role in learning of feature-rich software.

Investigating How Online Help and Learning Resources Support Children's Use of 3D Design Software

3D design software is increasingly available to children through libraries, maker spaces, and for free on the web. This unprecedented availability has the potential to unleash childrens creativity in cutting edge domains, but is limited by the steep learning curve of the software. Unfortunately, there is little past work studying the breakdowns faced by children in this domain-most past work has focused on adults in professional settings. In this paper, we present a study of online learning resources and help-seeking strategies available to children starting out with 3D design software. We find that children face a range of challenges when trying to learn 3D design independently-tutorials present instructions at a granularity that leads to overlooked and incorrectly-performed actions, and online help-seeking is largely ineffective due to challenges with query formulation and evaluating found information. Based on our findings, we recommend design directions for next-generation help and learning systems tailored to children.

Investigating the Post-Training Persistence of Expert Interaction Techniques

Expert interaction techniques enable users to greatly improve their performance; however, to realize these advantages, the user must first acquire the skill necessary to use a technique, then choose to use it over competing novice techniques. This article investigates several factors that may influence whether use of an expert technique persists when the context of use changes. Two studies examine the effect of changing performance requirements, and find that a high performance requirement imposed in a training context can effectively push users to adopt an expert technique, and that use of the technique is maintained when the requirement is subsequently reduced or removed. In a final study, performance requirement, high-level task, and environment of use are changed—participants played a training game to learn the menu for a drawing application, which they then used to complete a series of drawings over the following week. Participants exhibited a somewhat surprising “all-or-nothing” effect, using the expert technique nearly exclusively or not at all, and maintaining this behavior over a range of qualitatively different tasks. This suggests that switching to an expert technique involves a global change by the user, rather than an incremental change as suggested by previous work.