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IVIPAT: an in-vehicle information processing analysis tool to optimize user interaction flows.
- Source :
-
Cognition, Technology & Work . Jun2024, Vol. 26 Issue 2, p247-265. 19p. - Publication Year :
- 2024
-
Abstract
- This research introduces IVIPAT: an in-vehicle information processing analysis tool. The tool consists of a taxonomy (e.g., filter, search, interpret, monitor, decide) that can be used to carry out a task analysis with focus on information processing. This taxonomy is combined with a subjective mental demand rating scale to identify the intensity of each information processing step. The taxonomy is evaluated and revised based on the feedback of N = 15 practitioners in Study 1 and then applied by a second sample of N = 15 practitioners in Study 2. Results illustrate the added value of the tool: through the rating, user interaction flow variants with differences regarding the mental demand can be identified. In this case, text input via rotary knob was rated as significantly more demanding than text input via handwriting (p <.01, df = 14) or keyboard (p <.05, df = 14). When analyzing information processing during the three user interaction flows, the analysts assigned a total of 359 mental operators with the help of the taxonomy. Results show that the increased load while using the rotary knob could be explained by the necessary interpretation of the direction of rotation, the tracking of the visual highlight during rotation and the overall increased number of information processing steps during interaction. Overall, the focus on information processing and applicability for practitioners distinguish the presented approach from previous ones, like keystroke-level models and cognitive architectures. To facilitate the application, survey materials and analysis examples are included. [ABSTRACT FROM AUTHOR]
- Subjects :
- *INFORMATION processing
*TASK analysis
*MATERIALS analysis
Subjects
Details
- Language :
- English
- ISSN :
- 14355558
- Volume :
- 26
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Cognition, Technology & Work
- Publication Type :
- Academic Journal
- Accession number :
- 177371460
- Full Text :
- https://doi.org/10.1007/s10111-024-00752-y