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PhD Defense by David Martinez

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Name: David Martinez

School of Psychology Ph.D. Dissertation Defense Meeting

Date: Wednesday, August 15th, 2018

Time: 1:00 pm

Location: J.S. Coon bldg., room 217

 

Advisor:

Jenny Singleton, Ph.D. (Georgia Tech)

 

Dissertation Committee Members:

Susan Embretson, Ph.D. (Georgia Tech)

Randy Engle, Ph.D. (Georgia Tech)

Dan Spieler, Ph.D. (Georgia Tech)

Michael Bunting, Ph.D. (University of Maryland)

 

Title: Sign Learning and its Relationship to Word Learning in Hearing Adults

 

Summary: Between 1990 and 2013, enrollment in American Sign Language (ASL) as a second language in US colleges and universities increased by 6,840%; consequently, in 2013, ASL displaced German as the third most frequently taught second language in US schools of higher education. Despite the dramatic increase in popularity, we know very little about the cognitive processes involved in learning a signed language or how they relate to the processes involved in learning a spoken language.

 

In this study, structural equation modeling was used to 1) extend individual differences research on second language word learning to sign learning in hearing non-signers and 2) to model the relationship between word and sign learning. Two-hundred thirty-six participants completed 25 tasks assessing word learning, sign learning, language modality specific phonological short-term memory, fluid intelligence, crystallized intelligence, and working memory capacity.

 

The results of this study indicated that fluid intelligence was predictive of both word and sign learning, however, after accounting for other variables, phonological short-term memory was only predictive of lexical learning within modality (e.g., short-term memory for signs predicted sign learning but not word learning). A strong correlation was also observed between the sign and word learning factors. Exploratory analyses revealed that all tasks loaded onto a general lexical learning factor but sign learning tasks additionally loaded onto a specific factor. As such, this study provides insight into the cognitive components that are common to lexical learning regardless of language modality and those that are unique to either signed or spoken languages.

 

Status

  • Workflow Status:Published
  • Created By:Tatianna Richardson
  • Created:08/01/2018
  • Modified By:Tatianna Richardson
  • Modified:08/01/2018

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