Identifier

etd-1107102-140122

Degree

Master of Arts (MA)

Department

Psychology

Document Type

Thesis

Abstract

Participants were trained to generate exemplars of an artificial grammar by bubbling-in letters from exemplars (implicit training), observing a diagram of the grammar then reproducing it (explicit training), or tracing the path of exemplars through a diagram of the grammar (synergistic training). Performance was measured using a cued-generate task. It provided a template for an exemplar with two letters filled in. Participants attempted to generate exemplars that fit the template. The computer corrected the exemplar when it matched at least 70% of the letters in a valid string. Results showed that both explicit and synergistic training led to generation of better quality exemplars (closer to 100% match). However, implicit and synergistic training led to generating more exemplars good enough (at least 70% match) to fit into a wide variety of contextual cues. The author concluded that for both quality and generativity of exemplars synergistic training seemed the most beneficial.

Date

2002

Document Availability at the Time of Submission

Release the entire work immediately for access worldwide.

Committee Chair

Robert C. Mathews

Included in

Psychology Commons

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