Supercharging Trial-and-Error for Learning Complex Software Applications

Damien Masson, Jo Vermeulen, George Fitzmaurice, Justin Matejka

January 2022 · Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (CHI)

Abstract

Despite an abundance of carefully-crafted tutorials, trial-and-error remains many people’s preferred way to learn complex software. Yet, approaches to facilitate trial-and-error (such as tooltips) have evolved very little since the 1980s. While existing mechanisms work well for simple software, they scale poorly to large feature-rich applications. In this paper, we explore new techniques to support trial-and-error in complex applications. We identify key benefits and challenges of trial-and-error, and introduce a framework with a conceptual model and design space. Using this framework, we developed three techniques: ToolTrack to keep track of trial-and-error progress; ToolTrip to go beyond trial-and-error of single commands by highlighting related commands that are frequently used together; and ToolTaste to quickly and safely try commands. We demonstrate how these techniques facilitate trial-and-error, as illustrated through a proof-of-concept implementation in the CAD software Fusion 360. We conclude by discussing possible scenarios and outline directions for future research on trial-and-error.

DOI PDF

Figures

Figure 1: We present a Conceptual Model for trial-and-error and three techniques that improve support for trial-and-error in complex software at the Exploration, Execution and Recovery phases: ToolTra

Figure 2: Our conceptual model of trial-and-error. References to the challenges presented in Section 4.2 are underlined in red. The Exploration and Execution phases are further detailed in Figure 3 and Figure 4 respectively.

Figure 3: The exploration phase in the conceptual model.

Figure 4: Conceptual model of the execution phase.

Figure 5: Design space of support for trial-and-error.

Figure 6: ToolTrack shows unexplored commands with a yellow triangle, and for commands that have been used before, it shows a progress bar indicating how deeply that command has been explored.

Figure 7: ToolTrip ofers workfows that contain a particular command under the mouse cursor, highlighting other commands in that workfow with numbered badges.

Figure 8: ToolTaste allows users to test any command, even if it is currently disabled – either on the current document or on an example that has been curated to work with that command.

Figure 9: Our prototype implementation in Fusion 360 showing ToolTrack (A), ToolTrip (B, C, D) and ToolTaste (E, F).

Figure 10: Creating a pen holder by following a ToolTrip ti-tled “Phone Holder”.

Figure 11: Exploring an alternative approach using ToolTaste to work on a copy, and ToolTrack to pragmatically explore relevant commands and options.

BibTeX

@inproceedings{10.1145/3491102.3501895,
 abstract = {Despite an abundance of carefully-crafted tutorials, trial-and-error remains many people’s preferred way to learn complex software. Yet, approaches to facilitate trial-and-error (such as tooltips) have evolved very little since the 1980s. While existing mechanisms work well for simple software, they scale poorly to large feature-rich applications. In this paper, we explore new techniques to support trial-and-error in complex applications. We identify key benefits and challenges of trial-and-error, and introduce a framework with a conceptual model and design space. Using this framework, we developed three techniques: ToolTrack to keep track of trial-and-error progress; ToolTrip to go beyond trial-and-error of single commands by highlighting related commands that are frequently used together; and ToolTaste to quickly and safely try commands. We demonstrate how these techniques facilitate trial-and-error, as illustrated through a proof-of-concept implementation in the CAD software Fusion&nbsp;360. We conclude by discussing possible scenarios and outline directions for future research on trial-and-error.},
 address = {New York, NY, USA},
 articleno = {381},
 author = {Masson, Damien and Vermeulen, Jo and Fitzmaurice, George and Matejka, Justin},
 booktitle = {Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems},
 doi = {10.1145/3491102.3501895},
 isbn = {9781450391573},
 keywords = {design space, technique, conceptual model, trial-and-error, learning by exploration, software learning},
 location = {New Orleans, LA, USA},
 numpages = {13},
 publisher = {Association for Computing Machinery},
 series = {CHI '22},
 title = {Supercharging Trial-and-Error for Learning Complex Software Applications},
 url = {https://doi.org/10.1145/3491102.3501895},
 year = {2022}
}