Color Categorization in Bilingual Populations: Korean-English Bilinguals Prutha S. Deshpande Cognitive Sciences Advisors: Kimberly A. Jameson and Louis Narens Institute for Mathematical Behavioral Sciences Cognitive Sciences I would like to acknowledge the assistance of Helen Haan and Jacey Song in the collection of the Korean Language data. This research was supported by a UROP award to Prutha Deshpande.
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Color Categorization in Bilingual Populations:
Korean-English Bilinguals Prutha S. Deshpande
Cognitive Sciences
Advisors: Kimberly A. Jameson and Louis Narens Institute for Mathematical Behavioral Sciences
Cognitive Sciences
I would like to acknowledge the assistance of Helen Haan and Jacey Song in the collection of the Korean Language data.
This research was supported by a UROP award to Prutha Deshpande.
INTRODUCTION
Linguistic Relativity • Linguistic Relativity Hypothesis
– Influence of language on cognition • Traditional focus on the domain of color
categorization. • Rich history of cross-cultural empirical
research. Linguistic Relativity and Bilingualism: • Is the cognitive processing of non-linguistic
information impacted by bilingualism?
Gap in the Literature • Previous studies have primarily examined the
color cognition of bilinguals in their non-English language modes, in comparison with monolingual speakers of both languages.
• The present study addresses this gap by comparing the color categorization and naming behavior of bilinguals in both of their languages.
Rationale for choosing Korean-English Bilinguals
• The Korean color lexicon has interesting features that differentiate it from the English color lexicon.
• In particular, Korean has two highly salient basic color terms for the region of color space that in English would be described with the single color term “green” (Roberson, Hanley & Pak, 2009).
Choloksayk Yentwusayk
METHODS
Participants • Undergraduate students bilingual in Korean
and English, with varying proficiency in each of the languages.
• The final sample included 25 participants. • Participants scheduled for 2 sessions of 2
hours each. • One of the sessions was conducted in Korean,
while the other was conducted in English.
Assessments • Language Assessment • Color Vision Assessment
Ishihara Pseudoisochromatic
Plates Test
Farnsworth-Munsell 100 Hue
Test
Experimental Tasks 1. Naming
– Asked to name 330 colored chips – Provided confidence judgments
2. Focus Selection – Asked to select the best example or ‘focus’ of
the basic color terms elicited in Task 1. 3. Category Mapping
– For the same basic color terms as Task 2, asked to indicate every color that could be named with ‘X’ color term.
Task 1: Naming
Sample color chips (Lindsey & Brown, 2014)
Color chart approximating the samples used in this study (World Color Survey, Munsell chart)
Task 2: Focus Selection
Color chart approximating the samples used in this study (World Color Survey, Munsell chart)
Example: Indicate the focus of “Red”.
Task 3: Category Mapping
Color chart approximating the samples used in this study (World Color Survey, Munsell chart)
Example: Indicate all the colors that can be named “Red”.
OBJECTIVES
Objectives 1. Examine color category boundaries across
method used, i.e. Naming Method (Task 1) vs. Category Mapping Method (Task 3).
– Within an individual and language condition – To test for consistency in color categorization
2. Examine variations in color categorization across language of testing.
– Special emphasis on the “green” region of color space.
ANALYSES
OBJECTIVE 1
Consistency in Naming (Task 1) and Mapping (Task 3)
0%10%20%30%40%50%60%70%80%90%
100%
1 25
Perc
ent C
onsi
sten
cy
Participants (N=25)
Korean Language Condition
0%10%20%30%40%50%60%70%80%90%
100%
1 25
Perc
ent C
onsi
sten
cy
Participants (N=25)
English Language Condition
(Data sorted in a rank order)
Consistency in Naming (Task 1) and Focus Selection (Task 2)
0%10%20%30%40%50%60%70%80%90%
100%
1 25
Perc
ent C
onsi
sten
cy
Participants (N=25)
Korean Language Condition
0%10%20%30%40%50%60%70%80%90%
100%
1 25
Perc
ent C
onsi
sten
cy
Participants (N=25)
English Language Condition
(Data sorted in a rank order)
Consistency in Focus Selection (Task 2) and Mapping (Task 3)
Conclusions: Objective 1 • Did we observe consistency of color
categorization and naming across the three methods of testing?
Conclusions: Objective 1 • Did we observe consistency of color
categorization and naming across the three methods of testing? – Task 1 and Task 3 (Eng. 68%, Kor. 88%)
Conclusions: Objective 1 • Did we observe consistency of color
categorization and naming across the three methods of testing? – Task 1 and Task 3 (Eng. 68%, Kor. 88%) – Task 1 and Task 2 (Eng. 80%, Kor. 80%)
Conclusions: Objective 1 • Did we observe consistency of color
categorization and naming across the three methods of testing? – Task 1 and Task 3 (Eng. 68%, Kor. 88%) – Task 1 and Task 2 (Eng. 80%, Kor. 80%) – Task 3 and Task 2 (Eng. 92%, Kor. 92%)
Conclusions: Objective 1 • Did we observe consistency of color
categorization and naming across the three methods of testing? – Task 1 and Task 3 (Eng. 68%, Kor. 88%) – Task 1 and Task 2 (Eng. 80%, Kor. 80%) – Task 3 and Task 2 (Eng. 92%, Kor. 92%)
• Future analysis of individual differences in overall consistency based on language fluency.
Conclusions: Objective 2 Focus Selection
• We observed a similarity in the aggregate modal focal choice frequency across the two language modes. – Kendall’s Tau = 0.748
• This implies similar focal selection structure across language modes, but not identical.
Conclusions: Objective 2 Naming Frequency
• The contour plots show highly similar denotative ranges for the naming of green in English and the Korean green Choloksayk.
• The naming of the second Korean green Yentwusayk was not as robust by naming frequency measures.
Conclusions: Objective 2 Mapping Frequency
• The contour plots of mapping frequency for English green and both Korean greens was robust. – In contrast to the naming of the second Korean green.
• This suggests a task dependent asymmetry in color categorization and naming. – Similar to observations in a Vietnamese language study
(Jameson & Alvarado, 2003).
Future Analyses Comparison with two datasets: • Survey of American English (1994) at the George
Washington University. – 31 Monolingual speakers
• Survey of the Korean language (1994) by Dr. Rodney E. Tyson. – 22 Monolingual speakers – 21 Bilingual speakers
(Components of the Mesoamerican/Multinational Color Survey, conducted by Dr. Robert E. MacLaury from 1978 to 1981)
Thank you!
ADDITIONAL DATA
Aggregate Confidence Levels in Naming 1. English Color Naming