Thiyagu viva voce prsesentation

EFFECTIVENESS OF E-LEARNING MODULES IN

TEACHING MATHEMATICS AT THE SECONDARY

TEACHER EDUCATION LEVEL

Public Viva Voce Examination30.06.2014

EFFECTIVENESS OF E-LEARNING MODULES IN

TEACHING MATHEMATICS AT THE SECONDARY

TEACHER EDUCATION LEVEL

NEED FOR THE STUDY

NEED FOR THE STUDY

REVIEW OF RELATED LITERATURE

Total Studies

(81 Studies)

E-learning

Indian

(23 Studies)

Foreign

(23 Studies)

Math

Achievement

Indian &

Foreign

(15 Studies)

Attitude

Indian &

Foreign

(20 Studies)

OPERATIONAL KEY TERMS

Effectiveness

e-Learning Modules

Mathematics

Secondary Teacher Education Level

OBJECTIVES OF THE STUDY

OBJECTIVES …..

Develop E-learning modules

OBJECTIVES …..

To find out EffectivenessE-learning Modules

OBJECTIVES …..

To study the Influence

Methods of teaching Demographic variable

And their interaction of achievement scores

To find out the Relationship

Math Achievement Math Attitude

Perception towards e-learning

OBJECTIVES …..

HYPOTHESES OF THE STUDY

NO SIGNIFICANT DIFFERENCE

Control Group

Experimental Group

Pre-test

Whole Test

Lesson wise

Objective wise

NO SIGNIFICANT DIFFERENCE

Control Group

Experimental Group

Post-test

Whole Test

Lesson wise

Objective wise

NO SIGNIFICANT DIFFERENCE

Pre-test Post-test

Control Group

Whole Test

Lesson wise

Objective wise

NO SIGNIFICANT DIFFERENCE

Pre-test Post-test

Experimental Group

Whole Test

Lesson wise

Objective wise

NO SIGNIFICANT DIFFERENCES

Post-Test Experimental

GroupGender

Age

Level of Graduation

Locale

Type of Stay & Computer

Literacy

Control Group

Experimental Group

Attitude Towards Math

Before the Treatment

After the Treatment

NO SIGNIFICANT DIFFERENCE

Control Group

Experimental Group

Gain Ratio

NO SIGNIFICANT DIFFERENCE

PERCEPTION TOWARDS E-LEARNING

Experimental Group

PTEL

Before the Treatment

After the Treatment

THERE IS NO SIGNIFICANT RELATIONSHIP

Achievement

Test

Attitude

towards Math

Perception

towards e-learning

INFLUENCE

NO SIGNIFICANT INFLUENCE

Methods of teaching Demographic variable

And their interaction of achievement scores in Math

NO SIGNIFICANT DIFFERENCE

Control Experiment

Adjusted mean scores of achievement test

By considering pre test score as covariate

REGRESSION

Demographic variables

Prediction of Post test

VARIABLES OF THE STUDY

S.NO VARIABLES DESCRIPTION

1 Independent Variables Teaching Methods -e-learning modules & Conventional Method

2 Dependent Variable Achievement test in Mathematics. (Pre and post test)

3 Demographic Variables Gender, Age, Level of Graduation, Locale, Type of Stay and Computer

Literacy

4 Intervening Variables Attitude towards Mathematics and Perception towards e-learning

METHODOLOGY

METHOD

PRE TEST - POST TEST TWO EQUIVALENT GROUPS EXPERIMENTAL DESIGN

SAMPLE

Sample MathematicsTeacher Trainees

Sampling Techniques Random Sampling

Total Sample Size 68

Control Group 34 - Sivanthi College of Education

Experimental Group 34- Dr. Sivanthi College of Education

Tools

TOOLS USEDTOOLS DEVELOPERS DESCRIPTIONS

e-learning modules Investigator 3 Units (Story Board)

Achievement Test in Math(Pre and Post Test)

Investigator & Supervisor It has 65 items. {30 (5,16,9)/20 (9,6,5)/15 (4,8,3)}

Intelligent Test – Test of “g”: Culture Fair – Scale 2,

(Form A)

R.B.Cattell and A.K.S.Cattell It consists of four sub tests. They are series (12), classification (14), matrices (12) and conditions (8). It has 46 items.

Attitude towards Mathematics Inventory

(ATMI)

Martha Tapia and George Marsh (1996)

It has 40 items in Likert Scaleformat. Out of the 40 items 29were positive and 11 werenegative.

Perception towards e-learning Rajeshkumar and Krishnakumar (2008)

It has 20 items in Likert Scaleformat. Out of the 20 items 14were positive and 6 werenegative.

DATA ANALYSIS

DATA ANALYSIS

ANALYSIS CALCULATIONS

Descriptive Analysis Mean & SD

Differential Analyses ‘t’ test

Interaction effect and influence Two way ANOVA & ANCOVA

Relationship Pearson Product Moment Coefficient Correlation

Significant predictors Simple Linear Regression Analysis.

QUANTITATIVE ANALYSIS

QUALITATIVE ANALYSIS

Analysis Techniques

Case Study Interview

Quantitative Analysis

‘t’ tests - Differential Analysis Reveals

MAJOR FINDINGS OF THE STUDY

PRETEST

S.NO GROUP TEST RESULTS

1 Control Vs Experimental

WholePretest

Not Significant

2 Control Vs Experimental

Lesson wise Pretest

Not Significant

3 Control Vs Experimental

Learning Objectivewised Pretest

Not Significant

CalculationGraph

POST TEST

S.NO GROUP TEST RESULTS HIGHER LEVEL

1 Control Vs Experimental

WholePost test

Significant Experimental

2 Control Vs Experimental

Lesson wise Post test

Significant Experimental

3 Control Vs Experimental

Learning Objective wised

Post test

Significant Experimental

CalculationGraph

CONTROL GROUP

S.NO TEST GROUP RESULTS HIGHER LEVEL

1 Whole Pretest Vs Posttest

Control Group Significant Post test

2 Lesson wisePretest Vs Posttest

Control Group Significant Post test

3 Learning objective wised

Pretest Vs Posttest

Control Group Significant Post test

CalculationGraph

EXPERIMENTAL GROUP

S.NO TEST GROUP RESULTS HIGHER LEVEL

1 Whole Pretest Vs Posttest

ExperimentalGroup

Significant Post test

2 Lesson wisePretest Vs Posttest

ExperimentalGroup

Significant Post test

3 Learning objective wised

Pretest Vs Posttest

ExperimentalGroup

Significant Post test

CalculationGraph

The Mean, SD and ‘t’ value of Total Mean scores of Experimental Group

Calculation

Variables Groups N Mean SD ‘t’ value P

GenderMale 10 50.00 3.05

0.088 N.SFemale 24 50.12 4.01

AgeBelow 23 20 50.10 2.77

0.022 N.SAbove 23 14 50.07 4.87

Level of Graduation

UG 22 50.36 2.830.580 N.S

PG 12 49.58 5.05

LocaleRural 23 50.43 3.44

0.782 N.SUrban 11 49.36 4.29

Type of StayDay Scholar 21 50.19 3.73

0.201 N.SHosteller 13 49.92 3.81

Computer Literacy

Yes 12 50.00 3.350.185 N.S

No 22 50.25 4.45

ATTITUDE TOWARDS MATHEMATICS

S.NO GROUP TREATEMENT RESULTS HIGHER LEVEL

1 Control Vs Experimental

Before treatment Not Significant

-

2 Control Vs Experimental

After treatment Significant Experimental group

CalculationGraph

PERCEPTION TOWARDS E-LEARNING

S.NO TREATEMENT TREATEMENT RESULTS HIGHER LEVEL

1 BEFORE VSAFTER

EXPERIMENTALGROUP

SIGNIFICANT AFTER TREATEMENT

CalculationGraph

GAIN RATIO

Variable Group N Mean SD ‘t’ P

Gain Ratio Experimental 34 1.03 0.23

6.78

Significant

P < 0.01 Control 34 0.71 0.16

CalculationGraph

ANOVA & ANCOVAREVEALS

All other demographic variables and their interactions are not have significant interaction effect in the post test scores except the

methods of teaching

SourceSum of Squares

dfMean

SquareF Sig.

Partial Eta Square

Corrected Model 3831.00 7 547.28 31.84 0.000 0.78

Intercept 2771.60 1 2771.60 161.28 0.000 0.72

Gender 81.72 1 81.72 2.75 0.13 0.07

Age 24.87 1 14.87 1.44 0.23 0.02

Graduation Level 11.73 1 11.73 0.68 0.41 0.01

Locale 26.79 1 26.79 1.55 0.21 0.02

Type of Stay 18.31 1 18.31 1.06 0.30 0.01

Computer Literacy 0.00 1 0.00 0.00 0.98 0.00

Method of Teaching 3694.76 1 3694.76 214.99 0.00 0.78

Error 1031.11 60 17.18

Total 128880.00 68

Corrected Total 4862.11 67

The adjusted means scores of post test scores of control and experimental group are not significantly differ when

considering pre test scores as covariate.

Source Sum of Squares

df Mean Square

F Sig. Partial Eta Square

Corrected Model

3738.28 2 1869.14 108.10 0.000 0.769

Intercept 2847.93 1 2847.93 164.71 0.000 0.717

Pre Test Score

32.341 1 32.34 1.87 0.17 0.02

Treatment 3484.26 1 3484.26 201.52 0.000 0.769

Total 128880.0 68

Calculation

Regression Analysis Reveals

The demographic variables do not contribute to the prediction of achievement in the post test of Mathematics by B.Ed., Teacher Trainees.

Model Sum of squares

df Mean Square

F Sig.

1

Regression 46.424 6 7.737

0.512 0.794Residual 408.311 27 15.123

Total 454.735 33

Calculation

ModelUnstandardized coefficients

Standardized Coefficients t Sig

B Std. Error Beta

Gender 0.852 1.860 0.106 0.458 0.650

Age 3.482 3.357 0.469 1.038 0.309

Graduation Level -5.897 3.990 -0.771 1.478 0.151

Locale -0.780 1.689 -0.100 0.462 0.648

Type of Stay 0.056 1.424 0.007 0.039 0.969

Computer Literacy 2.403 2.138 0.314 1.124 0.271

Correlation Analysis Reveals

There is significant Relationship between

Achievement

&

Math attitude

Math Attitude

&

Perception towards

e-learning

Perception towards e-

learning

&

Achievement

Calculation

Qualitative Analysis

1 Name S.Vivek (Experimental Group)2 Gender Male3 Religion Hindu4 Level of Graduation UG5 Branch of Study Mathematics6 Age Below 237 Residence in home Rural8 Marital Status Single9 Parents Education School Level

10 Annual Income 1 Lakh11 Post test Score 57/65

Case Study Finding

Step by step learning

Flexible learning

Encouragement

ConfidenceOne-way learning

EDUCATIONAL IMPLICATION

ASSISTING

AUTO INSTRUCTIONAL MATERIAL

INTEREST AND NOVELTY

THEORETICAL AND PRACTICAL KNOWLEDGE

SMALL FRAMES

PRIVACY

EFFECTIVE INSTRUCTION

RECOMMENDATIONS

Recommendations

• Newer instructional technologies using e-learning module can beintroduced.

• Teachers should be trained to produce e-module package at variouslevels.

• In-service training and orientation courses can be provided fordevelopment of e-learning modules.

• New templates e-learning modules other than that templatesdeveloped by UGC-CEC may be evolved.

• Adequate infrastructure for the development of e-learning modulescan be built in all schools and colleges.

• Computer with LCD Projector will be used in all the classes in schoolsand colleges.

Recommendations

• NCERT and SCERT should take of the work ofproviding module as they produce teachers’handbook and different e-learning modules

• Appropriate software such as Adobepremiere editing and Flash and Dreamviewer for the development of animationmay be incorporated in the teachereducation curriculum at secondary level.

• Making students to be independent in theirlearning is one of the predominantresponsibilities of the teacher.

Suggestions for Further Research

• experimental study on e-learning modules can be done for other subjects atvarious levels.

• Interactive e-learning modules in relation to achievement of students on varioussubjects at different levels can be studied.

• Influence of other variables like social economic factors, ICT skills and soft skillsalso can be investigated.

• In-depth study may be undertaken to teach content based e-learning modules.

• Same method can be applied for the other topics in mathematics.

• The sample size may be increased for better generalization of the findings.

• This study was limited only for Mathematics B.Ed., Teacher Trainees. But it may beextended to other optional B.Ed., Teacher Trainees.

List of Articles and Book Published No Title of the Article / BOOK Name of the Journal / *Book Publisher Address

1 M-LEARNING IS THE FUTURE LEARNING EDUTRACKS – VOLUME 8 NO.6. – FEBRUARY 2009. (ISSN: 0972-9844)

Neelkamal Publications Pvt. Ltd. Sultan Bazar, Hyderabad

500 095.

2 ATTITUDE TOWARDS E-LEARNING AMONG THEPOSTGRADUATE ARTS AND SCIENCE STUDENTS

*ISSUES OF INFORMATION COMMUNICATION TECHNOLOGY (ICT) IN EDUCATION.

(First Edition 2009) ISBN:978-81-8457-118-9

Kanishka Publishers, distributors,New Delhi

110 002

3 U-LEARNING:THE NEXT GENERATION OFLEARNING

UNIVERSITY NEWS- VOL.47 NO.41. OCTOBER 12-18,2009(ISSN-0566-2257)

Weekly journal of higher education

Association of Indian Universities, AIU house,

16-Comrade Indrajit Gupta Marg, New Delhi 110002

4 WEB BASED INSTRUCTION IN LEARNINGMATHEMATICAL EDUCATION

* PROFESSIONAL COMPETENCE IN TEACHING(FIRST EDITION 2010)

ISBN:978-93-80375-02-1

Rakhi Prakashan, 4th Floor, Raman Tower, Sanjay Place,

Agra – 282 002.

5 HIGHER SECONDARY STUDENTS’ PERCEPTIONTOWARDS INFORMATION ANDCOMMUNICATION TECHNOLOGY AT THESCHOOL LEVEL

JOURNAL OF EDUCATIONAL RESEARCH & EXTENSIONVOLUME 47(1)

JANUARY-MARCH 2010(ISSN-0973-6190)

Sri Ramakrishna Missions Vidyalaya College of Education, Coimbatore – 641 020

6 ROLE OF ICT IN THE GOVERNANCE OF HIGHEREDUCATION

UNIVERSITY NEWS- VOL.48 NO.48. NOV 29 – DEC 05, 2010.(ISSN-0566-2257)

Weekly journal of higher education

Association of Indian Universities, AIU house,

16-Comrade Indrajit Gupta Marg, New Delhi 110002

7 EFFECTIVENESS OF E-MODULE IN TEACHINGMATHEMATICS

NEW HORIZONS IN EDUCATION, Volume III: No.2. April-Sep 2011.

(ISSN:0975-4008)

Dr.Sivanthi Aditanar college of Education, Tiruchendur – 628215.

8 TECHNOLOGY AND TEACHING-LEARNINGSKILLS” (First Edition - 2011)

KALPAZ Publications(ISBN: 978-81-7835-909-0)

KALPAZ Publications, Gyan Books Pvt.Ltd. Gyan Kunj, 23, Main Ansari Road, Darya Ganji, New

Delhi.

9 UBIQUITOUS LEARNING (U-LEARNING) AWARENESS AMONG THE TUTICORIN DISTRICT B.ED., TRAINEES

JOURNAL ON SCHOOL EDUCATIONAL TECHNOLOGY,Vol.6. No.4.

MARCH-MAY 2011(ISSN:0973-2217)

i-manager Publications, 3/343, Hill View, Town Railway Nagar, Nagercoil, Kanyakumari Dist. 629

001.

10 3G MOBILE TECHNOLOIGES IN EDUCATION: THECASE OF FUTURE LEARNING

UNIVERSITY NEWS- VOL.48 NO.49. NOV 40 – OCT 03-09, 2011.

(ISSN-0566-2257)Weekly journal of higher education

Association of Indian Universities, AIU house,

16-Comrade Indrajit Gupta Marg, New Delhi 110002