Explicit Feature Relation and Implicit Feature Correlation Knowledge in Semantic Memory

Existing literature suggests that failures to find influences of statistically-based or theorybased knowledge in learning feature co-occurrences are attributable to incongruence between task type (speeded versus untimed) and knowledge type (statistically-based versus theory-based), though these knowledge types influence congruent tasks (McRae, de Sa & Seidenberg, 1997; Ahn, Marsh, Luhmann & Lee, 2002). I argue that influence of both knowledge types should be found in tasks that directly tap feature co-occurrence knowledge, allowing meaningful contrasts of their influences. Detailed descriptions of causal theories were collected using interviews. Regression analyses using theory statistics and shared variance between features were used to compare the relative influences of the two knowledge types in untimed relatedness ratings and speeded relatedness decisions for 65 feature pairs that span a range of correlational strength. Both knowledge types influenced both tasks. It is concluded that both implicitly and explicitly correlated feature pairs influence conceptual computations.

Name thesis:degree_name

Master of Arts

Discipline thesis:degree_discipline

Psychology

Grantor dc:publisher

The University of Western Ontario

Year dc:date.issued

2004

Author dc:creator

• McNorgan, Christopher P.

Advisor dc:contributor.advisor

• McRae, Ken

• correlated features
• causal theories
• speeded tasks
• untimed tasks
• knowledge types.

Language dc:language.iso

en

Handle dc:identifier.uri

https://hdl.handle.net/20.500.14721/39063

OAI identifier oai:identifier

oai:uwo.scholaris.ca:20.500.14721/39063