Human inference beyond syllogisms : an approach using external graphical representations
- Submitting institution
-
University of Brighton
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 7827258
- Type
- D - Journal article
- DOI
-
10.1007/s10339-018-0877-2
- Title of journal
- Cognitive Processing
- Article number
- -
- First page
- 103
- Volume
- 20
- Issue
- 1
- ISSN
- 1612-4782
- Open access status
- Compliant
- Month of publication
- August
- Year of publication
- 2018
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
3
- Research group(s)
-
-
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Understanding inference, where statements involve multiple quantifiers and unary and binary relations, is an important step in the application of reasoning. This paper is significant because it establishes that topological-spatial representations are more effective for analysing inferences in graphical representations than topological representations alone. Prior to this output, psychology research about reasoning was limited to relatively inexpressive statements involving single quantifiers (syllogisms).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -