richard ng, phd open university malaysia

Richard Ng, PhDOpen University Malaysia

14 - 15, Nov 2011, Kuala Lumpur, Malaysia

Social Media and the Teaching of Mathematics in a Lifelong Learning Environment

Prof. Dr. Latifah Abdol LatifOpen University Malaysia

Overview of Presentation

2. Problem Statement

3. Conceptual Model

4. Research Methodology

5. Findings

6. Conclusion

7. Recommendations

1. Introduction

Email: [email protected]

OPEN UNIVERSITYMALAYSIA

ICLLL2011

1. Introduction:

At OUM courses are offered viaBlended Learning

Minimum F2F, Online Discussionvia MyVLE, and Self-Managed Learning


Email: [email protected] ICLLL2011

Social Media such as Facebook,Blogs, YouTube and Slidesharewere used:

- to supplement learning- to engage learners- to hold informal discussion

2. Problem Statement:

Most learners are working adults

Left school for more than 5 years

Math has always been a difficultsubject

Difficult to do online discussiondue to poor support for mathematical symbols

Limited F2F contact hours makeslearning math more difficult

Cause high incompletion rate



OPEN UNIVERSITYMALAYSIA3. Conceptual Model:



OPEN UNIVERSITYMALAYSIA4. Research Methodology:

Cross Sectional study using a 63-item survey

Administered on 100 learners

To measure rate of participation and how it correlates withthe learners’ sense of community, satisfaction, intrinsic motivation and commitment to stay in their programmes


Email: [email protected]

T-Test was carried out to find if there is a statistical differencein the level of learners’ sense of community, satisfaction, intrinsic motivation and commitment to stay between learnerswho have high level of participation rate compared to thosewho have low participation rate

ICLLL2011

4. Research Methodology … (cont…)

5. Findings:

5.1 Demography:



GenderMale Female Total

28 40 68

EthnicityM C I M C I Total

12 9 7 22 15 3 68

Age Group

21 - 30 31 - 40 41 - 50 > 50 Total

21 37 8 2 68

Attend Pre-Tutorial Workshop?

Yes No Total

47 21 68

No. of HoursSpent on FB

& Blog

< 1 hour 1 – 2 hours 2 – 3 hours > 3 hours Total

12 16 31 9 68

5.2 Mean Scores and Standard Deviation of Sense of Community, Satisfaction, Intrinsic Motivation and Commitment to stay:



Mean Std. Deviation

Sense of Community 3.7941 .36849

Satisfaction 3.5897 .33015

Intrinsic Motivation 3.6441 .23269

Commitment To Stay 3.7691 .43888

5.3 Level of participation:



The median point was found to be between 2 to 3 hours per week

5.4 Spearman Correlation:

Sense ofComm

SatisfyIntrinsic

MotivationCommitTo stay

AttendWorkshop

HoursSpent

Attend Workshop

Correlation Coefficient

.686(**) .481(**) .356(**) .440(**) 1.000 .797(**)

Sig. (2-tailed) .000 .000 .003 .000 . .000

Hours spent per

week

Correlation Coefficient

.746(**) .554(**) .418(**) .527(**) .797(**) 1.000

Sig. (2-tailed) .000 .000 .000 .000 .000 .

5.5 Independent Samples T-Test:OPEN UNIVERSITYMALAYSIA


Levene's Test for Equality of

Variancest-test for Equality of Means

F Sig. t dfSig. (2-tailed)

Mean Diff.

Std. Error Diff.

95% Confidence Interval of the

Difference

Lower Upper

SCIEqual variances assumed 5.444 .023 6.768 66 .000 .4757 .07029 .33538 .61605

Equal variances not assumed

7.436 63.343 .000 .4757 .06398 .34788 .60355

SATEqual variances assumed .115 .735 5.076 66 .000 .3529 .06951 .21408 .49164


5.277 64.673 .000 .3529 .06687 .21929 .48642

IMEqual variances assumed 3.900 .052 3.886 66 .000 .2025 .05211 .09845 .30655


3.661 45.400 .001 .2025 .05532 .09111 .31389

CTSEqual variances assumed 1.383 .244 3.769 66 .000 .3725 .09884 .17516 .56984


3.988 65.921 .000 .3725 .09340 .18602 .55898

5.6 Multiple Regression Analysis:



Model R R2 Adjusted R2 Std. Error of the Estimate

1 .801(a) .641 .624 .26906

ModelSum of

Squaresdf Mean Square F Sig.

1

Regression 8.272 3 2.757 38.090 .000(a)

Residual 4.633 64 .072

Total 12.905 67

Model

Unstandardized Coefficients

Standardized Coefficients t Sig.

B Std. Error Beta

1

(Constant) -1.255 .518 -2.425 .018

Sense of Community .328 .122 .276 2.681 .009

Satisfaction .439 .134 .331 3.289 .002

Intrinsic Motivation .604 .204 .320 2.962 .004

6. Conclusions:

Results concurred with Lee and McLoughlin (2010) that with appropriate learning designs and pedagogical strategies, the social networking tool can



Enhance Enrich Extend traditional distance education paradigms and increase connectivity and engagement of learners

Concurred with the findings by Ng (2010) that increased in the level of Engagement of learners will increase their level of - Sense of Community,

- Satisfaction and - Intrinsic Motivation and this has impact on their - Commitment to stay in their programmes

7. Recommendations:

As suggested by Hoffman (2009), social networking tool has both its advantage and problems for usage in teaching and learning

Learners need to be exposed first on how to use social network

Instructors and tutors should capitalised on the emergence of freely available Web 2.0 and open access tools which provide greater ability to customize online learning.



richard ng, phd open university malaysia

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