Northwestern Events Calendar


Cognitive Science Colloquia- Speaker: Peter Cheng (Local Host: Steven Franconeri)

When: Friday, November 12, 2021
10:00 AM - 11:30 AM Central

Audience: Faculty/Staff - Student - Post Docs/Docs - Graduate Students

Contact: Bahar Cimic  

Group: Cognitive Science Program

Category: Academic, Lectures & Meetings


 *All Tuesday events are LIVE @4:00pm unless specified otherwise, held in Swift 107*

Peter Cheng (Local Host: Steven Franconeri) 
Website: About Peter Cheng
Date: November 12, 2021, Friday 10:00am, Zoom 

Title:Representing knowledge and thought: insights from the design of radical representational systems

Abstract:As citizens of a technological society ours is a world of representational systems. They substantially determine what we can think, how easily we solve problems and the difficulty of learning.  To maximise the theoretical and empirical leverage available for the study of representations, I design novel notations for conceptually challenging topics (e.g., circuit electricity, probability theory, algebra, logic), novel user-interfaces for information intensive problem-solving (e.g., scheduling, planning), and novel diagrammatic systems for everyday activities (e.g., transit system navigation, dancing).  From the task analytic and experimental contrast of these novel representations with extant conventional representations, various insights have been gleaned.  STEM subjects should be easy to learn.  In representational terms, conventional notations that encode STEM knowledge are typically conceptually incoherent.  In contrast, effective representational systems possess semantic transparency and are syntactically plastic.  Such representations promise a factor of two performance improvement for problem solving and learning.  For the routine engineering of effective representational systems, in addition to the application of cognitive science, I propose (i) a theory that embraces the full conceptual richness of knowledge and (ii) a language to enable the systematic modelling of the full complexity of the concept-encoding functions of representational systems.


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