Supercharging Trial-and-Error for Learning Complex Software Applications


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.

Damien Masson
Autodesk Research, Toronto, Ontario, Canada
Jo Vermeulen
Autodesk Research, Toronto, Ontario, Canada
George Fitzmaurice
Autodesk Research, Toronto, Ontario, Canada
Justin Matejka
Autodesk Research, Toronto, Ontario, Canada


会議: CHI 2022

The ACM CHI Conference on Human Factors in Computing Systems (

セッション: Creativity Support

5 件の発表
2022-05-02 23:15:00
2022-05-03 00:30:00