INTERNATIONAL REVIEW OF HUMANITIES AND SCIENTIFIC …irhsr.org/papers/1567966794.pdf · Jose Rizal Memorial State University-Main Campus, Dapitan City [email protected] A

INTERNATIONAL REVIEW OF HUMANITIES AND SCIENTIFIC RESEARCH

By International Scientific Indexing

ISSN (Online): 2519-5336

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THE CHEMBOND INTERACTIVE TUTORIAL AND 3D SIMULATION

INSOLVING CHEMISTRY PROBLEMS

Farida C. Jamolod, M.Chem, MAGensci

Jose Rizal Memorial State University-Main Campus, Dapitan City

[email protected]

Abstract.

This study investigated the effects of Interactive Tutorial and 3D Simulation graphics modeler

softwareamong the Senior High School students belonging in the academic track Science, Technology,

Engineering and Mathematics (STEM) strand at Jose Rizal Memorial State University-Main Campus,

Dapitan City in terms of integrating both the traditional and technology-integrated pedagogical strategies

in teaching Inorganic Chemistry. The Quasi-Experimental Design 07 was employed. After a random

selection of the two groups to be the subjects of this study, twenty-one (21) students composed the

Experimental Group and twenty-one (21) students comprised the Control Group. The data collected were

treated using mean, z-test and t-test. The result of the study revealed that the pretest performance of the

two groups was at par before the intervention. However, in the post-test performance of the students

exposed to Interactive Tutorial and 3D Simulation Application, the result was “very good’ while that of

the students exposed to the traditional method of teaching was only "good." Indeed, students became

technologically–literate and engage in the use of software application in solving abstract and symbolic

Chemistry problems resulting in greater learning. Based on the findings of the study, the researcher

recommended that Chemistry Instructors should integrate the Chemical Bonding Interactive Tutorial and

3D Simulation Application in teaching Chemistry to have fun and meaningful learning.

Keywords: information and communication technology, the 3D simulation application, academic

performance, quasi-experimental design, Philippines




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Introduction

The deliberate integration of educational technologies into the classroom to enhance

21st-century teaching and learning experiences remains to be an integral aspect of

teacher education (Luu& Freeman, 2011; Windschitl, 2009). Computer-aided instruction

in the practice of simulations offers the teachers a distinctive opportunity to enable their

students to connect realistic visual models to essential scientific concepts.

Smetana and Bell (2012) decided that ‘‘as with any other educational tool, the

effectiveness of computer simulations is dependent upon the ways in which they are

used’’ and recommended that ‘‘computer simulations are most effective when these are

used as supplements; incorporate high-quality support structures; encourage student

reflection; and promote cognitive dissonance.’’The interactive engagement and instant

feedback of simulations allow students to do their own task and easily repeat trials and

thus, encourage conceptual reasoning and meaningful understanding. This learning-by-

doing approach can also make abstract concepts more concrete (Ramasundarm,et.al.,

2015).

Thus, one of the greatest challenges that Chemistry teachers face in the classroom is

instilling scientific understanding by communicating and clearing up what is taking

place at the sub-micro level. Inorganic Chemistryis a major branch of Chemistry that

deals with the study of matterthat consists of all of the elements other than carbon and

hydrogen and their combinations. It also considers the chemical and physical properties

of matter, the chemical and physical changes that happen, and the energy changes that

accompanythose processes. A very significantdiscipline in understanding the

fundamental feature of our worldbut is often regarded by students as an intricate subject.

Traditionally they are noted as being very hard to understand because the topics consist

of extremely conceptual and abstract concepts. Particularly, students’ difficulties lie in

accurately interpreting and producing chemical formulas, as well as connecting

symbolic to particulate level representations (Talanquer, 2011). There is substantial

evidence in the literature that many student problems and misconceptions in Chemistry

result from insufficient or inaccurate models at the molecular level. Absence of

meaningful learning is confirmed by the fact that several students can answer traditional-

style Chemistry problems without understanding the fundamental molecular processes

(Tasker, 2015).

To help understand the difficulties students were experiencing in learning of Chemistry,

Johnstone identified Three Levels of Chemistry Learning, namely: the microscopic, the

macroscopic and the representational or symbolic (Johnstone, 2000). He suggested that

an expert in Chemistry considers seamlessly between three levels as the macro which is

stated to as the observable level, the sub-micro which is discussed to as the molecular

level and the representational which is termed as to as the symbolic level. For this

reason, a tool that can enable students to visualize the molecular concepts in Chemistry

has a crucial role in enhancing their overall understanding as well as their general

interest and performance in Chemistry. Along with this view, the researcher was

challenged to undertake the present study in order to investigate the effects ofChemical

Bonding Interactive Tutorial and 3D Simulation on the Senior High School STEM track

student’s performance in Chemistry at Jose Rizal Memorial State University-Main

Campus during the Academic Year 2017-2018. Specifically, it aimed to investigate:

1. the pretest performance of the Chemistry STEM trackstudents in the:

1.1. Control Group;

1.2. Experimental Group.

2. the significant difference in the pretest performance of the Chemistry STEM track

students in the Control and Experimental Groups.

3. the posttest performance of the Chemistry STEM trackstudents in the:

3.1. Control Group;

3.2 Experimental Group.




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4. the significant difference in the posttest performance of the Chemistry STEM

trackstudents in the Control and Experimental Groups.

5. the significant difference on the pretest and posttest performance of the Chemistry

STEM track students in the Control and Experimental Groups.

6. the significant difference on the mean gains scores of the Control and Experimental

groups.

In this investigation, the researcher utilized the Chemical Bonding Interactive Tutorial

and 3D Simulation developed by a group of ADZU students taking Bachelor of Science

and Information Technology and enhanced by their adviser Engr. Ryann E.

Elumba(2011). The group developed graphics modeler software with two parts: the

tutorial class and the chemical bonding simulation. The application simulates

compounds formed from covalent bonding following the formula ABn. Using this

formula limited the number of compounds that can be formed. However, the

successfully bonded atoms have been represented by the Covalent Bonding Simulation

software and simulated in the 3D platform, and thus more comprehensible than the usual

illustrative approach and less costly and time-consuming than manually building

models.

Basically, these were utilized, in order to support the teaching and learning process of

some of the abstract concepts in Chemistry, in which along with this view, was the

interest of the researcher. CAI can motivate students to learn as it provides interactive,

hands-on activities for a rich learning environment.

Theoretical and Conceptual Framework

The present study is anchored on the Theory of Educational Technology by Skinner as

cited in Villanueva (2014) which states that technology integration provides a more

authentic learning environment. Moreover, it is imperative for schools to adopt

technology integration because research has shown that it turns teachers and students

complicated tasks simple and easy to accomplish. Using educational technology, the

teaching and learning activities become enjoyable. Students learn willingly by playing

and enjoying classroom activities.

The schema of the study is presented in Figure 1, on the succeeding page,

whichaimedtofindouttheeffectsofChemical Bonding Interactive Tutorial and 3D

Simulation on the students' performance in Inorganic Chemistry of Jose Rizal Memorial

State University.

The topmost block in the schema reflects the subjects under study, the Senior High

School STEM track students of Jose Rizal Memorial State University. Before the

teaching intervention, both the Experimental and Control Groups were given a 50-item

pretest. The research instrument used in the study was subjected to the degree of validity

and reliability such as TOS examination, item analysis, and reliability tests. The arrow

from the pretest block is pointing the next lower block containing the Inorganic

Chemistry topics in the pretest, namely: “Overview of the Chemical Bonding”, “Types

of Bonding”, “Molecule Shapes” and “Nomenclature of Compounds”.

Using the same subject matter the members of the Control Group were taught using the

traditional method, while the members of the Experimental Group were exposed to

computer-aided instruction (CAI). Unlike the traditional method of teaching, this time,

the ExperimentalGroup was exposed to the use of computers, LCD projectors and

speakers in presenting the lesson. Specifically, CAI used Chemical Bonding Interactive

Tutorial and 3D Simulation, video clips, and teacher-made PowerPoint presentations.

After the experiment, both the Control and Experimental group were administered with

posttest on the same items given during the pretest. This is reflected by the arrow from

the block containing the four topics in Chemistry pointing to the posttest block. The

pretest and posttest performances of the groups were eventually tabulated and analyzed

with the use of statistical tools such as mean, z- test and t-test.




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Figure 1 Schema of the Study

Methodology

The Quasi-Experimental method of research was utilized with a single test paper

administered to the respondents. There were three sections of Grade 12 STEM students

in the institution. The first section was selected to be the respondents of the study and

was selected through their first-semester average grade. The test paper was handed out

the 20 non-respondents belonging to the two other sections at JRMSU–Main Campus,

Dapitan City. These non-respondents were tasked to answer a 50-item test paper used in

item analysis comprising of the four dimension topics in Inorganic Chemistry. The items

in the instrument were based on the Table of Specification (TOS) in Chemistry utilizing

Bloom's Taxonomy. Few of the items were modified to be fit to the needs of this study

The researcher divided the class into two groups then randomly assign by tossing a

coin. The final test paper administered personally by the researchers and answered by 42

student-respondents, as shown in Table 1, during the Academic Year 2017-2018

evaluated the students’ performance in solving basic Chemistry problems. The two

groups were given a pretest of a valid and reliable teacher-made multiple choice test

composing of questions on the topics discussed.

Table 1 Subjects of the Study

Group Frequency Percentage

Control 21 50.00%

Experimental 21 50.00%

Total 42 100.00%

The process involved in the experiment is presented in Figure 2. Before the treatment

began, both the Experimental and Control Groups were given a 50-item pretest on

general concepts in Inorganic Chemistry (Pr1 and Pr2). After the pretest was conducted,

the Control Group was taught using the traditional method (TC) of teaching, while the

researcher employed the computer-aided instruction using Chemical Bonding Interactive

Experimental

Group

Pretest

STEM Track Studentsin Chemistry at

Jose Rizal Memorial State University-Main

Campus

Control

Group Chemistry Topics:

Overview of Chemical Bonding

Types of Bonds

Molecule Shapes

Nomenclature of Compounds

Chemical

Bonding

Interactive

Tutorial

and 3D

Simulation

Traditional

Teaching

Posttest




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Tutorial and 3D Simulation to the Experimental Group (TE). After the treatment, the

same 50-item pretest was administered to make up the posttest (Po1 and Po2). The

members of the control group were taught with the traditional method of teaching, while

the members of the Experimental Group were taught with computer-aided instruction.

Both groups learned the same concepts in Chemistry in consonance with the Senior

High School Curriculum Guide for K-12 STEM track. Finally, the pretest and posttest

performances of the groups were eventually tabulated and analyzed with the use of

statistical tools such as mean, z- test and t-test.

Figure 2 The Research Process

Results and Discussions

Pretest Performance of the Control Group Table 2 depicts the pretest performance of the Senior High School students in the STEM

track of the Control Group. The table shows that the group did not attain the 75% level

of performance on the four succeeding topics, namely: Overview of the Chemical

Bonding, Types of Bonds, Molecule Shapes and Nomenclature of Compounds with

AMs of 5.14, 3.10, 2.48, and 3.38, respectively.

Furthermore, the overall level of performance of the students exposed to the four topics

using the traditional method of teaching was described as "fair" performance having

14.10 AM and 2.00 SD, which was below the expected level of performance of 37.50

HM. The computed z-test value of -53.62 for the four topics did not exceed the critical

value of 2.086 at 20 degrees of freedom which is not significant at 95 percent confidence

level. This implies that the students that belong to this group have prior or stored

knowledge on the areas tested, but it was not fully strengthened because more often than

not, students are not aware of what they know.

This finding is supported by Svinicki (2011) who claimed that what students learned is

conditioned by what they already recognized. Students are not blank slates on which

teacher’s words are inscribed. What students learn is conditioned by what they already

know.

The findings of the current investigation as to the performance of the Control Group

during the pretest were also corroborated by the studies conducted in Baguinat (2011),

Buhian (2011) andSaavedra (2017)in which revealed that the control group was below

the expected performance during the pretest.

Table 2 Pretest Performance Profile of the Control Group

Topics No. of Items HM

(75%) AM SD Z – value De

Overview of Chemical

Bonding 15.00 11.25 5.14 1.71 -16.37

Fair

Types of Bonds 15.00 11.25 3.10 1.70 -21.97

Fair

EXPERIMENTAL

GROUP

CONTROL

GROUP

GROUP PRETEST TREATMENT POSTTEST

Pr2

TC P02

P01 TE Pr1




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Molecule Shapes 10.00 7.50 2.48 1.17 -19.66

Fair

Nomenclature of Compounds 10.00 7.50 3.38 1.12 -16.86

Fair

Total 50.00 37.50 14.10 2.00 -53.62

Fair

d.f.= 20 c.v.= 2.086 α = 0.05

Legend:

HM, Hypothetical Mean d.f. Degrees of Freedom

AM Actual Mean c.v. Critical Value

SD Standard Deviation De Description

Pretest Performance of the Experimental Group

Table 3 presents the pretest performance profile of the students exposed to the

instruction integrated with the Chemical Bonding Interactive Tutorial and 3D

Simulation. Results showed that like the Control Group, this group of students did not

succeed also in obtaining the 75 percent performance or 37.50score same with the latter

group. It is also evident in the table that the students exposed to the Chemical Bonding

Interactive Tutorial and 3D Simulationobtained AMs of 6.33, 4.29, 2.52 and 4.14,

respectively. On the four topics presented, topics about the overview of Chemical

Bonding and Nomenclature of Compounds, the group attained “good” performances

while the two remaining topics, Types of Bonds and Molecule Shapes they got only

“fair” performances. This implies that the group has preconceived knowledge on the

basic concepts in chemical bonding and naming compounds but they have difficulty on

learning sub-micro concepts in Chemistry especially identifying types of bonds and

geometrical shapes of the molecules as reflected in their actual mean value of 4.29 and

2.52with HMs of 11.25 and 7.50 respectively.

Similarly, like the Control group, the Experimental group obtained computed z-test

value of -22.13 for the four topics which did not exceed the critical value of 2.086 at 20

degrees of freedom which implies that it is not significant at 95 percent confidence level.

Generally, over-all pretest performance of the Experimental Group as seen in the table

was “fair”, having obtained a 17.29 AM and 37.50 HM.

Table 3 Pretest Performance Profile of the Experimental Group

Topics No. of

Items

HM

(75%) AM SD Z – value De

Overview of Chemical Bonding 15.00 11.25 6.33 2.71 -8.32 Good

Types of Bonds 15.00 11.25 4.29 1.52 -20.98 Fair

Molecule Shapes 10.00 7.50 2.52 0.98 -23.29 Fair

Nomenclature of Compounds 10.00 7.50 4.14 1.56 -9.87 Good

Total 50.00 37.50 17.29 4.19 -22.13 Fair

d.f. =20c.v. =2.086α = 0.05

Indeed, the pretest results revealed that there is a need in making these concepts in

Chemistry understandable as these are the very foundation for every student to logically

comprehend the macroscopic and symbolic concepts in Chemistry.

Numerous foreign studies like that ofTasker (2015) and local studies like that of

Daymiel (2008) substantiate the findings of the current study as they also found out that




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the Control Group, as well as the Experimental Group, did not perform well in the

conduct of the pretest.

In order to improve the students’ performance in Chemistry, in which like the other

Science subjects has traditionally been regarded as a difficult subject (Gongden, 2014),

the instruction must focus on instilling scientific understanding by communicating and

explaining what is taking place at the sub–micro level.

Likewise, Villanueva (2014) asserted that the student that may come into the situation

where they do not have a foundation and skills in logical concepts requires technology-

based integration in teaching. Hence, teachers need to employ strategies so that learning

will be easy and teaching the subject could be more meaningful.

Table 4 depicts the t-test table comparing the difference in the pretest performance

between the Control Group and the Experimental Group. The results disclose that for the

four topics given to the groups, there was no significant difference between the two

groups in their pretest performances on each topic since their critical value of 2.0453

was greater than their respective computed t-values of 1.70,1.39, 0.14 and 1.82. This

means that the students exposed to traditional method and students exposed to Chemical

Bonding Interactive Tutorial and 3D Simulationalmost exhibit the same level of

performance. Their pretest results before the proper experimentation were “fair”, which

means that students have preconceived notions or ideas about concepts that instructor

wants them to learn.

Table 4 Test of Difference on the Pretest Performance Between the Control and

Experimental Groups

d.f= 40 c.v = 2.0453 α = 0.05

Legend d.f. Degrees of Freedom cv Critical Value

SD Standard Deviation De Decision

Posttest Performance Profile of the Control Group

Table 5 presents the posttest performance of the students in the Control Group or those

students exposed to the traditional method of teaching. As reflected in Table 5, in the

Overview of Chemical Bonding topic, the posttest performance of the students obtained

an actual mean (AM) of 12.05 with 2.87 SD against the hypothetical mean (HM) of

11.25. This AM value exceeded the HM value. The group passed in obtaining the

expected mean score as confirmed in the computed z–value of 1.28 which is less than

Topics Traditional CAI Mean

Difference

t-

computed De

Mean SD Mean SD


Bonding 5.14 1.71 6.33 2.71 1.190 1.70

ns

H0 not

Rejected Types of Bonds 3.10 1.70 4.29 1.52 1.190 1.39ns

Molecule Shapes 2.48 1.17 2.52 0.98 0.048 0.14ns

Nomenclature of

Compounds 3.38 1.12 4.14 1.56 0.762 1.82

ns

Total 14.10 2.00 17.29 4.19 3.19 1.95ns




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the critical value of 2.086. The posttest was described as "fair". This shows that there is

an improvement in the students' performance during the posttest.

However, in the topic Molecules Shapes the group only attained a “fair” performance

with AM value of 3.33and HM of 7.50. Moreover, the group obtained a computed z-test

value of -8.65 for the said topic which did not exceed the critical value of 2.086 at 20

degrees of freedom which implies that it is not significant at 95 percent confidence level

In totality, the students in the Control Group failed to attain the 37.50 HM score in

the posttest since they only obtained the mean score of 29.62 with SD of 5.14 which was

described as ‘good” performance. The over-all z–value of -7.03 did not exceed the

critical value of 2.086at0.05level of significance. This means that the group did not

attain the 75% expected performance in a significant degree as reflected from the second

topic up to the fourth topic, topics which are highly abstract, molecular and symbolic.

This means clearly that students' interest to learn more was not stimulated.

Table 5 Posttest Performance Profile of the Control Group

d.f.= 20c.v. = 2.086 α = 0.05

The study of Dermirci cited in Salviejo, Aranes and Espinosa (2014) considered the

traditional method of instruction. Based on the study, traditional teaching method alone

does not promote high academic achievement in Science. The study supports the present

findings leading to the contention that there is a need to use computer-aided instruction

in order to generate better results than using the traditional method of teaching alone.

Considering that young students in the 21st century, nowadays, are engrossed and adept

in the use of technology.

Similarly, Tasker (2015) in his study concluded that animations and simulations can

communicate many key features about the molecular level effectively, and these ideas

can link the observable level to the symbolic level in order for the student to move

seamlessly between Johnstone's three "thinking-levels" in Chemistry.

Posttest Performance Profile of the Experimental Group

The posttest performance profile of the group of students exposed to Chemical Bonding

Interactive Tutorial and 3D Simulation.is presented in Table 6. A closer look on the

table reveals that the group passed the 75% expected level of performance on the two

topics covered to wit: Overview of Chemical Bonding and Nomenclature of

Compounds, obtaining AMs 13.38 with 1.66 SD and 7.67 with 1.32 SD, respectively. It

can also be gleaned in the table that the experimental group has “excellent”

performanceon the first topic and “very good’ performances on the succeeding three

topics. However, the group was not able to attain the 75% level of performances for the

two topics namely Types of Bonds and Molecules Shapes as the z–values of -1.72 and -

5.06 respectively are less than the critical value of 2.086.

Topics No. of

Item

HM

(75%

)

AM

SD Z–value

De

Overview of Chemical Bonding 15.00 11.25 12.05 2.87 1.28 Very Good

Types of Bonds 15.00 11.25 8.81 2.30 -4.86 Good

Molecule Shapes 10.00 7.50 3.33 2.21 -8.65 Fair

Nomenclature of Compounds 10.00 7.50 5.43 1.99 -4.77 Good

Total 50.00 37.50 29.62 5.14 -7.03 Good




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The results of the experiment vividly show that that the students exposed to computer-

aided instruction obtained an overall performance of 37.90 AM which was described as

“very good’ performance having an SD of 3.15.

Current research on learning has offered more and more evidence on the use of

computer-aided tutorial instruction and simulation to enhance the students’ academic

performance.The study conducted by Smetana and Bell (2012) suggested that the results

of their study revealed that computer simulations are most effective when these are used

as enhancements; integrate high-quality support structures; boost student reflection; and

stimulate cognitive dissonance.

The work of Carpenter, Moore, and Perkins (2015) corroborates the present findings that

interactive simulation offers an opportunity to foster student development of this skill

via an inquiry-driven approach. The result showed that there was a significant increase

in student's performance on Chemistry examination. Students who seemed to have little

or no prior background in balancing chemical equations seemed to particularly benefit

from the use of concurrent symbolic and molecular– scale representations,as well as the

less traditional balance scale representation.

Indeed computer-aided instruction was found to be of great help in reducing the learning

difficulty of the students in Chemistry as their performance became better.

Table 6 Posttest Performance Profile of the Experimental Group

Topics

No.

of Items

HM

(75%)

AM

SD

Z–value

De

Overview of Chemical Bonding 15.00 11.25 13.38 1.66 5.88 Excellent

Types of Bonds 15.00 11.25 10.52 1.94 -1.72 Very Good

Molecule Shapes 10.00 7.50 6.33 1.06 -5.06 Very Good

Nomenclature of Compounds 10.00 7.50 7.67 1.32 0.59 Very Good

Total 50.00 37.50 37.90 3.15 1.18 Very Good

d.f.= 20c.v.= 2.086 α = 0.05

Test of Difference on the Posttest Performance of the Control and Experimental

Groups

Table 7 discloses the data on the test of the significant difference between the posttest

performance of the group of students exposed to traditional teaching and students

exposed to chemical Bonding Interactive Tutorial and 3D Simulation. It can be gleaned

from the table that the group of students exposed to computer-aided instruction has a

higher mean score of 37.90 with SD of 3.15 than the group of students exposed to the

traditional method of teaching which has only 29.62 AM and SD of 5.14. This means

that the group of students exposed to computer-aided instruction performed better than

the students exposed to traditional teaching after the intervention.

Table 7 Test of Difference on the Posttest Performance between the Control

Group and Experimental Group

Topics

Control

Experimental

Mean

Difference

t-

computed

De

Mean SD Mean SD

Overview of Chemical Bonding 12.05 2.87 13.38 1.66 1.33 1.81ns H0

rejected




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d.f. = 40 c.v. =2.021 α = 0.05

Generally, the above result summarizes that there was a significant difference on the

experimental groups’ pretest and posttest performance since the recorded critical value

of 2.021is lesser than the computed t- value of 5.96with 40 degrees of freedom. This

finding provides sufficient evidence to reject the null hypothesis. Thus, there is a

significant difference between the posttest performances of the Control Group and

Experimental group. This means that there exists a significant performance of the two

groups after the intervention. This also means that the performance of students was

better with exposure to Chemical Bonding Interactive Tutorial and 3D Simulation.

Test of Difference between the Pretest and the Posttest Performance of the Control

Group

Table 8 presents the test of the significant difference between the pretest and posttest

performance of the Control Group. It can be gleaned in the table that in Overview of

Chemical Bonding topic the Control Group’s pretest was 5.14 with a SD of 1.71 while

its posttest mean was 12.05 with a SD of 2.87. When t-test was conducted, it had a

critical value of 2.021 lesser than the t-value of 9.30. In this light, there was a significant

difference between the pretest and posttest performance of the students. This result holds

true to other succeeding topics to wit: Types of Bonds and Nomenclature of

Compounds. However, to Molecule Shapes topic the critical value of 2.021 is greater

than the computed t- value of 1.54 which implies that there was no significant difference

between the pretest and the posttest topic. The group finds it very hard to comprehend

the geometrical shapes of the compounds, a highly abstract and micro-concept in

Chemistry.

Table 8 Test of Difference between the Pretest and the Performanceof the Control

Group

d.f = 40 cv = 2.021 α = 0.05

Test of Difference between the Pretest and the Posttest Performance of the

Experimental Group

Table 9 presents the data on the test of difference between the pretest and posttest

performance of the students exposed to Chemical Bonding Interactive Tutorial and 3D

Simulation. An Overview of Chemical Bonding topic, students registered a pretest mean

of 6.33 and a SD of 2.71 with a posttest mean of 13.38 and a SD of 1.66. When the

result was subjected to t-test, the t-value was 10.17, significantly higher than the critical

value of 2.021at 95% confidence level with 40 degrees of freedom, leading to the

Types of Bonds 8.81 2.30 10.52 1.94 1.71 2.57*

Molecule Shapes 3.33 2.21 6.33 1.06 3.00 5.49*

Nomenclature of Compounds 5.43 1.99 7.67 1.32 2.24 4.23*

Total 29.62 5.14 37.90 3.15 8.28 5.96*

Topics Pretest Posttest

t- computed De Mean SD Mean SD

Overview of Chemical Bonding 5.14 1.71 12.05 2.87 9.30*

H0

rejected

Types of Bonds 3.10 1.70 8.81 2.30 9.01*

Molecule Shapes 2.48 1.17 3.33 2.21 1.54

Nomenclature of Compounds 3.38 1.12 5.43 1.99 4.04*

Total 14.10 2.00 29.62 5.14 12.63*




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rejection of the null hypothesis. This means that there is a significant difference between

the pretest and posttest performance in the first topic being considered in the study.

Table 9 Test of Difference between the Pretest and the Posttest Performance

of the Experimental Group

Topics Pretest Posttest

t-computed

De

Mean SD Mean SD

Overview of Chemical Bonding 6.33 2.71 13.38 1.66 10.17*

H0 rejected

Types of Bonds 4.29 1.52 10.52 1.94 11.60*

Molecule Shapes 2.52 0.98 6.33 1.06 12.06*

Nomenclature of Compounds 4.14 1.56 7.67 1.32 7.92*

Total 17.29 4.19 37.90 3.15 17.14*

d.f = 40 c.v. =2.021 α = 0.05

Generally, the results provide sufficient evidence to reject the null hypothesis. This

implies a significant variation in the performance of the students after the computer-

aided instruction in the form of tutorial and simulation was given as an intervention. The

result of the experiment clearly showed that the use of CAI in teaching leads to better

performance of students in the subject compared to traditional method of teaching.

Test of Significant Difference on the Pre–Post Mean Gain Performance Between

the Control and Experimental Groups

Table 10 presents the test of significant difference on the pre-post mean gain between

the Control Group and Experimental Group. The table discloses that the t-value of 5.90

exceeds the critical value of 2.021at 0.05 confidence level with 40 degrees of freedom

thus leading to the rejection of the null hypothesis. On the four topics where the two

groups performances were measured, the pretest-posttest mean difference of the

Experimental Group (27.60) is greater than that of the Control Group (21.86) implying

that teaching with the intervention of Chemical Bonding Interactive Tutorial and 3D

Simulation results to better performance of the students in the Experimental Group than

those in the Control Group.

Table 10 Test of Significant Difference on the Pre–Post Mean Gain Performance

Between the Control and Experimental Groups

Topics Mean Gains

MeanDifference t-value p-

value De

Control Expt


Bonding 8.60 9.86 1.26 2.36* 0.01

H0

rejected

Types of Bonds 5.95 7.40 1.45 3.27* 0.00

Molecule Shapes 2.90 4.43 1.52 4.44* 0.00

Nomenclature of Compounds 4.40 5.90 1.50 4.32* 0.00

21.86 27.60 5.74 5.90* 0.00




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d.f= 40 c.v.= 2.0210 α = 0.05

The work of Moore & Perkins (2014) corroborate the present findings that the used of

simulation resulted to a significant increase on student's performance on Chemistry–pre-

post gains ranging from 23% to 78%. Similarly, the findings of Dangeet. al. (2006)

concluded on their study with the following results: There was a significant difference

between mean gain scores of posttest of control and experimental group and the level of

academic performance was significantly influenced by the integration of CAI in the

teaching-learning process. In order to improve students' academic performance, the role

of the teacher is to make the teaching-learning situation more effective and more

meaningful through vivid and dynamic visualizations of the concepts.

Findings Conclusions and Recommendations The findings of the study revealed that the pretest performances of the group of students

exposed to the traditional method of teaching (Control Group) and the group of students

exposed to Chemical Bonding Interactive Tutorial and 3D Simulation (Experimental

Group) were both “fair”. There was no significant difference between the pretest

performance of the two groups. The posttest performance of the Control Group was

“good”, while the Experimental Group was “very good”.There was a significant

difference between the posttest performances of the two groups. There was a significant

difference in the pretest and posttest performance of the two groups of students exposed

to the traditional method of teaching andChemical Bonding Interactive Tutorial and 3D

Simulation. There was also a significant difference on the pre-post mean gain scores of

the two groups.

Based on the findings of the study, the following conclusions are given. The prior

knowledge of students belonging to the groups of students exposed to the traditional

method of teaching and computer-aided instruction was at par before the intervention.

The students have stored knowledge in which anytime may be weakened or strengthened

during the teaching and learning process depending on the manner the lessons are

imparted. Both groups of students under study have the same level of performance prior

to the instructional interventions. The posttest performances of the students have been

augmented after the instructor taught the Chemistry topics using either traditional

method of teaching or Chemical Bonding Interactive Tutorial and 3D Simulation. The

posttest performance of the Experimental group was significantly better than the Control

group. The significant difference in the posttest performances between the two groups of

students tells that the group exposed to computer-aided instruction performed better. The

significant difference on the pretest and posttest performances of the two groups of

students shows that one from the teaching approaches used in the study, it was the use of

Chemical Bonding Interactive Tutorial and 3D Simulation that is better than the other.

The significant difference between the mean gain scores between the two groups

revealed that the integration of computer-aided instruction in teaching is better in

improving the performance of the students in the Chemistry subject.

Based on the conclusions formulated, the researcher suggests the following

recommendations, to wit: Science instructors should integrate computer-aided

instruction (CAI) in teaching sub-micro concepts in Chemistry so that learning will be

easy and fun and teaching can be more meaningful. The used of CAI includes

simulations, games, drills, videos and power point presentations. Similarly, instructors

can integrate CAI in the preparation of Chemistry syllabi, textbooks, modules,

workbooks, laboratory manuals and other instructional materials. Furthermore, they can

be given in-service training opportunities such as conferences, seminars, and workshops

focusing on CAI to enable them to update their scientific knowledge. By then, they will

be constantly abreast of the educational reforms brought by computer technology.




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