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TESL CANADA 2012 CONFERENCE THOMPSON RIVERS UNIVERSITY Applying the Theory of Multiple Intelligences in Teaching Vocabulary to Iranian Beginner EFL Learners PRESENTER: NAJI KHODASHENAS Oct- 2012 [email protected] [email protected] In the name of the most intelligent

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Page 1: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

TESL CANADA 2012 CONFERENCETHOMPSON RIVERS UNIVERSITY

Applying the Theory of Multiple Intelligences in Teaching Vocabulary to Iranian Beginner

EFL Learners

PRESENTER: NAJI KHODASHENASOct- 2012

[email protected]

[email protected]

In the name of the most intelligent

Page 2: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

Naji Khodashenas Firouzabadi

7 7 77

Married , 1 little boy

BA: Mining engineering – Exploration

MA: TEFL

MBA and Post MBA

Finishing DBA

Life guard in swimming pools and open water diver (PADI)

Love : Learning and Teaching

Presenter Biography

Page 3: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

IS THERE ANY QUESTION

BEFORE

I START?

Page 4: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

First Part : Introduction of the MI theory

Second Part : The applying of this theory in TEFL

What we will discuss…

Page 5: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

INTRODUCTION

Alfred Binet’s view toward intelligenece

Individual Differences

Howard Gardner’s view toward

intelligenece

Page 6: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

A prize! for who knows ….

Page 7: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

Rembrandt van Rijn -

Netherland (1606 - 1669)

Michelangelo di Lodovico

Buonarroti S

imoni - Italy

(1475 – 1564)

Pablo Picasso - Spain

(1881-1973)

Leopold Mozart -

Italy (1719–1787)

Ludwig van Beethoven –

Germany (1770-1827)

Franz Joseph Haydn –

Austria (1732-1809)

nima
Germany,Spain, Italy,Austria
Page 8: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

Gardner’s Theory of Multiple Intelligences (1983)

Page 9: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

. . .Multiple Intelligences

Page 10: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

Definition of Key termsIntelligence : Intelligence is defined as "the capacity to solve

problems or to fashion products that are valued in one or more cultural setting.” (Hatch & Gardner, 1989, p85, cited in Armstrong, 2000)

MDI : More dominant intelligence of each learner, based on the MIDAS test

Musical type learners : The learners with more dominant intelligence in music, as determined by the MIDAS test results

Pictorial type learners: The learners with more dominant intelligence in pictures, as determined by the MIDAS test results

Page 11: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

. . . Multiple Intelligences

Page 12: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

Perceiving the world visually

Preferred way of communication is

through out the pictures and photos

Preferred jobs: interior decorator, architect,

artist, painter

Pictorial Memory

1. Spatial intelligence (Pictorial Int.)

Page 13: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

2 .Linguistic intelligence

The capacity to use words

effectively, whether

orally or in written form

Influential auditors

Lawyer, reporter, Novelist

Page 14: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

The capacity to use numbers

effectively

Mathematician, tax accountant, or

statistician

Well Reasoning ability

Scientist, computer programmer, or

logician

3 .LOGICAL-MATHEMATICAL INTELLIGENCE

Page 15: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

4 .Bodily-Kinesthetic intelligence

Expertise in using one's whole body

to express ideas and feelings

Actor, Dancer, Athlete

Craftsperson, a sculpture,

mechanic

Page 16: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

The capacity to perceive and work with

musical aspects

Musicians, Composer

Musical memory

5 .Musical intelligence

Page 17: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

6 .Interpersonal intelligence

Understanding other people’s mood

Making effective communications

Conveying meaning and concepts to others

The role of this type of intelligence in

successfulness of teachers …

Public relations , Negotiators, Sellers, teachers

( Moafin survey)

Page 18: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

Self awareness

Self Control

A golden key for Poseidon

Archetypes (Emotional

peoples) to become successful

Actors and actresses

7 .Intrapersonal intelligence

Page 19: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

8 .Naturalistic intelligence

Loving the nature

Trees, Animals, Deserts,

Sea, Ocean, Mountain

Feeling and becoming relax at the

nature

Page 20: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

Paradigm Shifting toward IntelligenceNew Paradigm Old Paradigm

The intelligences could be nurtured or neglected

The intelligence could not be measured exactly by scores and would be outperformed in the problem solving procedure only..

The intelligence has different types and different students have different level of each intelligences and consequently different level of efficiency in each area

The intelligence should be measured in real life (Authenticity of the assessment procedure)

Self awareness for both teachers and students would be resulted from recognition of each person potentials

The intelligence was a constant variable for each student.

The intelligence was raveled out just by a score in IQ test.

Limitation in classification for students (Low, Normal and high IQ)

The intelligence was measured unauthentic

Non-effective teaching methods were applied for teaching ( Not in accordance with students MDI)

Page 21: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

METHOD

Participants

Materials

Procedure

Page 22: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

Teaching strategy & the used material for pictorial students …

Page 23: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

RESULTS & DISCUSSION

To check for the homogeneity of the two groups, the subjects were pre-tested through KET.

The descriptive statistics for the two groups are displayed in Table 3.

Table 3: Descriptive statistics of the pre-test (KET)

  

GROUP N MeanStd.

Deviation

Std. Error Mean

PRETEST

KET

Musical 30 11.96 2.47028 .45101

Spatial 30 10.80 2.63138 .48042

Page 24: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

It might be claimed that the groups are homogeneous in terms of their language proficiency prior to the administration of the treatment to the groups.

The mean scores for both groups were 11.96 and 10.80, respectively. An independent t-test was run to compare the mean scores of the groups on the pre-test. As displayed in Table 4 below, the t-observed value is 1.77, lower than the critical value of t at 58 degrees of freedom.

 

 Critical

tObserved t Df

Sig. (2-tailed)

KET

Test

2 1.77 58 .082

Table 4: Independent t-test of the pre-test (KET)

Page 25: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

The homogeneity of the two groups were tested through a validated vocabulary test.

An independent t-test was run to compare the mean scores of the groups on the pre-test. As displayed in Table 5, the t-observed value was 125. This amount of t-value at 58 degrees of freedom was lower than the critical value of t. The descriptive statistics for the two groups are displayed in Table 5.

Table 5: Descriptive Statistics of the Pre-test (Vocab.)

  

GROUP N Mean

Std. Deviat

ion

Std. Error Mean

PRETEST

Vocab.

Musical 30 6.43 2.20 .40

Spatial 30 6.36 1.90 .34

Page 26: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

.…

Thus, it could be claimed that the groups were homogeneous in terms of

their vocabulary ability prior to the administration of the treatment to the

groups. The mean scores for both groups were 6.43 and 6.36, respectively.

Since there were two independent experimental groups with relevant posttest

scores, two-way ANOVA repeated measure was applied to analyze the results.

The descriptive statistics for the two groups are displayed in Tables 7 and 8.

 Critical t Observed t df Sig. (2-tailed)

Vocabulary test2 .125 58 .901

Table 6: Independent t-test of the pre-test

Page 27: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

Table 7: Descriptive statistics of the groups

Table 7: Descriptive statistics of groups Descriptive Statistics (FinalData.sta)Level ofFactor

N Musical ScoresMean

Musical ScoresStd.Dev.

Musical ScoresStd.Err

Pictorial ScoresMean

Pictorial ScoresStd.Dev.

Pictorial ScoresStd.Err

60 10.64 3.01 0.39 10.11 3.57 0.46Pictorial 30 9.25 3.03 0.55 12.26 2.83 0.52Musical 30 12.02 2.30 0.42 7.96 2.89 0.53

Page 28: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

Table 8: Two way ANOVA repeated measure

Table 8: Two way ANOVA repeated measure

Repeated Measures Analysis of Variance (FinalData.sta)Sigma-restricted parameterizationEffective hypothesis decomposition

EffectSSDegr. of

FreedomMS F p

InterceptGroupsErrorSTRATEGYSTRATEGY*GroupsError

12908.58112908.581224.020.0017.71 1 17.711.680.20611.6758 10.558.37 1 8.371.720.19

374.531 374.5377.060.00281.9158 4.86

Page 29: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

The comparisons between posttest scores were done through Post Hoc analysis. The results are reported in Table 9.

Table 9: Post Hoc tests results

Tukey HSD test; variable DV_1 (FinalData.sta)Approximate Probabilities for Post Hoc TestsError: Between; Within; Pooled MS = 7.7033, df = 102.10

Cell No.GroupsSTRATEGY{1}

9.2533{2}

12.258{3}

12.018{4}

7.95671234

PictorialMusical Scores0.000.010.27PictorialPictorial Scores0.00 0.990.00MusicalMusical Scores0.010.99 0.00MusicalPictorial Scores0.270.000.00

Page 30: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

Graphical showing the result of the Post Hoc test

V ertic a l bars denote 0.95 c onf idenc e interv als

S t ra tegy ,Mus ic a l Sc ores S t ra tegy ,P ic toria l S c ores

Pic tor ia l Mus ic al

Groups

6

7

8

9

10

11

12

13

14

Mean

Figure 1: Vocabulary knowledge improvement of both groups

Page 31: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

The obtained results and Post Hoc results reveal that:

1. No statistically significant difference on vocabulary knowledge improvement between pictorial learners that had been taught through musical strategies and musical learners that received pictorial strategies

2. No statistically significant difference on vocabulary knowledge improvement of learners between applying pictorial strategies and musical strategies

3. Statistically significant difference between using teaching strategies in accordance with learners’ MDI and teaching strategies not in accordance with learners’ MDI

Page 32: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

Important points about MI model and the observations

1. We all have all however may be one/some is/are more dominant.

2. The intelligences could be nurtured / neglected.

3. It was seen that some pictorial students can not draw however their MDI is

pictorial. (WHY?)

4. The pictorial students draw nouns better than verbs.

5. The art of the teacher (as a learning facilitator) is having a full understanding

of this theory and being aware of her/his students differences and

consequently using a variety of teaching strategies/materials to fulfill and

guarantee that all students will take benefit and enjoy from teaching

materials.

Page 33: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

CONCLUSION

1. Becoming aware of learners’ individual differences leads to applying

various teachng strategies

2. Understanding more easily why learners perform differently within

a unique class with the same applied strategy

3. Designing the appropriate curriculum and come up with an effective

syllabus design based on various intelligences exist among learners.

4. Being aware of each person competency in general and each learner

competency in particular, helping to understand and focus on

competencies and positive potentials consciously

Page 34: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

Rembrandt van Rijn -

Netherland (1606 - 1669)

Michelangelo di Lodovico

Buonarroti S

imoni - Italy

(1475 – 1564)

Pablo Picasso - Spain

(1881-1973)

Leopold Mozart -

Italy (1719–1787)

Ludwig van Beethoven –

Germany (1770-1827)

Franz Joseph Haydn –

Austria (1732-1809)

Page 35: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

LAST WORDS . . .PAY ATTENTION TO THE COMPETENCIES

Do not hide your talents For use they are made …

Its not matter how much are you smart IT’S MATTER

HOW YOU ARE SMART…

Instead of focusing on weaknesses focus on

strength points and develop them among you and your students

Page 36: Naji Khodashenas Firouzabadi  7 7 77  Married, 1 little boy  BA: Mining engineering – Exploration  MA: TEFL  MBA and Post MBA  Finishing DBA

Thanks for your attention and patient ….Dedicated to Dr. Hasan Karimi (RP)