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INSTITUTE FOR MATHEMATICAL RESEARCHUNIVERSITY PUTRA MALAYSIA
MALAYSIA
www.inform.upm.edu.my
LEARNING MATHEMATICS THROUGH UTILIZATION OF TECHNOLOGY
STUDY 1STUDY 1
Rohani Ahmad Tarmizi ([email protected])
Ahmad Fauzi Mohd AyubKamariah Abu Bakar
Royati Saha
BACKGROUND• Technology in education had vast impact on
learners worldwide.• When technology and appropriate teaching
methods are integrated in teaching and learning, positive impact maybe observe on both cognitive and affective domain of learning.
• Technology as a tool or a support for communicating with others, allows learners to play active role in the classrooms.
In mathematics, many technological softwares and hardwares can be used as a tool in teaching and learning in the classrooms.
With technology students become more active in thinking about information, making choices, and executing skills than is typically in a teacher-led lessons.
In mathematics classrooms, tools such as Graphing calculators, Autograph, Geometer’s Sketchpad, e-transformation, Geogebra, Mathematica, Matlab, Derive, Cabri have been widely used both at secondary and tertiary level.
BACKGROUND
In this study, several technological tools were explored in its efficiency and utilization at the secondary level- Graphing calculators, Autograph
BACKGROUND
Graphing Calculator is a hand-held mathematics calculator that can Draw and analyses graphs,
Computes the values of mathematical expression,
Solve equations,
Perform symbolic manipulation,
Perform statistical analyses
Graphing Calculator Graphing Calculator GroupGroup
WINDOW
To set the viewing windows
ZOOM
To adjust the windows to a
predefined setting.TRACE
To move the cursor along the graph function using ◄ and ►
GRAPH
Displays the graph you have
defined.
▲ ► ▼ ◄
Let you move the cursor in four directions.
Y=
Display Y=Editor,where you can enter
functions.
2ND
Provides access to the secondary
function.
ALPHA
To access the green letters
above the keys.
X,T,Θ,n
Pastes the variable into the definition
of a function
CLEAR
Erases the last entry; erases the
Home screen.
ENTER
Executes commands and evaluates expressions.Graphing CalculatorGraphing Calculator
Graphing Calculator GroupGraphing Calculator Group
GRAPHING CALCULATOR GC is considerably a versatile tool for teaching or learning
mathematics. GC is not only a teaching tool in the hands of the teacher, it
is also a learning tool in the hands of students when used during classroom investigations, concept development and guided discovery exercises, explorations, open-ended homework exercises, and extended modeling projects.
The use of GC in classroom transforms the class to that of a laboratory.
Students could work in small groups where they can investigate patterns, analyze results and solve problems, thereby constructing their own mathematical understanding.
Graphing Calculator GroupGraphing Calculator Group
Autograph GroupAutograph Group
Autograph GroupAutograph Group
Conventional GroupConventional Group
Design of The Study Experimental design was used for this study. Students were selected at random and assigned to groups. The experimental groups underwent learning using graphing
calculator and Autograph technology while the control group underwent learning using conventional instructional strategy.
Four phases were conducted: Introduction to software Introduction to topic Integrated teaching and learning using software Testing using achievement test and The Paas Mental Effort
Rating Scale.
METHODOLOGY
Design of the Study
Group Pretest Learning Phase
Posttest
Exp - GC O1 X O2
Exp - Auto O1 X O2
Conventional O1 X O2
Experimental, non-equivalent control group
pretest-posttest design Students were assigned to three groups randomly.
Similar questions as in the posttest.
Introduction to the technological tools
Induction set phase Learning and
assessment phase Test phase
Learning to use the GC or Autograph or the traditional learning
• Concept development - important concepts learnt were emphasized
EXPERIMENTAL
GROUPS
CONTROL
GROUP
Using GCUsing Autograph
Traditional whole-class instruction
Beginning of a lesson - to induce in students an appropriate set of behavior and to spur students to attack their work enthusiastically and diligently.
EXPERIMENTAL GROUPS: Students were required to solve the given problems using paper-pencil
CONTROL GROUP: Students were given problems to solve using paper-pencil
INSTRUMENTS OF THE STUDY
1. Mathematics Achievement Test (MAT)
2. Paas Mental Effort Rating Scale
The MAT was designed by the researchers to
measure students’ understanding of the Quadratic Function
topic. It comprised of three questions based on
the learning outcomes covered in the learning
phase. The time allocated to do the test is
30 minutes.
PROCEDURE OF THE STUDY
Randomized assignment of students to the experimental and control groups and were placed in three different classrooms. A pretest on Quadratic Functions were then conducted a for all groups.
INTRODUCTION Use of GC or Autograph followed by
Induction Set for the topic ‘Quadratic Function’
INTERVENTIONGC Strategy, Autograph Strategy &
Conventional Strategy
POSTTESTMathematics Achievement & PAAS
mental effort rating scale
Videotaped sessions
METHODOLOGY
The target population of this study was Form Four students (grade 10) in National Secondary School in Malaysia.
The samples selected for this study were Form Four students from two schools.
The students were brought to the university (Universiti Putra Malaysia) to participate in the learning sessions.
The total number of students in the graphic calculator group was 41 students, groups two followed the Autograph learning mode was 39 and the conventional group was 47 students.
Population and Sample
Table 1: Comparison of Mathematics Achievement Test
RESULTS
Perfomance Group N M SD
MAT (Mathematics Achievement Test)
GC 42 15.54 3.14
Autograph 39 10.72 3.47
control 47 13.03 3.65
• Overall mean of MAT scores of GC group was significantly higher than the conventional group and Autograph group. • These findings indicated that the GC strategy group had performed better in test phase than the conventional group and Autograph.
Variables Group N M SD SE
Mental effort (learning phase)
GC 31 4.45 1.65 .296
Autograph 22 4.10 2.04 .435
Control 27 3.79 1.96 .378
Mental effort
(test phase)
GC 38 4.79 1.48 .24
Autograph 35 4.95 1.88 .32
Control 28 4.46 1.48 .28
Table 2: Comparison of Mental Effort
RESULTS
Learning phase ANOVA test results indicated that there was no significant
differences in the mean mental effort between the three groups during learning phase.
Planned comparison test showed that mean mental effort during learning phase of GC group was significantly higher from those of conventional group.
Test phase Planned comparison test showed that mean mental effort during
test phase of GC group was significantly lower from those of the Autograph group.
This finding indicated that the GC strategy group had benefited from the learning sessions hence their mental effort was lower compared to the Autograph group during the test phase.
RESULTS
Table 3: Comparison on instructional efficiency index
planned comparison test showed that the mean for GC group was significantly higher than conventional group followed by Autograph group
This suggests that learning by integrating the use of GC was more efficient than using conventional strategy and Autograph group.
Variable Group N M SD SE
2-D instructional
efficiency
GC 38 .3844 .8802 .1428
Autograph 35 -.5125 1.2261 .2072
Control 28 .1613 1.0214 .1930
2-D Instructional Efficiency
RESULTS
Table 4: Comparisons of selected variables
Variables Group N M SD
No. of problem solved
GC
Autograph
Control
42
39
47
6.98
6.64
6.28
.154
1.20
1.08
Total score of conceptual knowledge
GC
Autograph
Control
42
39
47
10.12
4.97
7.28
3.06
3.24
3.63
Total score of procedural knowledge
GC
Autograph
Control
42
39
47
18.36
16.92
18.06
2.72
3.86
1.36
No. of errors committed
GC
Autograph
Control
42
39
47
.7937
2.2886
1.5213
.596
2.87
.898
RESULTS
CONCLUSION The results also showed that the higher performance of
the GC strategy was achieved with a lower mean mental effort during test phase.
The eta squared indices were .34 and .13 respectively, a large and moderate effect based on Cohen (1988), implying that the GC strategy provides effective impact on cognitive load.
The results also suggested that the higher achievement was achieved with a reduction in cognitive load. This contention was supported by the significantly higher level of 3-D instructional condition efficiency index reported by the GC strategy as opposed to the other two strategy.
Graphing calculator is instructionally more efficient compared to conventional method and Autograph software.
Systematic planning of instructions and good learning package using graphing calculator and Autograph will give new views in mathematics teaching and learning.
This shows that dynamic technological tools, particularly graphing calculator provide positive impact upon learners thus becoming potential tools in teaching mathematics at Malaysian secondary school level.
CONCLUSION
CONCLUSION In conclusion, graphing calculators are
excellent tools which can foster students to explore and investigate during mathematical activities besides enhancing students understanding and performance.
However, there is a need to conduct further research on how to integrate graphing calculators in mathematics instruction so that students' mathematical understanding are enhanced and reinforced.
EXPLORING EFFECT OF UTILIZING GEOMETER SKETCHPAD ON PERFOMANCE
AND MATHEMATICAL THINKING OF SECONDARY MATHEMATICS LEARNERS
STUDY 2STUDY 2
Kamariah Abu Bakar([email protected])
Rohani Ahmad Tarmizi Ahmad Fauzi Mohd AyubAida Suraya Mohd Yunus
The teaching and learning of geometry utilizing dynamic geometry softwares have been explicitly indicated in the Malaysian secondary school syllabus (Ministry of Education, 2003)
Teachers have been recommended to utilize such software and one such dynamic geometry software licensed to be used in the Malaysian schools is the Geometer’s Sketchpad (GSP) software.
BACKGROUND
• Geometer’s Sketcpad (GSP) is a software programme that revolutionized the teaching and studying of mathematics especially in geometry.
• It is a computer software for creating, exploring and analyzing a wide range of mathematics concepts in the field of algebra, geometry, trigonometry, calculus, and other areas (Geometer’s Sketchpad, Reference Manual, 2001).
BACKGROUND
BACKGROUND
• Almeqdadi(2000) in his study had investigated the effect of using the GSP on students’ understanding of some of the geometrical concepts.
• The sample consisted of 52 students from the Model School, Yarmouk University, Jordan.
• The result of the study indicated that there was a significant difference between the means of students on the posttest and more gain in the scores from the pretest to the posttest in the case of the experimental group.
BACKGROUND• There are also some studies that showed negative
results.• Teoh Boon Tat & Fong Soon Fook (2005) in their
study to examine the effects of using the GSP and the graphic calculator (GC) in the learning of the vertex form of quadratic functions among field dependent (FD) and field independent (FI) cognitive style students.
• They found that the students performed as well when using GSP or the GC in the learning of quadratic function by way of visualization of graphs.
BACKGROUND
• A similar research was conducted by Ling (2004) which compared the use of the GSP software, the GC and the traditional method to learn on the cross-section of a cone.
• Reslts of the study showed that the GSP software and the GC did not show a significant effect on the achievement of the students.
• From all the findings, it may be concluded that the utilization of the GSP software has obtained mixed reviews on its effectiveness.
OBJECTIVES
The purpose of this study is to investigate the effectiveness of integrating a mathematical software which is Geometer’s Sketchpad compared to the traditional approach in teaching and learning of form four Additional Mathematics subject on the topic of ‘Quadratic Functions’.
Specifically, the objectives are:
To compare students mathematical perfomance utilizing GSP and conventional instruction in mathematics teaching and learning at the Malaysian secondary level.
• To compare instructional efficiency of learning conditions utilizing GSP and conventional instruction in mathematics teaching and learning at the Malaysian secondary level.
• To investigate the attitude of students towards learning GSP and conventional instruction in mathematics teaching and learning at the Malaysian secondary level.
METHODOLOGY
• A true experimental design randomized posttest only control group design was used for this study with students randomly assigned into two groups.
• The experimental group underwent learning using GSP technology while the control group underwent learning using a conventional instructional strategy.
• This study used four phases:i. Introduction to Geometer Sketchpadii. Introduction to Quadratic functionsiii. Integrated teaching and learning using Geometer Sketchpadiv. Testing using set of Quadratic Equation Test
Design of The Study
Design of The Study
Group Pretest Learning Phase
Posttest
Exp - GC O1 X O2
Exp - Auto O1 X O2
Conventional O1 X O2
Experimental, non-equivalent control group
pretest-posttest design Students were assigned to two groups randomly.
Similar questions as in the posttest.
Introduction to the technological tools
Induction set phase Learning and
assessment phase Test phase
Learning to use the GC or Autograph or the traditional learning
• Concept development - important concepts learnt were emphasized
EXPERIMENTAL
GROUPS
CONTROL
GROUP
Using Geometer Sketchpad
Traditional whole-class instruction
Beginning of a lesson - to induce in students an appropriate set of behavior and to spur students to attack their work enthusiastically and diligently.
EXPERIMENTAL GROUPS: Students were required to solve the given problems using Geometer Sketchpad software
CONTROL GROUP: Students were given problems to solve using paper-pencil
INSTRUMENTS OF THE STUDY
• Mathematics Achievement Test (MAT)
• Pass Mental Effort Rating Scale
• Questionnaire on Perceived Efficacy of the technological tools
The MAT was designed by the researchers to measure students’ understanding of the Quadratic
Function topic. It comprised of three questions based on the learning
outcomes covered in the learning phase. The time allocated to do the
test is 30 minutes.
A set of Questionnaire was adapted from previous studies measuring
perceived efficacy of the instructional strategy followed by the students
namely the use of Geometer Sketchpad and traditional learning.
PROCEDURE OF THE STUDY
Randomized assignment of students to the experimental and control groups and were placed in three different rooms. A pretest on Quadratic Functions were then conducted a for all groups.
Introduction to the Intervention Mode followed by Induction Set for the topic ‘Quadratic Function’
INTERVENTIONGSP Strategy &
Conventional Strategy
POSTTESTMathematics Achievement & Survey of Perceived Efficacy of GSP Strategy or
Conventional Strategy
Videotapes sessions
Population and Sample The target population of this study was Form
Four students (grade 10) in National Secondary School in Malaysia.
The samples selected for this study were Form Four students from two schools.
The students were brought to the university (Universiti Putra Malaysia) to participate in the learning sessions.
The total number of students in the GSP group was 45 students whilst the conventional group was 47 students
METHODOLOGY
Table 1: Comparison of Mathematics Achievements
RESULTS
Variable Group N M SD
MAT score GSP 45 11.78 4.10
control 47 13.03 3.65
• Overall mean of MAT scores showed that there was no significant difference between mean perfomance scores of the control group compared to scores for the GSP group.• In fact, the mean score of the control group is higher than the result of the experimental group.
…RESULTS
Table 2: Comparisons of selected variables
Variables Group N M SD SE
No. of problem solved
GSP
Control
45
47
5.98
6.28
1.29
1.08
.19
.16
Total score of conceptual knowledge
GSP
Control
45
47
5.99
7.28
4.67
3.63
.70
.53
Total score of procedural knowledge
GSP
Control
45
47
18.4
18.06
1.39
1.36
.21
.19
Total score of the test
GSP
Control
45
47
24.01
25.34
4.74
3.78
.71
.55
…RESULTS
Table 2 (con’t): Comparisons of selected variables
Variables Group N M SD SE
No. of errors committed
GSP
Control
45
47
1.95
1.52
1.54
.898
.23
.13
Mental Load GSP
Control
45
47
5.61
4.46
2.03
1.48
.30
.28
2D Efficiency GSP
Control
45
47
- 0.28
0.43
1.22
0.95
.181
.178
3D Efficiency GSP
Control
45
47
- 0.56
0.61
1.24
0.87
.216
.198
…RESULTS
• There was no significant difference between procedural steps when performing each activity like plotting the graphs, were analyzed.
• There was also no significant difference between conceptual skills obtained by the control group as compared to the experimental group.
…RESULTS
Table 3: Mean and SD of students’ attitutes towards the teaching and learning approaches.
Levels
Control GSP
Mean SD Mean SD
Enthuasiasm 3.29 0.612 3.52 0.526
Enjoyment 3.28 0.610 3.40 0.565
Anxiety 1.87 0.386 1.93 0.474
Avoidance 1.77 0.612 1.69 0.526
…RESULTS
• The attitudes of students towards the respective teaching approaches used was measured according to the four dimensions of students attitudes.
• Level of enthuasiasm refers to the extent students were enthused to continue learning using the respective approaches.
• Level of enjoyment refers to extent students had enjoyed the approached used to teach the respective group.
• Level of anxiety refers to the extent the approach had imposed and created anxiety during learning.
• Level of avoidance refers to students perceptions that the respective approaches were a waste of time and a fruitless effort.
It is crucial to note that the respondents are form four students selected from a nearby school.
Within six hours, students need to undersatnd the contents and to familirize with GSP.
For them, GSP is a new and exciting experince as observed from the attitudinal measures, but they do not have enough time to explore the GSP and benefited from its utilization during teaching and learning.
Time’s constraint thus might be one of the factors why this study came out with negative impact on the use of technology.
CONCLUSION
CONCLUSION Further studies need to be done, especially
on time needed for students to explore and learning using GSP in learning mathematics.
Furthermore, research also need to be conducted in normal classroom settings in Malaysian school in order to explore further in utilizing GSP in mathematics learning.
However, findings from this study can elicit ideas to teachers and researchers on the needs using ICT technology in teaching and learning mathematics.
Exploring the effectiveness of using GeoGebra and e-transformation in teaching and learning Mathematics
STUDY 3Kamariah Abu Bakara
Ahmad Fauzi Mohd Ayubc
Rohani Ahmad Tarmizi b
a,b,cInstitute of Mathematical Research, Universiti Putra Malaysia, Malaysia
Many studies have been conducted to determine the suitability or effectiveness of the use of computer software in teaching and learning mathematics.
Research by Rohani Ahmad Tarmizi, Ahmad Fauzi Md. Ayub, Kamariah, Abu Bakar, Aida Suraya Md. Yunus (2008) showed that teaching and learning mathematics utilizing the graphing calculator was found to be instructionally efficient significantly, compared to the conventional and Autograph software.
Introduction
Findings by Kamariah, Abu Bakar, Rohani Ahmad Tarmizi, Ahmad Fauzi Mohd. Ayub, Aida Suraya Md. Yunus (2009). indicated that the use of Gemeters Sketchpad (GSP) induced higher mathematical thinking process amongst the GSP group. These findings showed that the use of GSP had an impact on both mathematical thinking process and performance.
Norris (1995) and Penkow (1995) reported that there was no significant differential effect between conventional teaching and the use of graphing calculator.
Purpose
The purpose of this study was to investigate students’ performance score using GeoGebra and e-transformation in the learning of mathematics by Form two secondary school students’ on the topic of Transformation.
GeoGebra is an open source software while e-transformation is a computer based learning courseware, specially developed for learning transformation.
Specifically, the objective of this study was to compare the effects of utilizing the two technologies (GeoGebra and e-Transformation) on various performance measures in learning the topic on transformation.
GeoGebra is an open source software under General Public License (GPL) and freely available at www.geogebra.org.
This software combines geometry, algebra and calculus into a single ease-to-use package for teaching and learning mathematics from elementary to university level
GeoGebra
GeoGebra
e-Transformation (e-Transform) is a courseware developed by a group of researchers, based on students’ difficulties.
e-transform
e-transform
e-transform
Methodology A true experimental design was used for this study with students
being randomly assigned into two groups. One group used GeoGebra while the other used e-transformation.
In this study, there is no control group because both groups underwent computer based learning.
Four phases were conducted:
1) The Pre Testing phase;
2) Introduction to Software (GeoGebra and e-Transformation) phase;
3) Integrated teaching and learning phase using each software and a Learning Activity Module; and
4) the Post Test phase.
Purposive sampling was used to select the three classes of Form two students from a school.
These students were randomly assigned into two groups, whereby group one followed the GeoGebra mode of learning and the second group used e-transformation.
The total number of students in group one was 40 students, and group two was 30 students.
Methodology
Results
A. Effects of GeoGebra on Performance score for pre and post test.
For the group that used GeoGebra, the analysis on the performance scores for pre and post tests were by using Wilcoxon T.
Research findings indicated that there was significant difference in performance scores for the post test (Mdn = 31.00) compared to the pre test (Mdn = 25.00), z = - 2.85, p =.004 <.05, r = -0.45).
The results showed that students who learned transformation using GeoGebra showed increase in their performance after they used it.
the effect size was medium
B. Effects of e-transformation on Performance score for pre and post test.
For the second hyphotesis, analysis using Wilcoxon T showed that there were significant differences in post test performance scores (Mdn = 25.00) compared to the pre test scores (Mdn = 20.00), z = - 2.76, p = .006 < .05, r = -0.50).
This showed that the e-Transformation could help students to increase their performance.
the effect size was big.
Results
C. Effects of GeoGebra and e-transformation on Overall Performance score for pre test
To answer the third hypothesis, the Mann-Whitney test was conducted on pre test performance scores for the groups using GeoGebra and e-transformation.
Research findings showed that there was no significant difference in the pre test performance scores for the GeoGebra group (Mdn = 25.00) compared to the e-transformation group (Mdn= 20:00, U = 478.00, z =- 1.45, p =. 147 > .005, r = 0.173) and the effect size was small [2].
This shows that based on the pre test, students from both groups were at the same level.
Results
D. Effects of GeoGebra and e-transformation on Overall Performance score for post test
For the fourth hypothesis, the Mann-Whitney test was also conducted on the post test performance scores.
Findings also indicated that there was no significant difference in post test performance score for the group GeoGebra (Mdn= 31.00) compared to the e-Transformation group (Mdn = 25.00, U = 494.00, z = - 1.262, p = .207 > .005, r = 0.15) and the effect size was small [2].
This finding also showed that students who used GeoGebra and e-transformation did not differ significantly on the post test.
Results
E. Effects of GeoGebra and e-transformation on each of the topics (transformation, reflection and rotation) tested
For the transformation topic, there was no significant difference in performance scores for the GeoGebra group (Mdn = 11.00) compared to the e-transformation group (Mdn = 7:00, U = 483.50, z = -1.407, p = .159 > .005, r = 0.17).
For reflection, the Mann-Whitney test analysis did not show any significant difference in the performance score for the GeoGebra group (Mdn = 15.50) compared to the e-transformation group (Mdn = 14.00, U = 538.50, z = -.767, p = .443 > .005, r = 0.09).
Results
As for rotation topic, findings also indicated that there was no significant difference in performance scores for GeoGebra group (Mdn = 7.00) compared to the e-Transformation group (Mdn = 3.50, U =472.00, z = -1.543, p = .123 > . 005, r = 0.18).
These findings showed that each topic included in the post test did not show any significant difference in terms of the students’ performance scores.
Students who used e-Transformation and GeoGebra had the same skills when answering questions related to transformation, reflection and rotation.
Results
Students who used the GeoGebra software and e-transformation shows improvement in performance when comparing the results of the pre and post tests scores of both groups.
This shows that the use of technology can have a positive effect on student achievements.
The findings did not show any significant difference between students who used the GeoGebra software compared to the e-transformation group.
Conclusion
• Technology Oriented• Business Driven • Sustainable Development• Environmental Friendly
The Effects of GeoGebra on Mathematics Achievement:
Enlightening Coordinate Geometry Learning
STUDY 4
Royati Abdul Saha
Ahmad Fauzi Mohd Ayub
Rohani Ahmad Tarmizi
INTRODUCTION
What is GeoGebra? Dynamic Mathematics
Software For Learning and Teaching
Mathematicsin Schools
This software was developed by Markus Hohenwarter in 2001 at the University of Salsburg
Has been translated to 48 languages. Use in 190 countries.
Geometry, Algebra , Calculus and Statistics.
Freely available fromwww.geogebra.org
It was designed to combine features of
• dynamic geometry software (e.g. Cabri Geometry, Geometer’s Sketchpad)
• computer algebra systems (e.g. Derive, Maple)
and easy to-use system for teaching and learning mathematics ( Hohenwarter & Preiner, 2007).
High technical portability
• runs on Windows, Linux, Solaris, MacOS X
• dynamic worksheets (html)
GeoGebra is Innovative
GeoGebra = Geometry Algebra+
Geometry & Graphics Window
Algebra Window
RESEARCH OBJECTIVES
METHODOLOGY
Use quasi-experimental study with non-equivalent control group post-test only 2 x 2 (visual-spatial ability x treatment) factorial designs.Research sample - two homogeneous Form Four classes in Sekolah Menengah Perempuan Jalan Ipoh, Kuala Lumpur, aged 16 and 17 years
Use quasi-experimental study with non-equivalent control group post-test only 2 x 2 (visual-spatial ability x treatment) factorial designs.Research sample - two homogeneous Form Four classes in Sekolah Menengah Perempuan Jalan Ipoh, Kuala Lumpur, aged 16 and 17 years
Table 1: Factorial Design 2 x 2
Group N Mean Standard Deviation
t DF Significant
Control Group 26 54.7 15.660
2.259 51 0.028GeoGebra Group
27 65.23 19.202
Significant difference between mean performance scores of the control group (M=54.7, SD= 15.660) compared to GeoGebra group (M= 65.23, SD= 19.202; t(51) = 2.259, p = .028 < .05) The effect size (eta squared, 2) is approximately 0.09, which is considered to be a moderate effect (Cohen, 1988). Students who had learned Coordinate Geometry using GeoGebra was significantly better in their achievement compared to students who underwent the traditional learning.
Group N Mean Standard Deviation
t DF Significant
Control Group 12 61.667
13.793
0.953 22 0.351GeoGebra Group
12 67.583
16.489
No significant difference between mean performance scores of the control group (M=61.667, SD= 13.793) compared to GeoGebra group (M= 67.583, SD= 16.489; t(22) = 0.953, p = .351> .05) However, the mean score of the HV students in GeoGebra group is higher than the result of the HV students in Control Group
No significant difference between mean performance scores of the control group (M=61.667, SD= 13.793) compared to GeoGebra group (M= 67.583, SD= 16.489; t(22) = 0.953, p = .351> .05) However, the mean score of the HV students in GeoGebra group is higher than the result of the HV students in Control Group
Group N Mean Standard Deviation
t DF Significant
Control Group 14 48.786
15.106
2.222 27 0.036GeoGebra Group
15 64.067
21.569
Significant difference between mean performance scores of the control group (M=48.786, SD= 15.106) compared to GeoGebra group (M= 64.067, SD= 21.569; t(27) = 2.222, p = .036< .05) The effect size (eta squared, 2) is approximately 0.15, which is considered to be a very large effect (Cohen, 1988) LV students who had undergone learning Coordinate Geometry using GeoGebra was significantly better in their achievement rather than students underwent the traditional learning. GeoGebra software enhanced the LV students in their mathematics performance.
Significant difference between mean performance scores of the control group (M=48.786, SD= 15.106) compared to GeoGebra group (M= 64.067, SD= 21.569; t(27) = 2.222, p = .036< .05) The effect size (eta squared, 2) is approximately 0.15, which is considered to be a very large effect (Cohen, 1988) LV students who had undergone learning Coordinate Geometry using GeoGebra was significantly better in their achievement rather than students underwent the traditional learning. GeoGebra software enhanced the LV students in their mathematics performance.
DISCUSSION & CONCLUSION
DISCUSSION & CONCLUSION
