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INTERNATIONAL REVIEW OF HUMANITIES AND SCIENTIFIC RESEARCH
By International Scientific Indexing
ISSN (Online): 2519-5336
www.irhsr.org
368
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
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
INTERNATIONAL REVIEW OF HUMANITIES AND SCIENTIFIC RESEARCH
By International Scientific Indexing
ISSN (Online): 2519-5336
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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.
INTERNATIONAL REVIEW OF HUMANITIES AND SCIENTIFIC RESEARCH
By International Scientific Indexing
ISSN (Online): 2519-5336
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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.
INTERNATIONAL REVIEW OF HUMANITIES AND SCIENTIFIC RESEARCH
By International Scientific Indexing
ISSN (Online): 2519-5336
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371
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
INTERNATIONAL REVIEW OF HUMANITIES AND SCIENTIFIC RESEARCH
By International Scientific Indexing
ISSN (Online): 2519-5336
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372
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
INTERNATIONAL REVIEW OF HUMANITIES AND SCIENTIFIC RESEARCH
By International Scientific Indexing
ISSN (Online): 2519-5336
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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
INTERNATIONAL REVIEW OF HUMANITIES AND SCIENTIFIC RESEARCH
By International Scientific Indexing
ISSN (Online): 2519-5336
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374
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
Overview of Chemical
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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By International Scientific Indexing
ISSN (Online): 2519-5336
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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
Overview of Chemical
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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References:
Baguinat, P.S. III (2012), College Algebra Instruction with Code- Switching
Application: Singapore and Hongkong Practices. The Threshold Journal, RFM
Motong Printing Press.Jose Rizal Memorial State University.
Buhian, V. (2011) Experiential Learning Model in Teaching Communication Arts and
Skills: Effects on Students' Performance. Jose Rizal Memorial State University.
Unpublished Thesis.
Carpenter, Y., Moore, E.B., & Perkins, K.K(2015). Representations and Equations in an
Interactive Simulation that Supports Student Development in Balancing Chemical
Equations. The University of Colorado Boulder, Spring 2015 ConfChem:
Interactive Visualizations for Chemistry Teaching and Learning. Retrieved on
May 17, 2016, from https://confchem. ccce. divched.
org/sites/confchem.ccce.div
Daymiel, A. (2008) Games and Simulations Effective Tools for Teaching Mathematics.
The Threshold Journal, RFM Motong Printing Press. Jose Rizal Memorial State
University.
Elumba, Ryann Z. (2011).ChemBond Tutorial and Simulation: Computer-aided
Instruction for Chemical Bonding Concepts. Jose Rizal Memorial State
University, Main Campus. Unpublished Paper.
Gongden, J.J. (2014).Assessment of the Difficult Areas of the Senior Secondary School
2 (two) Chemistry Syllabus of the Nigeria Science Curriculum. University of
Jos, P. M. B. 2084, Jos –Nigeria. Retrieved on June 9, 2016 from
https://www.ajol.info/index.php/ajce/article/download/82525/72681
Johnstone, A. H. (2000). Teaching of Chemistry-Logical or Psychological.Chemistry
Education: The Practice of Chemistry Education Research and Practice in Europe.1
(1), 9-15.Retrieved on April 10,2016 from http://pubs.rsc.org
/en/content/articlelanding/2000/rp/a9rp90001
Moore, E. B., & Perkins, K. (2014). Assessing the Implicit Scaffolding Design
Framework:
Effectiveness of the Build a Molecule Simulation.In Proceedings of the National
Association for Research in Science Teaching (NARST), Annual International
Conference. Pittsburgh, PA. Retrieved on May 20, 2016, from https:
//phet.colorado.edu/en/research
Ramasundarm, V., Grunwald, S., Mangeot, A., Comerford, N.B., and Bliss, C.M. 2005.
Development of an Environmental Virtual Field
Laboratory.Computers,45(1):21–34
Saavedra, Farida (2017). Computer-Aided Instruction Effects on Student Performance in
Chemistry.Jose Rizal Memorial State University.Unpublished Thesis.
Salviejo, E. Aranes, F. Espinosa, A. (2014) Strategic Intervention Material-Based
Instruction, Learning Approach and Students‘ Performance in Chemistry. International
Journal of Learning Teaching and Educational ResearchVol. 2, No. 1, pp. 91-
123.Retrieved on May 18, 2016, from https://www.ijlter.org/index.php/
ijlter/article/view/10
INTERNATIONAL REVIEW OF HUMANITIES AND SCIENTIFIC RESEARCH
By International Scientific Indexing
ISSN (Online): 2519-5336
www.irhsr.org
381
Skinner, BF.(2003) Technology of Teaching. BF Skinner Foundation.ISBN 978-0-
9964539-2-99(epub).Retrieved on May 1, 2016, from https.book.google.com.ph
Smetana, L.K., & Bell, R.L. (2012).Computer Simulations to Support Science
Instruction and Learning: A Critical Review of the Literature. International
JournalofScienceEducation,34
(9):13371370.doi:10.1080/09500693.2011.605182.
Retrieved on May 2, 2017 from http://www.tandfonline.com/doi/abs
Svinicki, M.(2003).What They Don’t Can’t Hurt Them: The Role of prior Knowledge in
Learning. University of Texas, Texas.
Talanquer, V. (2011).Macro, Submicro, and Symbolic: The Many Faces of the
Chemistry Triplet. International Journal of Science Education, 33(2), 179–195.
https://eric.ed.gov/?id=EJ910991
Tasker, R.(2015) Research into Practice: Visualizing the Molecular World for a Deep
Understanding of Chemistry. Spring 2015 ConfChem: Interactive Visualizations for
Chemistry Teaching and Learning.Retrieved on June 5, 2016,
fromhttps://confchem.ccce.divched.org/sites/confchem.ccce.divched.org/files/20
15SpringConfChemP5_0.pdf
Villanueva, R. (2014).Technology–Based Integration in Teaching Mathematics. Jose
Rizal Memorial State University.