David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Thinking and Reasoning 15 (4):405-430 (2011)
In three experiments we tested hypotheses derived from the goal specificity literature using a real-world physics task. In the balance-scale paradigm participants predict the state of the apparatus based on a configuration of weights at various distances from the fulcrum. Non-specific goals (NSG) have been shown to encourage hypothesis testing, which facilitates rule discovery, whereas specific goals (SG) do not. We showed that this goal specificity effect depends on task difficulty. The NSG strategy led to rule induction among some participants. Among non-discoverers, SG participants were faster and more accurate on difficult problems than NSG participants. The use of misleading exemplars (scale configurations that obscured the rule governing outcomes) led to fixation on inappropriate hypotheses for NSG but not SG participants. When more diagnostic learning exemplars were used, NSG non-discoverers still performed worse than SG participants on difficult problems. SG participants also outperformed NSG participants on a post-test of difficult problems. These findings qualify the generality of goal specificity effects
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
No references found.
Citations of this work BETA
No citations found.
Similar books and articles
Anna Papafragou (2010). Source-Goal Asymmetries in Motion Representation: Implications for Language Production and Comprehension. Cognitive Science 34 (6):1064-1092.
Christian P. Janssen, Duncan P. Brumby, John Dowell, Nick Chater & Andrew Howes (2011). Identifying Optimum Performance Trade-Offs Using a Cognitively Bounded Rational Analysis Model of Discretionary Task Interleaving. Topics in Cognitive Science 3 (1):123-139.
George L. Dunbar (2000). Traces of Reasoning with Pragmatic Schemas. Thinking and Reasoning 6 (2):173 – 181.
Mike Oaksford, Nick Chater & Becki Grainger (1999). Probabilistic Effects in Data Selection. Thinking and Reasoning 5 (3):193 – 243.
K. J. Gilhooly, L. H. Phillips, V. Wynn, R. H. Logie & S. Della Sala (1999). Planning Processes and Age in the Five-Disc Tower of London Task. Thinking and Reasoning 5 (4):339 – 361.
Barbara A. Spellman (1999). Hypothesis Testing: Strategy Selection for Generalising Versus Limiting Hypotheses. Thinking and Reasoning 5 (1):67 – 92.
John A. Dewey, Adriane E. Seiffert & Thomas H. Carr (2010). Taking Credit for Success: The Phenomenology of Control in a Goal-Directed Task. Consciousness and Cognition 19 (1):48-62.
Magda Osman (2008). Observation Can Be as Effective as Action in Problem Solving. Cognitive Science 32 (1):162-183.
Aldo Zanga & Jean-Fran (2004). Implicit Learning in Rule Induction and Problem Solving. Thinking and Reasoning 10 (1):55 – 83.
Added to index2010-07-27
Total downloads2 ( #345,268 of 1,098,836 )
Recent downloads (6 months)0
How can I increase my downloads?