title: Experience and problem representation in statistics.
abstract: This research investigated experience level differences in problem representation in statistics. A triad judgment task was designed so that source problems shared either surface similarity (story narrative) or structural (inferential level) features (t test, correlation, or chi-square) with the target problem. Graduate students with varying levels of experience in statistics were asked to choose which source problem "goes best" with the target problem for each triad. Given a choice between a problem that shares surface-level characteristics and one that shares inferential-level characteristics, students who had taken 0 to 4 courses in statistics tended to represent problems on the basis of surface-level features. Students who had more than 4 courses did not consistently make choices on the basis of surface-level features, nor did they consistently rely on structural features. However, all students with statistics course backgrounds noticed structural features when competition between different types of features was eliminated. The role of surface and structural features in determining problem representations is discussed.
authors.affiliation: Fordham University, Graduate School of Education, New York, NY 10023, USA. mrabinowitz@fordham.edu
authors.forename: Mitchell
authors.initials: M
authors.lastname: Rabinowitz
authors.forename: Tracy M
authors.initials: TM
authors.lastname: Hogan
mesh_terms: D002755:Choice Behavior; D003071:Cognition; D003657:Decision Making; D004522:Educational Status; D006801:Humans; D007600:Judgment; D011340:Problem Solving; D012107:Research Design; D013223:Statistics as Topic / Q000193:education / Q000379:methods*; D013334:Students / Q000523:psychology; D013647:Task Performance and Analysis; D013663:Teaching; D014829:Vocational Education