1. Student Demography and Perception & Attitude towards English as predictor of Academic Achievement
By:
Assoc. Prof. Dr. Nagarajah Lee
Prof. Dr. Latifah Abdol Latif
Prof. Ramli Bahroom.

2. Proficiency in English is necessary to reap the full benefit of information explosion.
As a lifelong learning being the pillar, OUM fully recognizes this and as a results made English language as the medium of instruction.
However, the effectiveness of learning much depends on learners, competence in the language where one of the contributing factor is their attitude towards the use of the language in T&L

3. Overview Purpose Research Design, Population & Sample Instrument
Findings
Conclusion & Recommendation

4. Purpose
This paper examines the association between some selected demographic factors, attitude and perception towards English language use in T&L and academic performance among students in an Open and Distance Learning institution.

5. Students’ perception & attitude towards English language
Conceptual Framework
Student Demogrphy
Academic Performance
Students’ perception & attitude towards English language

6. Research Design, Population & Sample
This is a cross sectional survey using self administered questionnaire.
The population for this study are all undergraduate students enrolled with OUM at the point of data collection.
The sample consist of 761 students in various degree program at OUM.

7. INSTRUMENT
Student Attitude Towards the use of English in T&L
Attitude towards English
Instrumental Motivation
Intrinsic Motivation
Learning Instruction
Student Perception on English Language use:
Perceived Ability
Perceived Competency
Respondents are required to rate their perceptions on a five point Likert scale

8. Respondents’ Demography%
Gender
male
328
43.7
female
422
56.3
Age
283
37.2
256
33.6
141
18.5
Above 50 81
10.6
Race
Malay
449
60.9
Chinese
117
15.9
Indian 87
11.8
Other Bumi 73
9.9
Others 11
1.5
Entry Mode
Flexi
412
56.2
Normal
321
43.8

9. Respondent Demography vs CGPA
CGPA Category
Less than
3.00
n= 491(65.8%)
3.00 and
above
n= 255 (34.2%)
Gender
Male
219 (68.4%)
101 (31.6%)
= 1.985
(p = 0.159)
Female
264(63.5%)
152 (36.5%)
Age
Category
205 (73.7%)
73 (26.3%) =
(p = 0.003)
153 (61.0%)
98(39.0%)
90 (64.3%)
50 (35.7%)
Above 50
43 (55.8%)
34 (44.2%)
Race
Malay
313 (70.5%)
131 (29.5%) =
( p = 0.002)
Chinese
47 (41.2%)
67 (58.8%)
Indian
49 (58.3%)
35 ( 41.7%)
Other Bumi
59 (83.1%)
12 (16.9%)
Others
5 (50.0%)
Entry Mode
Flexi
274 (68.0%)
129 (32.0%)
= 2.403
( p = 0.121)
Normal
198 (62.5%)
119 (37.5%)
Age and Ethnicity are significantly associated with students academic performance

10. As for the age category, are higher percentages of students from the age groups years, years and above 50 years obtained a CGPA of 3.00 and above. Students from the age category 20 – 35 years registered the lower percentage for CGPA 3.00 and above.
Greater percentage of Chinese students obtained CGPA of 3.00 and above, followed by ‘others’, Indian and Malay. The lowest percentage for CGPA 3.00 and above was recorded for East Malaysian Bumiputra students

11. Student Perception and attitude towards English vs CGPA
Mean
Std. Deviation
t-value
Perceived Competency
Below 3.00
488
3.9349
-7.369
0.0001
3.00 and above
252
4.5093
.94585
Perceived Ability
487
3.7480
-8.575
4.4135
Attitude towards English
490
3.8433
.67236
-8.926
254
4.3172
.71387
Instrumental Motivation
4.4869
-6.584
5.0301
.93967
Intrinsic Motivation
489
4.6564
-4.896
5.0246
.91897
Learning Instruction
480
3.6760
-8.960
0.001
4.4702
Both the TWO dimensions of students’ perception towards English use in T&L as well as their attitude towards the language (all four dimensions) are significantly associated with students’ academic achievement. Positive perception and attitude towards the use of English in T&L leads to better academic achievement

12. The Logistic Regression Model
Variables in the Equation
Reference group B
S.E.
Wald df
Sig.
exp B
Perceived Competency
0.612
0.182
11.307 1
0.001
1.844
Perceived Ability
0.594
0.194
9.375
0.002
1.811
Attitude
0.469
0.143
10.757
1.598
Instrumental Motivation
0.512
0.171
8.965
0.003
1.669
Intrinsic Motivation
0.666
0.192
12.032
0.000
1.946
Learning Instruction
0.495
0.193
6.578
0.039
1.640
Male
Female
0.319
0.189
2.838
0.092
1.375
Malay
Race 4
A4(1)
0.741
0.268
7.612
0.006
2.097
A4(2)
0.577
0.318
3.283
0.079
1.562
A4(3)
-1.08
0.392
7.606
0.34
A4(4)
0.007
0.76
0.993
1.007
Flexi Entry
Mode of Entry
0.29
2.346
0.126
1.337
Age
0.03
0.011
7.014
0.008
1.03
Constant
-5.392
0.782
47.562
0.005
a. Variable(s) entered on step 1: Perceived Competency, Perceived Ability, Attitude, Instrumental Motivation, Intrinsic Motivation, Learning_ Instruction, Gender, Race, Mode of Entry, Age.

13. Hosmer and Lemeshow Test
Model Fit
Hosmer and Lemeshow Test
Step
Chi-square df
Sig. 1
17.432 9
.127
Model Summary
Step
-2 Log likelihood
Cox & Snell R Square
Nagelkerke R Square 1 a
.191
.254
a. Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.
The Logistic Regression is a valid model to predict the relationship
between the predictor and outcome variables

14. Model Sensitivity & Specificity
Area Under the Curve
Test Result Variable(s):Predicted probability
Area
Std. Errora
Asymptotic Sig.b
Asymptotic 95% Confidence Interval
Lower Bound
Upper Bound
.740
.021
.000
.698
.781
The test result variable(s): Predicted probability has at least one tie between the positive actual state group and the negative actual state group. Statistics may be biased.
a. Under the nonparametric assumption
b. Null hypothesis: true area = 0.5
Sensitivity [ability to predict event correctly] = 83%
Specificity [ability to predict non event correctly] = 87.7%

15. Logistic Model Explaining the relationships
CGPA 3.00 and above = (Learning Instruction) +
(Int. Mot. ) ( Instr. Mot.) +
0.512 (Attitude) (Perceived Ability) +
0.612 (Perceived competency ) (Age) +
0.741 (Chinese) – 1.08 (Other Bumi)
Int. Mot = Intrinsic Motivation
Instr. Mot = Instrumental Motivation

16. Conclusion
The findings of this study suggested that students’ perception and attitude towards the use of English in Teaching and Learning together with the selected demographic factors can be used as a good predictor of students’ academic performance.
These variables can be used to identify ‘at risk’ students and the institution can formula interventions to reduce attrition rate.

17. Questions and comments are welcome
Thank You
Questions and comments are welcome