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DocWizards: a system for authoring follow-me documentation wizards
- In Proc. ACM symposium on User interface software and technology
, 2005
"... Traditional documentation for computer-based procedures is difficult to use: readers have trouble navigating long complex instructions, have trouble mapping from the text to display widgets, and waste time performing repetitive procedures. We propose a new class of improved documentation that we cal ..."
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Cited by 42 (0 self)
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Traditional documentation for computer-based procedures is difficult to use: readers have trouble navigating long complex instructions, have trouble mapping from the text to display widgets, and waste time performing repetitive procedures. We propose a new class of improved documentation that we call follow-me documentation wizards. Follow-me documentation wizards step a user through a script representation of a procedure by highlighting portions of the text, as well application UI elements. This paper presents algorithms for automatically capturing follow-me documentation wizards by demonstration, through observing experts performing the procedure. We also present our DocWizards implementation on the Eclipse platform. We evaluate our system with an initial user study that showing that most users have a marked preference for this form of guidance over traditional documentation. ACM Classification: H5.2 [Information interfaces and
The Impact of Tutorials on Games of Varying Complexity
"... One of the key challenges of video game design is teaching new players how to play. Although game developers frequently use tutorials to teach game mechanics, little is known about how tutorials affect game learnability and player engagement. Seeking to estimate this value, we implemented eight tuto ..."
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Cited by 22 (5 self)
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One of the key challenges of video game design is teaching new players how to play. Although game developers frequently use tutorials to teach game mechanics, little is known about how tutorials affect game learnability and player engagement. Seeking to estimate this value, we implemented eight tutorial designs in three video games of varying complexity and evaluated their effects on player engagement and retention. The results of our multivariate study of over 45,000 players show that the usefulness of tutorials depends greatly on game complexity. Although tutorials increased play time by as much as 29 % in the most complex game, they did not significantly improve player engagement in the two simpler games. Our results suggest that investment in tutorials may not be justified for games with mechanics that can be discovered through experimentation.
Recovering from Errors during Programming by Demonstration
"... Many end-users wish to customize their applications, automating common tasks and routines. Unfortunately, this automation is difficult today — users must choose between brittle macros and complex scripting languages. Programming by demonstration (PBD) offers a middle ground, allowing users to demons ..."
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Cited by 16 (0 self)
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Many end-users wish to customize their applications, automating common tasks and routines. Unfortunately, this automation is difficult today — users must choose between brittle macros and complex scripting languages. Programming by demonstration (PBD) offers a middle ground, allowing users to demonstrate a procedure multiple times and generalizing the requisite behavior with machine learning. Unfortunately, many PBD systems are almost as brittle as macro recorders, offering few ways for a user to control the learning process or correct the demonstrations used as training examples. This paper presents CHINLE, a system which automatically constructs PBD systems for applications based on their interface specification. The resulting PBD systems have novel interaction and visualization methods, which allow the user to easily monitor and guide the learning process, facilitating error recovery during training. CHINLE-constructed PBD systems learn procedures with conditionals and perform partial learning if the procedure is too complex to learn completely. ACM Classification D.2.2 [Design Tools and Techniques]: User Interfaces, H1.2. [Models and principles]: User/Machine
Interpreting Written How-To Instructions
"... Written instructions are a common way of teaching people how to accomplish tasks on the web. However, studies have shown that written instructions are difficult to follow, even for experienced users. A system that understands human-written instructions could guide users through the process of follow ..."
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Cited by 15 (3 self)
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Written instructions are a common way of teaching people how to accomplish tasks on the web. However, studies have shown that written instructions are difficult to follow, even for experienced users. A system that understands human-written instructions could guide users through the process of following the directions, improving completion rates and enhancing the user experience. While general natural language understanding is extremely difficult, we believe that in the limited domain of howto instructions it should be possible to understand enough to provide guided help in a mixed-initiative environment. Based on a qualitative analysis of instructions gathered for 43 web-based tasks, we have formalized the problem of understanding and interpreting how-to instructions. We compare three different approaches to interpreting instructions: a keyword-based interpreter, a grammar-based interpreter, and an interpreter based on machine learning and information extraction. Our empirical results demonstrate the feasibility of automated how-to instruction understanding. 1
Why PBD systems fail: Lessons learned for usable AI
, 2008
"... Programming by demonstration systems have long attempted to make it possible for people to program computers without writing code. These systems typically employ artificial intelligence techniques to learn from user behavior in order to predict their future behavior. However, while these systems hav ..."
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Cited by 12 (0 self)
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Programming by demonstration systems have long attempted to make it possible for people to program computers without writing code. These systems typically employ artificial intelligence techniques to learn from user behavior in order to predict their future behavior. However, while these systems have resulted in many publications in AI venues, none of the technologies have yet achieved widespread adoption. Usability remains a critical barrier to their success. Based on lessons learned from three different programming by demonstration systems, we present a a set of guidelines to consider when designing usable AI-based systems.
Graphstract: Minimal Graphical Help for Computers
"... We explore the use of abstracted screenshots as part of a new help interface. Graphstract, an implementation of a graphical help system, extends the ideas of textually oriented Minimal Manuals to the use of screenshots, allowing multiple small graphical elements to be shown in a limited space. This ..."
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We explore the use of abstracted screenshots as part of a new help interface. Graphstract, an implementation of a graphical help system, extends the ideas of textually oriented Minimal Manuals to the use of screenshots, allowing multiple small graphical elements to be shown in a limited space. This allows a user to get an overview of a complex sequential task as a whole. The ideas have been developed by three iterations of prototyping and evaluation. A user study shows that Graphstract helps users perform tasks faster on some but not all tasks. Due to their graphical nature, it is possible to construct Graphstracts automatically from pre-recorded interactions. A second study shows that automated capture and replay is a low-cost method for authoring Graphstracts, and the resultant help is as understandable as manually constructed help.
Interactive Data Integration through Smart Copy & Paste
"... In many scenarios, such as emergency response or ad hoc collaboration, it is critical to reduce the overhead in integrating data. Here, the goal is often to rapidly integrate “enough ” data to answer a specific question. Ideally, one could perform the entire process interactively under one unified i ..."
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Cited by 8 (2 self)
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In many scenarios, such as emergency response or ad hoc collaboration, it is critical to reduce the overhead in integrating data. Here, the goal is often to rapidly integrate “enough ” data to answer a specific question. Ideally, one could perform the entire process interactively under one unified interface: defining extractors and wrappers for sources, creating a mediated schema, and adding schema mappings — while seeing how these impact the integrated view of the data, and refining the design accordingly. We propose a novel smart copy and paste (SCP) model and architecture for seamlessly combining the design-time and run-time aspects of data integration, and we describe an initial prototype, the CopyCat system. In CopyCat, the user does not need special tools for the different stages of integration: instead, the system watches as the user copies data from applications (including the Web browser) and pastes them into CopyCat’s spreadsheet-like workspace. CopyCat generalizes these actions and presents proposed auto-completions, each with an explanation in the form of provenance. The user provides feedback on these suggestions — through either direct interactions or further copy-and-paste operations — and the system learns from this feedback. This paper provides an overview of our prototype system, and identifies key research challenges in achieving SCP in its full generality. 1.
Creating Contextual Help for GUIs Using Screenshots
"... Contextual help is effective for learning how to use GUIs by showing instructions and highlights on the actual interface rather than in a separate viewer. However, end-users and third-party tech support typically cannot create contextual help to assist other users because it requires programming ski ..."
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Cited by 8 (1 self)
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Contextual help is effective for learning how to use GUIs by showing instructions and highlights on the actual interface rather than in a separate viewer. However, end-users and third-party tech support typically cannot create contextual help to assist other users because it requires programming skill and source code access. We present a creation tool for contextual help that allows users to apply common computer skills—taking screenshots and writing simple scripts. We perform pixel analysis on screenshots to make this tool applicable to a wide range of applications and platforms without source code access. We evaluated the tool’s usability with three groups of participants: developers, instructors, and tech support. We further validated the applicability of our tool with 60 real tasks supported by the tech support of a university campus. ACM Classification: H5.2 [Information interfaces and
An Evaluation of Using Programming by Demonstration and Guided Walkthrough Techniques for Authoring and Utilizing Documentation
"... Much existing documentation is informal and serves to communicate “how-to ” knowledge among restricted working groups. Using current practices, such documentation is both difficult to maintain and difficult to use properly. In this paper, we propose a documentation system, called DocWizards, that us ..."
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Cited by 5 (0 self)
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Much existing documentation is informal and serves to communicate “how-to ” knowledge among restricted working groups. Using current practices, such documentation is both difficult to maintain and difficult to use properly. In this paper, we propose a documentation system, called DocWizards, that uses programming by demonstration to support low-cost authoring and guided walkthrough techniques to improve document usability. We report a comparative study between the use of DocWizards and traditional techniques for authoring and following documentation. The study participants showed significant gains in efficiency and reduction in error rates when using DocWizards. In addition, they expressed a clear preference for using the DocWizards tool, both for authoring and for following documentation. Author Keywords Programming by demonstration, Guided-walkthrough,
Information Integration for the Masses
"... Abstract Information integration applications combine data from heterogeneous sources to assist the user in solving repetitive data-intensive tasks. Currently, such applications require a high level of expertise in information integration since users need to know how to extract data from an on-line ..."
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Abstract Information integration applications combine data from heterogeneous sources to assist the user in solving repetitive data-intensive tasks. Currently, such applications require a high level of expertise in information integration since users need to know how to extract data from an on-line source, describe its semantics, and build integration plans to answer specific queries. We have integrated three task learning technologies within a single desktop application to assist users in creating information integration applications. It includes a tool for programmatic access to data in on-line information sources, a tool to semantically model them by aligning their input and output parameters with a common ontology, and a tool that enables the user to create complex integration plans using simple text instructions. Our system was integrated within the Calo Desktop Assistant and evaluated independently on a range of problems. It enabled non-expert users to construct integration plans for a variety of problems in the office and travel domains. Key Words: Information extraction; web applications; assistants. Category: D.2.11; H.3.5; H.3.6; H.3.7.