university of pedagogy
DESCRIPTION
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:. - PowerPoint PPT PresentationTRANSCRIPT
University of PedagogyDepartment of English
Contribution for
language teaching
Instructor: Mr. Kh ng ươ
Group 2
ContrastiveAnalasy
s
Diagnosis of Error
Scales of Difficulty
Prediction
Traditional Applications
C.A in Pedagogy
Prediction
What aspect can cause problems.
Difficulty
Error
the tenacity of certain errors.
Things C.A can predict:
Prediction
Predict of Error
The existence of error
The form of error
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.
Scales of Difficulty
The notions of positive and negative transfer potential
Conditions for transfers assumed to be statable in terms of the relations between rules of L1 and L2.
Based on:
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.
Scales of Difficulty
Identify types of choices: 3 types Optional (Op): the possible selection
among phonemes
Obligatory (Ob): phonological choice involving little freedom
Zero (Ø): the absence in one of the language while it is available in the other
Scales of Difficulty
Different availabilities of choice allow eight kinds of relationship between L1 & L2
eight-point hierarchy of difficulty
Scales of Difficulty
1 ……… Ø Ob2 ……… Ø Op3 ……… Op Ob4 ………. Ob Op5 ………. Ob Ø6 ………. Op Ø7 ………. Op Op8 ………. Ob Ob
Order of difficulty Comparison of Choice TypeL1 L2Most
Least
I
II
III
A scale of three order of difficulty by coalescing
Diagnosis of Error
Teacher (monitor, assessor)
Student ‘s errors
Avoiding the same errors
recognize errors organize feedback
Self-correct
CA Hypothesis
diagnostic functions (tenable)
predictor errors (not tenable)
Diagnosis of Error
1. My class has a good boy, name call Ninja.Ming jiao (Chinese) - name call (English)
There are some errors NOT related to L1 components.
Diagnosis of Error
There are some errors related to L1 components.
2. I very love you.
Ex:
Ex: A: How are you?B: I’m fine, thanks. And you?
Thanks for ^oo^ Your Time
^oo^