Purpose
The Representational Systems Lab conducts research on the nature and use of representational system from the perspective of Cognitive Science.
Representational systems are symbolic systems that encode knowledge, for example: diagrams, graphical user interfaces, information visualization, formal notations, maps and natural language. Cognitive Science is the science of how the mind functions by processing information. So, the Lab's research applies theories and methods from Cognitive Science to study how representational systems shape cognition and to create new representational systems and technology to enhance how we think and learn.
Current RepSys Lab research areas
- Knowledge visualizations / representational epistemology:
- Diagrammatic notional systems for problem solving and learning; e.g., logic, mathematics, physics, dance
- Graphical user-interfaces: e.g., planning/scheduling, cyber-security user access control
- Diagrammatic intelligent tutoring systems
- Automatic representation selection for human-like AI system
- Competence assessment by chunk hierarchy evaluation technique (CACHET):
- Competence measurement; e.g., mathematics, programming, natural language
- User-authentication
- Cognition of writing and drawing
- Individual differences and the control of behaviour
- Cognitive science of tactile interaction and graphics:
- Tactile graphics for people with visual impairment
- Reading diagrams and notations by touch
- Graphic design of tactile material
Do you want to know more?
See the diverse research projects we are currently working on as well as our PhD projects.
Meet our lab members and know more about our interests.
See our list of publications and software too.
Or contact our Represenational Systems (RepSys) Lab director, Profesor Peter Cheng:
By post:
Peter Cheng, Professor of Cognitive Science
Department of Informatics,
University of Sussex
Falmer, Brighton,
BN1 9QH, UK
By email or phone:
Email: p (dot) c (dot) h (dot) cheng (at) sussex (dot) ac (dot) uk
Phone direct line: +44 (0)1273 873652
Dept office: +44 (0)1273 678030