Demotivation and Technological Institute Students EFL Proficiency

1
Demotivation and Technological Institute
Students EFL Proficiency

• Rou-Jui Sophia Hu
• Department of Applied Foreign Languages
• Cheng Shiu University
• snh_at_isu.edu.tw

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OUTLINE

• Introduction
• Literature Review
• Methodology
• Findings
• Conclusion

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INTRODUCTON

• Most technological institute students, in
  general, do not perform as well as university
  students do, either in academic performance or
  EFL proficiency. This paper aims to explore the
  relationship between the demotivating factors and
  technological institute students English
  language proficiency.

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LITERATURE REVIEW

• Not much discussion has been found about the
  relationship between demotivation and English
  proficiency attainment.
• Dornyeis (2001b) definition of demotivation
• the mental and physical condition of an
  individual when the existing motivation is
  lessened or the ongoing action is stopped by some
  external influences.
• ? Chang and Cho (2003) found the following
  factors that are responsible for junior high
  students demotivation (1) learning
  difficulties, (2) threats to self-worth, (3)
  monotonous teaching, (4) bad teacher-students
  relationship, (5) punishments, (6) general and
  language-specific anxiety, (7) lack of
  self-determination, (8) poor classroom management.

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METHODOLOGY

• Subject
• -- 467 students from Cheng Shiu University
  participated in this study.
• Instrument for measuring EFL proficiency
• (GEPT-basic)
• --Grammar reading comprehension Test (20
  multiple choice questions)
• --Listening Comprehension Test (20 multiple
  choice questions)

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METHODOLOGY(cont)

• Instrument for measuring demotivating factors
• --35 statements on 11 hypothetical variables
• (1)learning difficulties,
• (2)threats to self-worth,
• (3)monotonous teaching,
• (4)bad teacher-student relationship,
• (5)punishment,
• (6)general language-specific anxiety,
• (7)lack of self-determination,
• (8)poor classroom management,
• (9) theory not put into practice,
• (10)xenophobia-orientedness,
• (11)negligence of English from previous schools.
  
• ( variables (9), (10), and (11) are from the
  authors investigation.)

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DATA ANALYSIS

• Descriptive Statistics
• Correlational Analysis

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Descriptive Statistics (1)

• Background information

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Descriptive Statistics (2)

• EFL proficiency

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Correlational Analysis (1a)--learning
difficulties vs. EFL measures

• English grammar and vocabulary building are two
  most significant predictor items in relation with
  Grammar Test.
• Vocabulary building and reading comprehension
  have similar correlation coefficients with not
  only Grammar Test but also Listening Test. Thus,
  it can be told that vocabulary building is an
  issue that should be taken note of among
  technological college students.

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Correlational Analysis (1b)--learning
difficulties vs. EFL measures

• Vocabulary building, listening training and
  reading comprehension are three most significant
  predictor items in relation with Listening Test

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Correlational Analysis (2a)--Threats to
self-worth vs. EFL measures

• From the correlation with Grammar Test,
  practicing pronunciation in class is deemed as
  one of the most significant predictor items.

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Correlational Analysis (2b)--Threats to
self-worth vs. EFL measures

• From the correlation with Listening Test,
  practicing pronunciation in class, being looked
  down upon by teachers, and being mocked by
  friends are all related with school, not family
  members. It can be told that students do care
  about how teachers and friends treat them while
  learning. On the other hand, the pressure from
  their families is not as strong as it is from
  school.

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Correlational Analysis (3a)--Monotonous teaching
vs. EFL measures
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Correlational Analysis (3b)--Monotonous teaching
vs. EFL measures
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Correlational Analysis (4)--Bad teacher-student
relationship vs. EFL measures
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Correlational Analysis (5)--Punishment vs. EFL
measures
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Correlational Analysis (6)--General and
language-specific anxiety vs. EFL measures

• Being asked to speak a foreign language in the
  class is usually the source of anxiety for EFL
  learners. The anxiety of training speaking skill
  is reflected not only in Listening Test but also
  in Grammar Test.

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Correlational Analysis (7)--lack of
self-determination vs. EFL measures
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Correlational Analysis (8)--Poor classroom
management vs. EFL measures

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Correlational Analysis (9)--Theory not put into
practice vs. EFL measures

• The so-called pragmatic English or every-day
  English, agreed by most EFL learners, equals
  effective listening speaking skills training,
  not grammar translation.

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Correlational Analysis (10)--Xenophobia-orientedn
ess vs. EFL measures

• Communicating with native speakers of English
  depends primarily on speaking/listening skills.
  Therefore, it is no surprise to find the above
  correlation.

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Correlational Analysis (11)--Negligence of
English from previous schools vs. EFL measures
This correlation shows that there is no doubt
for EFL learners to see speaking/listening skills
as a more important tool for communication than
grammar translation or vocabulary building.
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CONCLUSION

• The item I am bad at memorizing vocabulary is
  found to have the second highest correlation
  coefficient with Grammar Test and the highest
  correlation coefficient with Listening Test at
  .01 level of significance. Therefore, it should
  be noted that vocabulary building is indeed the
  major problem for technological college students
  when encountering learning difficulties.
• The item related with language-specific anxiety
  are found to have the third highest correlation
  coefficient with Grammar Test, and the second
  highest correlation coefficient with Listening
  Test among all items. Anxiety has been a very
  significant factor for ESL/EFL learners. How to
  lessen low achievers learning anxiety is an
  important issue for teachers to face and solve.
• On the other hand, weak correlations are found
  among the items bad teacher-student
  relationship, lack of self-determination, and
  disorder of the classroom, which means these
  items have weak demotivating influence for
  technological college students in this subject.

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RECOMMENDATION FOR FURTHER RESEARCH

• Stepwise Multiple Regression analysis is
  recommended to analyze the relative weighting of
  the eleven hypothesized variables. By applying
  this statistical analysis, we can locate which
  variable(s) explain the most variance when
  entering the regression(s) and, therefore, find
  the rank of the hypothetical variables.