Open AccessPROBABILITY‐BASED INFERENCE IN A DOMAIN OF PROPORTIONAL REASONING TASKS
Author(s) -
Béland Anne,
Mislevy Robert J.
Publication year - 1992
Publication title -
ets research report series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.235
H-Index - 5
ISSN - 2330-8516
DOI - 10.1002/j.2333-8504.1992.tb01447.x
Subject(s) - inference , cognition , perspective (graphical) , computer science , context (archaeology) , domain (mathematical analysis) , imperfect , artificial intelligence , observational study , statistical inference , machine learning , cognitive science , cognitive psychology , psychology , mathematics , statistics , paleontology , mathematical analysis , linguistics , philosophy , neuroscience , biology
Educators and psychologists are increasingly interested in modelling the processes and knowledge structures by which people learn and solve problems. Progress has been made in developing cognitive models in several domains, and in devising observational settings that provide clues about subjects' cognition from this perspective. Less attention has been paid to procedures for inference or decision‐making with such information, given that it provides only imperfect information about cognition—in short, test theory for cognitive assessment. This paper describes probability‐based inference in this context, and illustrates its application with an example concerning proportional reasoning.