Abstract
Implicit Statistical Learning (ISL) studies how exposing individuals
to repeated statistical patterns can help develop skills in the absence
of conscious awareness, such as learning a language or detecting
familiar shapes. This paper transposes ISL in the context of menu
design learnability. Our analysis of menu patterns in various applications from the 80s to today reveals a consistent linear pattern
with command names on the left and keyboard shortcut cues aligned
on the right. We then develop a design space of menu patterns by
manipulating two factors of ISL theory, spatial proximity (distance)
and relative positioning between commands and shortcut cues. We
empirically compare four menu patterns of this design space on
whether they can improve keyboard shortcut adoption through two
controlled experiments. Results did not capture clear effects among
the menu patterns, suggesting that ISL in the context of HCI might
involve more complex factors than initially anticipated, such as the
time the users are exposed to the menu pattern. We reflect on the
challenges in applying theories from cognitive science to HCI and
hope that our systematic methodology and experiment designs will
serve as a basis for encouraging more studies in the area.
to repeated statistical patterns can help develop skills in the absence
of conscious awareness, such as learning a language or detecting
familiar shapes. This paper transposes ISL in the context of menu
design learnability. Our analysis of menu patterns in various applications from the 80s to today reveals a consistent linear pattern
with command names on the left and keyboard shortcut cues aligned
on the right. We then develop a design space of menu patterns by
manipulating two factors of ISL theory, spatial proximity (distance)
and relative positioning between commands and shortcut cues. We
empirically compare four menu patterns of this design space on
whether they can improve keyboard shortcut adoption through two
controlled experiments. Results did not capture clear effects among
the menu patterns, suggesting that ISL in the context of HCI might
involve more complex factors than initially anticipated, such as the
time the users are exposed to the menu pattern. We reflect on the
challenges in applying theories from cognitive science to HCI and
hope that our systematic methodology and experiment designs will
serve as a basis for encouraging more studies in the area.
Original language | English |
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Title of host publication | AVI 2022: Proceedings of the 2022 International Conference on Advanced Visual Interfaces |
Publisher | Association for Computing Machinery |
Pages | 1-9 |
Number of pages | 9 |
ISBN (Print) | 978-1-4503-9719-3 |
DOIs | |
Publication status | Published - 6 Jun 2022 |
Bibliographical note
Publisher Copyright:© 2022 ACM.
Keywords
- Implicit Statistical Learning
- spatial relationships
- GUI
- menu