Using a Cognitive Analysis Grid to Inform Information Systems Design
Laurence Dumont (),
Gabrielle Chénier-Leduc (),
Élaine Guise (),
Ana Ortiz Guinea (),
Sylvain Sénécal () and
Pierre-Majorique Léger ()
Additional contact information
Laurence Dumont: Tech3Lab, HEC Montréal
Gabrielle Chénier-Leduc: Tech3Lab, HEC Montréal
Élaine Guise: Université de Montréal
Ana Ortiz Guinea: Tech3Lab, HEC Montréal
Sylvain Sénécal: Tech3Lab, HEC Montréal
Pierre-Majorique Léger: Tech3Lab, HEC Montréal
A chapter in Information Systems and Neuroscience, 2015, pp 193-199 from Springer
Abstract:
Abstract Following our first conceptualization of a cognitive analysis grid (CA grid) for IS research in 2014, the CA grid was improved and tested in a proof of concept manner. The theory and application of this method are briefly explained, along with lessons learned from a first experiment. The next steps in the validation of this method include applying it to a wider group of naïve participants. This will allow to draw statistical parallels between the cognitive demand of the interface and the performance of the users based on their cognitive profile. Ultimately, this technique should be useful both in NeuroIS research and user experience (UX) tests to guide hypotheses and explain user’s performance.
Keywords: Cognitive psychology; UX; Cognitive demand; Pupil; Workload (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-319-18702-0_26
Ordering information: This item can be ordered from
http://www.springer.com/9783319187020
DOI: 10.1007/978-3-319-18702-0_26
Access Statistics for this chapter
More chapters in Lecture Notes in Information Systems and Organization from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().