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EFFECTIVENESS OF E-LEARNING MODULES IN
TEACHING MATHEMATICS AT THE SECONDARY
TEACHER EDUCATION LEVEL
Public Viva Voce Examination
30.06.2014
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 Effectiveness
E-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
Group
Gender
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 Mathematics
Teacher 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 USED
TOOLS 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 Scale
format. Out of the 40 items 29
were positive and 11 were
negative.
Perception towards e-learning Rajeshkumar and
Krishnakumar (2008)
It has 20 items in Likert Scale
format. Out of the 20 items 14
were positive and 6 were
negative.
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
Whole
Pretest
Not Significant
2 Control Vs
Experimental
Lesson wise
Pretest
Not Significant
3 Control Vs
Experimental
Learning Objective
wised Pretest
Not Significant
CalculationGraph
POST TEST
S.NO GROUP TEST RESULTS HIGHER LEVEL
1 Control Vs
Experimental
Whole
Post 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 wise
Pretest 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
Experimental
Group
Significant Post test
2 Lesson wise
Pretest Vs Posttest
Experimental
Group
Significant Post test
3 Learning objective
wised
Pretest Vs Posttest
Experimental
Group
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
Gender
Male 10 50.00 3.05
0.088 N.S
Female 24 50.12 4.01
Age
Below 23 20 50.10 2.77
0.022 N.S
Above 23 14 50.07 4.87
Level of
Graduation
UG 22 50.36 2.83
0.580 N.S
PG 12 49.58 5.05
Locale
Rural 23 50.43 3.44
0.782 N.S
Urban 11 49.36 4.29
Type of Stay
Day Scholar 21 50.19 3.73
0.201 N.S
Hosteller 13 49.92 3.81
Computer
Literacy
Yes 12 50.00 3.35
0.185 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 VS
AFTER
EXPERIMENTAL
GROUP
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 < 0.01Control 34 0.71 0.16
CalculationGraph
ANOVA & ANCOVA
REVEALS
All other demographic variables and their interactions are not have
significant interaction effect in the post test scores except the
methods of teaching
Source
Sum of
Squares
df
Mean
Square
F 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
Model
Unstandardized 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 Male
3 Religion Hindu
4 Level of Graduation UG
5 Branch of Study Mathematics
6 Age Below 23
7 Residence in home Rural
8 Marital Status Single
9 Parents Education School Level
10 Annual Income 1 Lakh
11 Post test Score 57/65
Case Study Finding
Step by step learning
Flexible learning
Encouragement
Confidence
One-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 be
introduced.
• Teachers should be trained to produce e-module package at various
levels.
• In-service training and orientation courses can be provided for
development of e-learning modules.
• New templates e-learning modules other than that templates
developed by UGC-CEC may be evolved.
• Adequate infrastructure for the development of e-learning modules
can be built in all schools and colleges.
• Computer with LCD Projector will be used in all the classes in schools
and colleges.
Recommendations
• NCERT and SCERT should take of the work of
providing module as they produce teachers’
handbook and different e-learning modules
• Appropriate software such as Adobe
premiere editing and Flash and Dream
viewer for the development of animation
may be incorporated in the teacher
education curriculum at secondary level.
• Making students to be independent in their
learning is one of the predominant
responsibilities of the teacher.
Suggestions for Further Research
• experimental study on e-learning modules can be done for other subjects at
various levels.
• Interactive e-learning modules in relation to achievement of students on various
subjects at different levels can be studied.
• Influence of other variables like social economic factors, ICT skills and soft skills
also 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 be
extended 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 THE
POSTGRADUATE 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 OF
LEARNING
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 LEARNING
MATHEMATICAL 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’ PERCEPTION
TOWARDS INFORMATION AND
COMMUNICATION TECHNOLOGY AT THE
SCHOOL LEVEL
JOURNAL OF EDUCATIONAL RESEARCH & EXTENSION
VOLUME 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 HIGHER
EDUCATION
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 TEACHING
MATHEMATICS
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-LEARNING
SKILLS” (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: THE
CASE 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
Thiyagu viva voce prsesentation
Thiyagu viva voce prsesentation

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Thiyagu viva voce prsesentation

  • 1.
  • 2. EFFECTIVENESS OF E-LEARNING MODULES IN TEACHING MATHEMATICS AT THE SECONDARY TEACHER EDUCATION LEVEL Public Viva Voce Examination 30.06.2014
  • 3. EFFECTIVENESS OF E-LEARNING MODULES IN TEACHING MATHEMATICS AT THE SECONDARY TEACHER EDUCATION LEVEL
  • 4. NEED FOR THE STUDY
  • 5. NEED FOR THE STUDY
  • 6. 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)
  • 7. OPERATIONAL KEY TERMS Effectiveness e-Learning Modules Mathematics Secondary Teacher Education Level
  • 10. OBJECTIVES ….. To find out Effectiveness E-learning Modules
  • 11. OBJECTIVES ….. To study the Influence Methods of teaching Demographic variable And their interaction of achievement scores
  • 12. To find out the Relationship Math Achievement Math Attitude Perception towards e-learning OBJECTIVES …..
  • 16. NO SIGNIFICANT DIFFERENCE Pre-test Post-test Control Group Whole Test Lesson wise Objective wise
  • 17. NO SIGNIFICANT DIFFERENCE Pre-test Post-test Experimental Group Whole Test Lesson wise Objective wise
  • 18. NO SIGNIFICANT DIFFERENCES Post-Test Experimental Group Gender Age Level of Graduation Locale Type of Stay & Computer Literacy
  • 19. Control Group Experimental Group Attitude Towards Math Before the Treatment After the Treatment NO SIGNIFICANT DIFFERENCE
  • 21. PERCEPTION TOWARDS E-LEARNING Experimental Group PTEL Before the Treatment After the Treatment
  • 22. THERE IS NO SIGNIFICANT RELATIONSHIP Achievement Test Attitude towards Math Perception towards e-learning
  • 23. INFLUENCE NO SIGNIFICANT INFLUENCE Methods of teaching Demographic variable And their interaction of achievement scores in Math
  • 24. NO SIGNIFICANT DIFFERENCE Control Experiment Adjusted mean scores of achievement test By considering pre test score as covariate
  • 26. 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
  • 28. METHOD PRE TEST - POST TEST TWO EQUIVALENT GROUPS EXPERIMENTAL DESIGN
  • 29. SAMPLE Sample Mathematics Teacher Trainees Sampling Techniques Random Sampling Total Sample Size 68 Control Group 34 - Sivanthi College of Education Experimental Group 34- Dr. Sivanthi College of Education
  • 30. Tools
  • 31. TOOLS USED TOOLS 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 Scale format. Out of the 40 items 29 were positive and 11 were negative. Perception towards e-learning Rajeshkumar and Krishnakumar (2008) It has 20 items in Likert Scale format. Out of the 20 items 14 were positive and 6 were negative.
  • 33. 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
  • 34.
  • 35.
  • 36. Quantitative Analysis ‘t’ tests - Differential Analysis Reveals MAJOR FINDINGS OF THE STUDY
  • 37. PRETEST S.NO GROUP TEST RESULTS 1 Control Vs Experimental Whole Pretest Not Significant 2 Control Vs Experimental Lesson wise Pretest Not Significant 3 Control Vs Experimental Learning Objective wised Pretest Not Significant CalculationGraph
  • 38. POST TEST S.NO GROUP TEST RESULTS HIGHER LEVEL 1 Control Vs Experimental Whole Post 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
  • 39. CONTROL GROUP S.NO TEST GROUP RESULTS HIGHER LEVEL 1 Whole Pretest Vs Posttest Control Group Significant Post test 2 Lesson wise Pretest Vs Posttest Control Group Significant Post test 3 Learning objective wised Pretest Vs Posttest Control Group Significant Post test CalculationGraph
  • 40. EXPERIMENTAL GROUP S.NO TEST GROUP RESULTS HIGHER LEVEL 1 Whole Pretest Vs Posttest Experimental Group Significant Post test 2 Lesson wise Pretest Vs Posttest Experimental Group Significant Post test 3 Learning objective wised Pretest Vs Posttest Experimental Group Significant Post test CalculationGraph
  • 41. The Mean, SD and ‘t’ value of Total Mean scores of Experimental Group Calculation Variables Groups N Mean SD ‘t’ value P Gender Male 10 50.00 3.05 0.088 N.S Female 24 50.12 4.01 Age Below 23 20 50.10 2.77 0.022 N.S Above 23 14 50.07 4.87 Level of Graduation UG 22 50.36 2.83 0.580 N.S PG 12 49.58 5.05 Locale Rural 23 50.43 3.44 0.782 N.S Urban 11 49.36 4.29 Type of Stay Day Scholar 21 50.19 3.73 0.201 N.S Hosteller 13 49.92 3.81 Computer Literacy Yes 12 50.00 3.35 0.185 N.S No 22 50.25 4.45
  • 42. 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
  • 43. PERCEPTION TOWARDS E-LEARNING S.NO TREATEMENT TREATEMENT RESULTS HIGHER LEVEL 1 BEFORE VS AFTER EXPERIMENTAL GROUP SIGNIFICANT AFTER TREATEMENT CalculationGraph
  • 44. GAIN RATIO Variable Group N Mean SD ‘t’ P Gain Ratio Experimental 34 1.03 0.23 6.78 Significant P < 0.01Control 34 0.71 0.16 CalculationGraph
  • 46. All other demographic variables and their interactions are not have significant interaction effect in the post test scores except the methods of teaching Source Sum of Squares df Mean Square F 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
  • 47. 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
  • 49. 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 Model Unstandardized 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
  • 51. There is significant Relationship between Achievement & Math attitude Math Attitude & Perception towards e-learning Perception towards e- learning & Achievement Calculation
  • 52. Qualitative Analysis 1 Name S.Vivek (Experimental Group) 2 Gender Male 3 Religion Hindu 4 Level of Graduation UG 5 Branch of Study Mathematics 6 Age Below 23 7 Residence in home Rural 8 Marital Status Single 9 Parents Education School Level 10 Annual Income 1 Lakh 11 Post test Score 57/65 Case Study Finding Step by step learning Flexible learning Encouragement Confidence One-way learning
  • 53. EDUCATIONAL IMPLICATION ASSISTING AUTO INSTRUCTIONAL MATERIAL INTEREST AND NOVELTY THEORETICAL AND PRACTICAL KNOWLEDGE SMALL FRAMES PRIVACY EFFECTIVE INSTRUCTION
  • 55. Recommendations • Newer instructional technologies using e-learning module can be introduced. • Teachers should be trained to produce e-module package at various levels. • In-service training and orientation courses can be provided for development of e-learning modules. • New templates e-learning modules other than that templates developed by UGC-CEC may be evolved. • Adequate infrastructure for the development of e-learning modules can be built in all schools and colleges. • Computer with LCD Projector will be used in all the classes in schools and colleges.
  • 56. Recommendations • NCERT and SCERT should take of the work of providing module as they produce teachers’ handbook and different e-learning modules • Appropriate software such as Adobe premiere editing and Flash and Dream viewer for the development of animation may be incorporated in the teacher education curriculum at secondary level. • Making students to be independent in their learning is one of the predominant responsibilities of the teacher.
  • 57. Suggestions for Further Research • experimental study on e-learning modules can be done for other subjects at various levels. • Interactive e-learning modules in relation to achievement of students on various subjects at different levels can be studied. • Influence of other variables like social economic factors, ICT skills and soft skills also 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 be extended to other optional B.Ed., Teacher Trainees.
  • 58. 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 THE POSTGRADUATE 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 OF LEARNING 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 LEARNING MATHEMATICAL 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’ PERCEPTION TOWARDS INFORMATION AND COMMUNICATION TECHNOLOGY AT THE SCHOOL LEVEL JOURNAL OF EDUCATIONAL RESEARCH & EXTENSION VOLUME 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 HIGHER EDUCATION 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 TEACHING MATHEMATICS 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-LEARNING SKILLS” (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: THE CASE 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