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

Published: 05 November 2015 Publication History
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  • Abstract

    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.

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

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      cover image ACM Conferences
      UIST '15: Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology
      November 2015
      686 pages
      ISBN:9781450337793
      DOI:10.1145/2807442
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      Published: 05 November 2015

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      Author Tags

      1. feature-rich software
      2. feedforward
      3. help
      4. learning
      5. tooltips

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      UIST '15 Paper Acceptance Rate 70 of 297 submissions, 24%;
      Overall Acceptance Rate 842 of 3,967 submissions, 21%

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      • (2024)Why and When LLM-Based Assistants Can Go Wrong: Investigating the Effectiveness of Prompt-Based Interactions for Software Help-SeekingProceedings of the 29th International Conference on Intelligent User Interfaces10.1145/3640543.3645200(288-303)Online publication date: 18-Mar-2024
      • (2024)Do I Just Tap My Headset?Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314517:4(1-28)Online publication date: 12-Jan-2024
      • (2023)From Discovery to Adoption: Understanding the ML Practitioners’ Interpretability JourneyProceedings of the 2023 ACM Designing Interactive Systems Conference10.1145/3563657.3596046(2304-2325)Online publication date: 10-Jul-2023
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      • (2022)Command SelectionHandbook of Human Computer Interaction10.1007/978-3-319-27648-9_19-1(1-35)Online publication date: 12-Mar-2022
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      • (2021)Model-based Engineering of Feedforward Usability Function for GUI WidgetsInteracting with Computers10.1093/iwcomp/iwab01433:1(73-91)Online publication date: 18-May-2021
      • (2020)Examining Whether Secondary Effects of Temperature-Associated Virtual Stimuli Influence Subjective Perception of Duration2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)10.1109/VR46266.2020.00070(493-499)Online publication date: Mar-2020
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