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University of Pedagogy

University of Pedagogy. Department of English. Instructor: Mr. Khương. Contribution for language teaching. Contrastive. Analasys. Group 2. C.A in Pedagogy. Prediction. Traditional Applications. Scales of Difficulty. Diagnosis of Error. Prediction. Things C.A can predict:.

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University of Pedagogy

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  1. University of Pedagogy Department of English Instructor: Mr. Khương Contribution for language teaching Contrastive Analasys Group 2

  2. C.A in Pedagogy Prediction Traditional Applications Scales of Difficulty Diagnosis of Error

  3. Prediction Things C.A can predict: • What aspect can cause problems. • Difficulty • Error • thetenacityof certain errors.

  4. Prediction Predict of Error The existence of error The form of error

  5. Prediction • C.A can predict a limitation on the number of error • Interlingual errors: result of L1 interference • Ex: He usually go to school late. • Intralingual errors: effect of L2 asymmetries • Ex: She has a hat beautiful.

  6. Scales of Difficulty Based on: • The notions of positive and negativetransfer potential • Conditions for transfers assumed to be statablein terms of the relations between rules of L1 and L2.

  7. Scales of Difficulty inter-lingual rule relationships: • L1 has rule and L2 has equivalent. • L1 has rule but L2 has no equivalent. • L2 has rule but L1 has no equivalent.

  8. Scales of Difficulty Identify types of choices: 3 types • Optional (Op): the possible selection amongphonemes • Obligatory (Ob): phonological choice involving little freedom • Zero (Ø): the absence in one of the language while it is available in the other

  9. Scales of Difficulty Different availabilities of choice allow eight kinds of relationship between L1 & L2 eight-point hierarchy of difficulty

  10. Scales of Difficulty Order of difficulty Comparison of Choice Type Most L1 L2 1 ……… Ø Ob 2 ……… Ø Op 3 ……… Op Ob 4 ………. Ob Op 5 ………. Ob Ø 6 ………. Op Ø 7 ………. Op Op 8 ………. Ob Ob I II III Least A scale of three order of difficulty by coalescing

  11. Diagnosis of Error Teacher (monitor, assessor) recognize errors organize feedback Student ‘s errors Self-correct Avoiding the same errors

  12. Diagnosis of Error diagnostic functions (tenable) CA Hypothesis predictor errors (not tenable)

  13. Diagnosis of Error • There are some errors related to L1 components. Ex: 1. My class has a good boy, name call Ninja. Ming jiao (Chinese) - name call (English) 2. I very love you. • There are some errors NOT related to L1 components. Ex: A: How are you? B: I’m fine, thanks. And you?

  14. Thanks for ^oo^ Your Time ^oo^

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