Searching for software learning resources using application context

Ekstrand, Michael D.; Li, Wei; Grossman, Tovi; Matejka, Justin; Fitzmaurice, George

doi:10.1145/2047196.2047220

Cited by 30 publications

(28 citation statements)

References 25 publications

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“…Two interrelated themes of their research concern understanding the best interface mechanisms for presenting recommendations to users and devising methods to generate high-quality recommendations. Their key interface goals are that the assistive content should be dynamically updated to maintain contextually relevant assistance [Ekstrand et al 2011], that it should be continually available to the user, and that it should be presented in an ambient manner that allows access at a glance, thus minimizing impediments to access . Figure 10, from Matejka et al [2013], shows their Patina interface adaptation method, which uses colored heatmap overlays to emphasize command recommendations without impeding access to them.…”

Section: Domain 3: Vocabulary Extensionmentioning

confidence: 99%

“…Interfaces to online help systems have evolved substantially since Rieman's study, but more recent studies indicate that online help is still predominantly used as material of last resort [Novick and Ward 2006]. However, this situation may evolve as systems improve at extracting the user's task context (e.g., Ekstrand et al [2011]) and adopt ambient presentation to assure that help is continually ready to hand (e.g., ).…”

Section: Task Training: Manuals Online Help and Tutorialsmentioning

confidence: 99%

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Supporting Novice to Expert Transitions in User Interfaces

et al. 2014

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Interface design guidelines encourage designers to provide high-performance mechanisms for expert users. However, research shows that many expert interface components are seldom used and that there is a tendency for users to persistently fail to adopt faster methods for completing their work. This article summarizes and organizes research relevant to supporting users in making successful transitions to expert levels of performance. First, we provide a brief introduction to the underlying human factors of skill acquisition relevant to interaction with computer systems. We then present our focus, which is a review of the state of the art in user interfaces that promote expertise development. The review of interface research is based around four domains of performance improvement: intramodal improvement that occurs as a factor of repetition and practice with a single method of interaction; intermodal improvement that occurs when users switch from one method to another that has a higher performance ceiling; vocabulary extension, in which the user broadens his or her knowledge of the range of functions available; and task mapping, which examines the ways in which users perform their tasks. The review emphasizes the relationship between interface techniques and the human factors that explain their relative success.

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Section: Domain 3: Vocabulary Extensionmentioning

confidence: 99%

Section: Task Training: Manuals Online Help and Tutorialsmentioning

confidence: 99%

Supporting Novice to Expert Transitions in User Interfaces

et al. 2014

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“…While the captions, labels, and official names given to user interface objects typically constrain the terms used by tutorial writers, numerous factors can give rise to a broader vocabulary and the use of synonyms for identical objects. For example, Ekstrand et al noted that Inkscape users often refer to a "line tool" rather than to the correctly named "pen tool" because this tool is commonly used to draw straight lines [3]. Likewise, we have observed that GIMP tutorials often refer to an "Eyedropper" tool rather than the official name, "Color Picker," because the tool's icon depicts an eyedropper.…”

Section: Entity Linkingmentioning

confidence: 59%

Mining online software tutorials

Fourney

Terry

2014

CHI '14 Extended Abstracts on Human Factors in Computing Systems

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Web-based software tutorials contain a wealth of information describing software tasks and workflows. There is growing interest in mining these resources for task modeling, automation, machine-guided help, interface search, and other applications. As a first step, past work has shown success in extracting individual commands from textual instructions. In this paper, we ask: How much further do we have to go to more fully interpret or automate a tutorial? We take a bottom-up approach, asking what it would take to: (1) interpret individual steps, (2) follow sequences of steps, and (3) locate procedural content in larger texts.

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“…The success rate was low, only 30% -the participants were unable to construct an appropriate search term to describe the problem (Ekstrand et al 2011).…”

Section: Other Traditional Sources Of User Interface Knowledgementioning

confidence: 99%

Inline training: a technique for continuous, within-task learning

Krisler

Alterman

2018

Research in Learning Technology

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As software continues to grow in power and complexity, frequent on-the-job training is essential to maintain a proficient and productive skill set. However once a base operational skill set is attained, software users rarely continue to become proficient with the tools they use on a daily basis. This lack of proficiency results in the frequent occurrence of workflow interruptions due to the continued locating and re-locating of the operators required to perform both new and routine tasks. Aids such as reference cards and application help systems exist to make the user aware of efficient methods for task completion; however, these resources are seldom used. This study presents a new and efficient approach to help software users continue to learn about the tools they use to complete their work. This new approach to learning, called inline training, leverages common workflow interruptions to facilitate the discovery of new application knowledge. At issue is fitting the amount of work necessary to use the trainer into the already occurring interruption window. By understanding the amount of within-interruption work tolerated by the user, including an inline trainer within the window, promotes a deeper understanding of the application, resulting in a more efficient workflow.Keywords: training; continuous learning; learning; software training; interruptions IntroductionIn the modern technological landscape, the tools required to perform everyday tasks change at a rapid pace. Therefore, today's workers must adjust to improvements to the applications that support their work-related activities (Boothby, Dufour, and Tang 2010). The drive for increased productivity, mixed with the pace of technology evolution, makes essential the development of learning technologies for users to remain competitive in the modern workplace (Gravill and Compeau 2008).Although the skills learned in the classroom are an important starting point, in this rapidly changing environment, continuous learning is imperative. The research reported in this article explores inline training as a training style that weds the everyday use of a technology with incremental learning and training, which is directly relevant to the activities of the user (Krisler 2014).This article closely examines how users interact with the tools they use on a daily basis. Initially, they develop a working knowledge of the interface. With this, users can find their way around the interface to complete routine tasks. However, the necessity to get work done prevents the user from progressing beyond a basic understanding of the application (Carroll and Rosson 1987). This failure to develop proficiency results from a strong dependence on basic operators. This limited functional knowledge is the cause of workflow interruptions. These slowdowns manifest themselves through searching for known or 'hoped for' operations.Presented here is an analysis of an experiment designed to leverage the naturally occurring workflow interruptions in normal everyday activities as learning opportunitie...

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Searching for software learning resources using application context

Cited by 30 publications

References 25 publications

Supporting Novice to Expert Transitions in User Interfaces

Supporting Novice to Expert Transitions in User Interfaces

Mining online software tutorials

Inline training: a technique for continuous, within-task learning

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