Cognitive analysis for representation change

Stockdill, Aaron, Garcia Garcia, Grecia, Cheng, Peter C H, Raggi, Daniel and Jamnik, Mateja (2022) Cognitive analysis for representation change. HLC 2022 Human-Like Computing Workshop 2022, Windsor, UK, September 28th-30th 2022. Published in: CEUR Workshop Proceedings. 3227 6-10. CEUR Workshop Proceedings ISSN 1613-0073

[img] PDF - Published Version
Available under License Creative Commons Attribution.

Download (499kB)

Abstract

The rep2rep project is developing an AI tool to automatically select an appropriate representation to solve a particular problem for a particular person. A prerequisite of this tool is to understand (i.e., model) how a reader interprets a representation. But interpretations can vary wildly between novices and experts, readers of similar ability, or even the same reader in different tasks. We present a theory and notation (RIST and RISN) for analysing the cognitive features of a representation's interpretation, and introduce a web app to construct RISN models. These models provide information about cognitive properties of representations to guide automated representation selection to support human problem solving.

Item Type: Conference Proceedings
Schools and Departments: School of Engineering and Informatics > Informatics
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 14 Nov 2022 11:15
Last Modified: 07 Dec 2022 09:52
URI: http://sro.sussex.ac.uk/id/eprint/109054

View download statistics for this item

📧 Request an update