The Use of Explorative Learning Model with Inquiry Labs Method
and Verification Laboratory Method for Improving Students’ Skill
Process
Sheila Fitriana
1
, Miftahul Husnah
1
, Nana Mardiana
1
, Hasrita Lubis
2
, Rachmat Rizaldi
1
and Syahwin
1
1
Physics Education, Universitas Islam Sumatera Utara, Jl. Sisingamangaraja. Teladan-Medan. Medan. Indonesia
2
Chemistry Education, Universitas Islam Sumatera Utara, Jl. Sisingamangaraja. Teladan-Medan. Medan. Indonesia
Keywords: elasticity, inquiry labs, explorative learning model, science process skills, laboratory verification.
Abstract: This study aims to determine differences in the improvement of students' science process skills that get
explorative learning model with inquiry labs method and laboratory verification method. This research uses
two classes as the sample, they are one class of experiment and one class of control class XI SMA Negeri 2
Pulau Punjung, Dharmasraya Regency, West Sumatra. The experiment class is a class that accepts explorative
learning model with inquiry method in the class of control class that is the class that accepts explorative
learning model with laboratory verification method. The research method used is a quasi-experiment with the
design of the randomized pretest-posttest control group design. The result shows that the students’ science
process skills increase and the normalized gain scores <g> for the students' science process skills in the
experiment class is 0.54 and the control class is 0.40. Data processing is done by t-test statistic for the average
difference. The result of the research shows that the application of explorative learning model with inquiry
labs method on the concept of elasticity can significantly improve the students' science process skills
compared with the use of explorative learning model with verification laboratory method.
1 INTRODUCTION
Physics is related to how to systematically find out
about nature so that physics is not only mastery of a
collection of knowledge in the form of facts, concepts
or principles but also the process of discovery
(Ministry of National Education, 2006). In addition,
natural science is a basic science that is developed
based on the results of scientific discovery related to
the events of nature every day. Therefore, the
application of physics learning cannot be separated
from processes and products. Science learning has
goals that are closely related to the environment and
everyday life. This is in line with the functions and
objectives of Physics subjects at the secondary school
level as a means of: i) Arousing the beauty and
regularity of nature to increase trust in God, ii)
Fostering a scientific attitude that includes; honesty
and objective with respect to data, open in accepting
opinions based on certain evidence, critical of
scientific statements, and able to work together with
others, iii) Providing experience to be able to propose
and test hypotheses through experiments; designing
and compiling experimental instruments, collecting,
processing and interpreting data, compiling reports,
and communicating experimental results from written
and oral experiments, iv) Developing the ability to
think inductive and deductive analysis using concepts
and physical principles to explain natural events and
solve problems both qualitatively and quantitatively,
v) Mastering knowledge, concepts, and principles of
physics, and possessing scientific knowledge, skills
and attitudes (Ministry of National Education, 2003).
Therefore, in the learning process emphasis
should be placed on learning activities that train
students to have process skills. Rustaman (Rustaman,
2006) suggests that the basic skills of scientific work
consist of emotional intelligence and intellectual
intelligence. Intellectual intelligence is largely a
science-process skill (SPS) in primary and secondary
education, which includes observing, interpreting,
classifying, predicting, communicating,
hypothesizing, planning experiments, applying
concepts, and asking questions.
Fitriana, S., Husna, M., Mardiana, N., Lubis, H., Rizaldi, R. and Syahwin, .
The Use of Explorative Learning Model with Inquiry Labs Method and Verification Laboratory Method for Improving Students’ Skill Process.
DOI: 10.5220/0008892006570663
In Proceedings of the 7th International Conference on Multidisciplinary Research (ICMR 2018) - , pages 657-663
ISBN: 978-989-758-437-4
Copyright
c
 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
657

The case study report conducted in 2014 showed
that cognitive physics learning outcomes from 25
students were still low, especially in understanding
science process skills. In the results of student science
skills tests, 25% aspects were observed, hypothetical
aspects were 47%, predictions 45%, identification
aspects 35%, 49% aspects of data interpretation, 20%
aspects of conclusions. From all aspects, it can be
concluded that students' science process skills are in
the low category. This is due to the learning process
is lacking in facilitating and training aspects of
students' skills.
Explorative learning is a learning aimed at
exploring different ideas, arguments and ways from
students through a number of open questions and
commands that can lead the students to an
understanding of concepts and solving problems. In
this approach, students become active explorers and
teachers serve only as mentors and exploratory
facilitators.
The purpose of exploration activities is to enable
students to engage broadly in problem-solving. The
role of the teacher in the exploration activities is as a
facilitator and guide during the activation process, the
teacher facilitates the possibility of exposing the
students' ability in expressing different ideas,
arguments, and ways of finding concepts or solving
problems through explorative problems.
In order for the learning process to be in
accordance with the nature of physical learning and
students can build on the concept of knowledge that
they already have, it requires learning methods that
facilitate it. One method that can be applied to
achieve that goal is investigation. This investigation
will bring the impact of learning on the positive
mental development of students because through this
learning, students have a wide opportunity to find and
find out for themselves what is needed especially in
abstract learning.
Thus, it is important to apply laboratory activities
to the method of inquiry in conducting physics
learning. Implementation of this method is expected
to improve students' science process skills. In general,
the literature study conducted by Rohaeti,
Dwirahayu, Roth et al., Tamir, etc. (Rohaeti, 2008;
Dwirahayu, 2012; Roth et al. 2003; Tamir, 2005),
shows the results of physics learning using
investigative lab methods can support to improve
some of the skills that exist in students and the interest
of students to follow the learning process.
Physical learning in schools is generally done
through verification of laboratory activities. Many
concepts, principles, and laws can be well developed
through a deductive approach, where teachers teach
concepts in the classroom, followed by laboratory
activities to verify attributes and relationships.
2 RESEARCH METHODS
The method used in this research is Quasi-method of
the experiment. This design has a control group but
cannot function fully to control the outside variables
that affect the experiment execution (Sugiyono,
2010). The use of the quasi-experiment method is
used to find out the comparison of science skill
improvement among students who get explorative
learning with inquiry labs method and students who
get explorative learning by laboratory verification
method.
The design used in this research is The
Randomized pretest-posttest control group design,
which is a research design where initially one
experiment group measured its dependent variable
(pre-test). After that, the group is given treatment, and
the dependent variable is re-measured (post-test). The
research design of The Randomized Pretest-Posttest
Control Group Design (Fraenkel and Wallen, 2009)
is more clearly seen in Table 1 below:
Table 1: Randomized Control Group Pretest-Posttest
Design.
Category Pre-test Treatment
Experiment
Class
O X
1
Control Class O X
2
Information:
O : pre-test and post-test to measure science process
skills
X
1
: Treatment using explorative learning model with
inquiry labs method.
X
2
: Treatment using explorative learning model with
verification laboratory method.
Do not add any text to the headers (do not set
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For a best viewing experience, the used font must
be Times New Roman, on a Macintosh use the font
named times, except on special occasions, such as
program code (Section 2.3.7).
2.1 Population and Sample
The population in this research is all students in SMA
Negeri 2 Pulau Punjung in the odd semester of
academic year 2013/2014. The sample in this
ICMR 2018 - International Conference on Multidisciplinary Research
658

research is class XI SMA N 2 Pulau Punjung. From a
number of classes, it will be determined two classes
using cluster random sampling technique. The
technique used is the drawing technique. The drawing
technique is performed to determine the control class
and the experiment class. One selected class is used
as the experiment class that will receive learning
treatment using explorative learning model with
inquiry labs method. The other one class as a control
class that accepts learning using an explorative
learning model with a verification laboratory method.
Another class that functions as a control class accepts
learning using an exploration learning model with a
verification laboratory method.
The data were collected during pre-test and post-
test using science skill test. Science process skill tests
are multiple choice questions that include aspects of
observing skills, concluding, identifying variables,
predicting, hypothesizing, and interpreting. The test
has been tested for validity, reliability, distinguishing
power and convenience level test.
2.2 Data Analysis
Analysis of data is intended to make interpretation of
data obtained from research results. The data analysis
is used to know the improvement of students' science
process skill.
2.2.1 Scores on Pre-test and Post-test
Results
Before data processing is carried out, all the pretest
and posttest answers of students are examined and
scored. The correct answer is ranked first and the
answer is incorrect or not answered with a zero value.
2.2.2 Calculating a Normalized Gain Score
(N-Gain)
Normalized gains are the comparison between the
gain scores obtained by students with the maximum
gain scores that can be obtained (Hake, 1999). They
can be mathematically written as follows:
SS
g
SS
post pre
m ideal pre



(1)
Information:
g = normalized gain
S
post
= final test score obtained by the student
S
pre
= initial test score obtained by the student
S
m Ideal
= ideal maximum score
2.2.3 Determine Normalized Average Gain
Scores
To find out the improvement of students' science
process skills in the elasticity material, normalized
mean score data were processed using equations
developed by Hake (1999), namely as follows:
<S S
<g>
SS
post pre
m ideal pre
 



(2)
information:
<g> = normalized average gain scores
<S
post
> = the average score of the final tests students
get
<S
pre
> = the average score of the initial tests
students get
S
m Ideal
= ideal maximum score
2.2.4 Introduces a Normalized Average
Gain Score using Table
Tabel 2: Interpretasi Skor Rata-Rata Gain yang
Dinormalisasi
(Hake, 1999).
<
g
> Criteria
<g> ≥ 0,7 High
0,3 ≤ <g>< 0,7 Mediu
m
<g>< 0,3 Low
2.2.5 Hypothesis Testing
To further strengthen whether the data obtained has a
significant increase or not, it is necessary to have two
different test averages (hypothesis testing). This
hypothesis test consists of several steps that must be
passed to achieve the right results. The following are
steps that must be taken to test the hypothesis using
the help of SPSS 16.0 data processing software for
Windows.
1) Normality Test of N-Gain Data
Normality test aims to determine the distribution
of data obtained. Normality test used in this
study is Kolgomorov-Smirnov test with a
significance level (
0, 05


). If the value
.sig


then Ha accepted. In other words, the
data is normally distributed.
2) Homogeneity Test of N-Gain Data Variance
The homogeneity test was conducted to see
whether the data values obtained from these two
groups had the same variance or not. In this
study, homogeneity test was performed by using
Levene Test (Test of Homogeneity of
The Use of Explorative Learning Model with Inquiry Labs Method and Verification Laboratory Method for Improving Students’ Skill
Process
659

Variances) with a significance level (
0, 05


). If the value
.sig


of Ha is
accepted. In other words, the variance for both
data is homogeneous.
3 RESULTS AND DISCUSSIONS
Testing the application of explorative learning model
with inquiry labs method to improve the science
process skills on the concept of elasticity is done by
comparing the normalized average gain values
between experiment classes using explorative
learning model with inquiry labs method with control
class using explorative learning model with
laboratory method verification. Comparison of the
mean initial test scores, the final test and the
normalized gain (in percent) between the experiment
class and the control class are shown in Figure 1.
Figure 1: Bar chart Comparison of Average Scores Initial
Test, Final Test and Normalized Gain.
Figure 2: Normalized Mean Gain Value Chart Diagram Per Type of Science Process Skills.
Based on Fig. 1, it was found that the normalized
gain-averaged values for the experiment class were
0.54 in the medium category and the normalized
average gain for the control class was 0.40 in the
moderate category. This direct comparison of values
demonstrates that the use of explorative learning
models with inquiry labs methods can more
effectively improve students' science process skills on
the elasticity concept than the verification laboratory
model.
Improved science process skills can be grouped
for each type of skill that is, observing skills,
concluding, identifying variables, predicting,
hypothesizing, and interpreting. Normalized gain
values for each type of science process skill for the
34
70
54
27
56
40
0
10
20
30
40
50
60
70
80
Pretest Postest N-gain
Score (%)
Experiment
Control
0,29
0,31
0,5
0,67
0,6
0,63
0,29
0,28
0,46
0,35
0,25
0,38
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
N‐gain
Experiment
control
ICMR 2018 - International Conference on Multidisciplinary Research
660

experiment class and control class are shown in
Figure 2.
3.1 Observing Skills
The type of observing skill is the skill of collecting
data on phenomena or events using its senses.
Observing is the foundation for all other process
skills. In other words, through observation, we collect
data about our responses. In the learning process,
students are asked to observe either a picture or a
natural phenomenon related to elasticity either in the
form of a direct phenomenon or a tool that can
indicate an elasticity event.
Based on Fig. 2, the normalized gain averaged for
the experiment class is 0.29 (low category) and the
normalized gain value for the control class is 0.29
(low category). It can be seen that the improvement
of the type of science process skill observed in the
experiment class is the same as the control class.
3.2 Concluding Skills
The conclusion is an explanation one uses of what is
observed to explain something that has happened.
The conclusions are based on observations and
explanations of observations.
Based on Fig. 2, the mean gain values of
normalized skill concluded for the experiment class
were 0.31 (medium category) and the normalized
gain value for the control class was 0.28 (low
category). In this type, the normalized average gain
ratio between the experiment class and the control
class is not too large.
3.3 Identifying Variable Skills
A variable is a quantity that can vary or change in a
given situation. Based on Fig. 2, the mean values of
the normalized gain of the skill in identifying the
variables for the experiment class were 0.5 (medium
category) and the normalized gain values for the
control class were 0.46 (medium category). In this
type, the normalized average gain ratio between the
experiment class and the control class is not too large.
3.4 Predicting Skills
The predicting skill is the submission of results that
may result from an experiment. Prediction is based on
previous observations and inferences.
Based on Fig. 2, the normalized average gain
values for the experiment class are 0.67 (medium
category) and the normalized gain values for the
control class are 0.35 (medium category). If the
normalized average gain values for the two classes
can be seen, the use of explorative learning model
with inquiry labs method can more effectively
improve the students' prediction skills on the
elasticity concept compared with the verification
laboratory model.
3.5 Hypothesis Skills
The formulation of the hypothesis is the formulation
of a reasonable guess that can be tested about how or
why something happened. Hypotheses are often
expressed as statements if and then. Based on Fig. 2,
the normalized average gain values for the
experiment class were 0.6 (medium category) and the
normalized gain-averaged values for the control class
were 0.25 (low category).
In general, based on the normalized average gain
values for the two classes, it can be concluded that the
application of explorative learning model with
inquiry labs method can more effectively improve
students' hypothesized skills on the concept of
elasticity compared to the class using the verification
laboratory model.
3.6 Data Interpretation Skills
The skills to interpret data is to explain the meaning
of information that has been collected. Included in
interpreting data is entering data into a table and
drawing graphs of data obtained or vice versa. Based
on Fig. 2, the normalized gain averaged the
experiment data skill for the experiment class is 0.63
(medium category) and the normalized gain value for
the control class is 0.38 (medium category). In this
type the normalized average gain ratio between the
experiment class and the control class is large.
In general, based on the normalized average gain
values for the two classes, it can be concluded that the
application of explorative learning model with
inquiry labs method can more effectively improve the
communication skill on the concept of elasticity
compared to the class using the laboratory
verification model.
Based on the description of the improvement of
science process skill, it can be concluded that the
application of explorative learning model with
inquiry labs method is more effective in improving
the science process skills on the concept of elasticity
compared to the class using the laboratory
verification model.
The Use of Explorative Learning Model with Inquiry Labs Method and Verification Laboratory Method for Improving Students’ Skill
Process
661

3.7 Skills Improvement of Student's
Science Process on Elasticity Concept
Based on the results of pre-test data analysis of
science process skills on the concept of elasticity, it is
known that the average score of the control class is
not too much different from the experiment class
before the application of the model of laboratory
activities. Thus, it can be concluded that both classes
have the same initial ability. This is because some
concepts of elasticity have been studied by students
in junior high schools, and the context of pre-test
problems faced by many students on a daily basis.
The two classes were given different learning
treatments that controlled the class using an
exploratory learning model with laboratory
verification methods while the experimental class
used an exploratory learning model with an
investigative laboratory method. To find out the
improvement of students' science process skills, the
posttest was implemented and the results were
analyzed.
Observation skills did not show a high N_gain
difference between the experiment and the control
class because in the laboratory activities, the students
were poorly trained to observe the experiment
activities. Similarly, the low N_gain difference in the
ability to plan the experiment. On the skills of
identifying these variables, the experiment class
students are trained to design experiment steps with
guided by method questions. But from the posttest
result, it turns out the N_gain difference is not too
high. This is presumably because the instruments to
test these skills are less able to measure the skills of
identifying variables.
Based on the result of data analysis, students who
get learning with explorative learning model with
inquiry labs as a whole method show their science
process skill better than those who get learning with
the model of verification laboratory activity. The high
acquisition of posttest score and the normalized gain
of the experiment class is caused by the explorative
learning model with the inquiry labs method directing
the students to various activities such as observing
skill, concluding, identifying variables, predicting,
hypothesizing, and interpretation.
Dahar (Dahar, 1985) states that when a child
during science learning is only informed about
existing science by listening to teacher explanations,
the science itself will stop growing. Science is not just
knowledge that consists of facts, principles, concepts,
and theories known as science products, but also the
skills and attitudes necessary to achieve a product of
science known as the process of science.
This is in line with Rustaman (Rustaman, 1997)
who defines the skills of the scientific process as the
necessary skills to acquire, develop and apply the
concepts, principles, laws, and theories of science in
the form of mental skills, physical skills, and social
skills. The skills of this science process can be
improved with an explorative model. Through these
step-by-step laboratory models, students are guided
and directed to initiate activities by identifying
contextual problems, preparing tools and materials to
solve problems, predicting problem solutions,
devising experiment steps to solve problems/plan
experiments, explore, measure, analyze the data
obtained and conclude so the problem can be finished
well.
The highest increase in the science process skills
for the experiment class is on predicting skills with a
normalized average gain value of 0.67 (medium
category). This happens because, in the learning
process, students are trained to be able to submit
results that may result from an experiment. Prediction
is based on previous observations and inferences.
While the skill improvement of the lowest experiment
class science process is on observing skill with the
normalized average gain value of 0.29 (low category).
This is because, in the learning process, students are
poorly trained to observe either a picture or a natural
phenomenon related to elasticity either in the form of
a direct phenomenon or a tool that can indicate an
elasticity.
The highest increase in science process skills for
the control class is on the skill indicator of the
variables with a normalized average gain value of
0.46 (medium category). This happens because in the
learning process, students are able to identify
variables from the experimental activities carried out.
While the lowest increase in science process skills in
the control class was on hypothesizing skills with a
normal average gain of 0.25 (low category). This is
because, in the learning process, students are poorly
trained to form reasonable assumptions that can be
tested on how or why something happens and the
LKS used is verification of LKS.
Based on the results of the analysis and discussion
above, it can be concluded that the improvement of
the science process skills of students’ elasticity using
explorative learning model with the inquiry labs
method is significantly higher than the students using
the laboratory verification model.
ICMR 2018 - International Conference on Multidisciplinary Research
662

4 CONCLUSIONS
Based on data and analysis of the results of research
conducted on exploratory learning models with
inquiry lab methods in elasticity learning to develop
science process skills, it can be concluded that
exploratory learning models with inquiry lab methods
can significantly improve science process skills
compared to explorative learning models with
methods laboratory verification. Improving the
science process skills of students in the inquiry
laboratory class is relatively better than that of
students in the verification laboratory class.
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