Sign Language Science: Factors Contributing to Natural Learning
- 0.0
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Brief Introduction
This course promotes a better understanding of the factors that may affect how people learn signed language.
Description
In this course, we will look at how multiple, varying factors can account for language-learning patterns. Age, for example, is a key factor that predicts fluency. Another topic of particular importance to signed languages is the mind. Knowing that spoken language primarily activates the left hemisphere, in this course we will explore how signed languages also primarily activate the left hemisphere.
Knowledge
- Distinguish between continuous variation and discrete componentiality in sign innovation
- Define the term "linguistic typology"
- Describe the potential reasons for typological differences within ASL morphology according to observational and neuro-linguistic research on the morphological continuum.
- Stages and milestones in natural sign language acquisition
- Compare sign language pedagogies for L1 and L2 learning
- Identify the characteristic features of grammar that occur in both home sign and mature community sign languages
Learn Data Science Deep Learning, Machine Learning NLP & R
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Learn Data Science, Deep Learning, Machine Learning, Natural Language Processing, R and Python Language with libraries || DATA SCIENCE || What Does a Data Scientist Do?...
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- 4.3
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Including well over 100 hours of content, e-book (EPUB, MOBI, PDF) ,Excel worksheet, & PDF files, this is comprehensive Recently updated with A LOT of added content....
Sign Language Science: Factors Contributing to Natural Change
- 0.0
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This course describes how we use historical data to demonstrate language change. In this course, we will explore how language changes over time....
Sign Language Science: Factors Contributing to Natural Learning
- 0.0
-
![]()
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This course promotes a better understanding of the factors that may affect how people learn signed language. Age, for example, is a key factor that predicts fluency....
