649
1 INTRODUCTION
Maritime education is always a pillar in producing
competent seafarers [1] [2]. Theoretical immersion is
extremely essential in the upbringing a competent and
holistic ship crew. Akl [3] expressed that education in
higher education requires teaching finesse and tact in
learning progression as the world treads
globalization. This also puts pressure on the
educational structures and deliverance in the pressing
matter of producing intellectual and skillful graduates
[4].
Traditional lecture-based instruction
predominantly follows the old-age concept of
pedagogy. Since the traditional approach dominates
most academic environments, students lack active
learning as instructions only provide a one-way
teacher-student information feed [5]. However, in
producing competent graduates, this method can no
longer accommodate such demands [6]. Cognitive-
centered education is now the eye of many higher
education practices as it can sufficiently scaffold
cognitive prowess [7]. Also, this method significantly
reduces the burden on the educators, as presented by
Arseven et al. [8].
Effectiveness of Problem-based Learning (PBL)
on
Maritime Courses in a Blended Learning Modality
R.R
. Germo, V.S. Tan & A.F. Casañare
John B. Lacson Foundation Maritime University
, Iloilo City, Philippines
ABSTRACT: This study aimed to determine the effectiveness of problem-based learning (PBL) on identified
courses in improving the performance of maritime students. This study utilized pretest-posttest non-equivalent
group design. Respondents were 480 BSMT students gathered using a match group design. Instrument used
was a 45-item researcher-made multiple-choice test that has undergone content validity and reliability testing.
Statistical tools used were mean and standard deviation for descriptive data analysis, Mann-Whitney test and
Wilcoxon-Signed ranks for inferential data analysis, and Cohen’s d effect size, to determine the effectiveness of
PBL. Results showed that the experimental and control group pretest performance before the intervention is
described as poor and fair, while excellent and very good thereafter. No significant difference in the pretest
scores of experimental and control groups. No significant differences in the posttest scores of experimental and
control groups in NGEC 9, NAV 5, and SEAM 6, while there were significant differences in the posttest scores
of experimental and control groups in NAV 2, NAV 4, and NAV 7. Significant differences were noted in the
pretest and posttest scores of the experimental and control groups in all identified courses. The mean gain score
of the experimental group in all identified courses is higher than the control group. No significant difference in
the mean gains of experimental and control groups, for NGEC 9, NAV 5, and for SEAM 6 but significantly
different was noted in NAV 2, NAV 4, and NAV 7. Based on the effect size results, PBL is highly effective on
NAV 2 and NAV 7 compared to the traditional method. These results confirm how effective the PBL approach
is as a teaching style in all identified courses. PBL approach is highly recommended for all maritime courses.
h
ttp://www.transnav.eu
the
International Journal
on Marine Navigation
and Safety of Sea Tra
nsportation
Volume 18
Number 3
September 2024
DOI: 10.12716/1001.18.03.
19
650
Problem-based learning (PBL) is vastly applied to
broad fields of discipline and instructional concepts
promoting cognitive scaffolding and developing
critical problem-solving attributes. Thru real-life
problem contexts, PBL provides an efficient teaching
and learning approach considering long-term
knowledge retention and application [9]. PBL’s
approach revolves around activity engagement in
meaningful problems. Students are given
collaborative problem-solving undertakings in an
attempt to form their own mental learning models, as
well as their self-directed habits through practice and
reflection. PBL’s model includes a broad objective of
strengthening critical-thinking abilities, talents in
investigation, problem-solving, and ability to learn
independently [10] [11] [12].
Problem-based learning can simply be defined as a
teaching method where problems are presented in
context [13] for the students to emulate and learn.
PBL’s process of education requires the following: a
problem to be encountered, problem – solving,
learning needs identification, self-study, application,
and summarizing what has been learned [9] [14] [15]
According to Prosser and Sze [16], PBL is effective in
long-term retention of course content and short-term
regarding elaboration of new information. The use of
PBL demonstrates its potential for learning through
the integration of maritime students’ cognitive,
behavioral and social dimensions, fostering closer
integration with the context of professional activity
[17].
The integration of PBL in blended learning is
widely observed after the COVID-19 pandemic.
According to the study of Yennita and Zukmadini
[18], the application of PBL on blended learning can
improve the critical thinking skills of students. This is
supported by the study of Zamroni et al. [19].
Essentially, blended learning promotes higher order
thinking which is largely harnessed in this modern
globalization [20] [21].
This study was conducted to provide instructors
with practical direction for more effective instruction
inside the classroom. The results of this study may
move school administrators to provide in-service
seminars, workshops, and trainings for their teachers
for them to learn the PBL approach model in teaching.
The students will certainly be benefited by the results
of this study since these will inform them about the
need to adjust to new instructional modes which may
lead to better learning of their course. Lastly, the PBL
approach had been used at JBLFMU, thus, this study
will validate previous results.
This study was anchored to the Theory of
Constructivism [22] [23] [24] [25], wherein it strongly
suggests an established link between the new
information and the existing ones each individual
during the process. The individual information is not
piled on and individual establishes the basis of
information by adding his own comment. Teachers
play vital role in this approach where the learner
serves as the core. With this approach, teachers do not
directly transfer the information to the students; but
they guide and help learners to reach the information
and to construct it [26]. According to Ayaz and
Şekerci [27] a teaching and learning environment
dominated by the constructivist approach is different
from a teaching and learning environment dominated
by the traditional approach. With this learning
approach, discourse, interests and needs of learners
are essentially paid attention thru certain
uncertainties and collaborative learning efforts.
Constructivism is related to the present study because
students will be exposed to PBL in a blended learning
modality to improve performance in maritime
professional courses [28].
Generally, this study aimed to determine the
effectiveness of PBL on identified courses using
blended learning modality in improving the students’
performance during the second semester of school-
year 2022-2023.
2 MATERIALS AND METHODS
2.1 Research Design
This study utilized the quasi-experimental specifically
the pretest-posttest non-equivalent group design. In
the pretest-posttest nonequivalent group design there
is a treatment group that is given a pretest, receives a
treatment, and then is given a posttest. But at the
same time, there is a nonequivalent control group that
is given a pretest, does not receive the treatment, and
then is given a posttest [29]. This design covered the
effectiveness of PBL in blended learning modality in
improving maritime students’ performance on
General Education and Maritime Professional courses.
Also, it utilized an instruction-related treatment or
intervention in one student group but no such
treatment in another comparable group, that is, the
experimental group incorporated the PBL while the
control group utilized with the traditional method
which is lecture-discussion. Both groups are under the
blended learning modality as mitigation for post-
COVID 19 responses among BSMT students. The
intervention lasted for four months.
2.2 Participants
Table 1 shows the 480 participants composed of 40
students per section who were bonafide students of
the institution. The participants were two comparable
sections taking the same course. The selection utilized
match-group design using General Weighted Average
(GWA) in the first semester of school-year 2022-2023.
Thus, there were 12 sections, each with two courses
for each year level who participated in the study. The
identified courses were chosen because of their
problem-solving attributes. Similarly, the chosen
subjects are vital in honing a future officer.
2.3 Instrument
Each of six instruments was a 45-item researcher-
made multiple-choice tests which contain topics
covering prelims to finals. The instruments had
underwent content validity from experts and
reliability-testing using the Kuder-Richardson (KR)
20. The Table of Specifications (TOS) was created to
assist in the construction of the instrument prior to
reliability testing. There was a total of five
651
professional and one general education courses
covered in the study. Each year level is composed of
160 students with 40 students in the experimental and
40 in the control groups in both general education and
professional courses. The list is shown in Table 1.
Table 1. Year Level, Identified Courses, Number of Section
and Students, Reliability Coefficients, and Descriptive Title
________________________________________________
1 Year/Level
2 Course
3 Number of Section
4 Number of Students
5 Reliability Coefficient
6 Descriptive Title
________________________________________________
1 2 3 4 5 6
________________________________________________
First NGEC 4 2 80 0.94 Mathematics in the
Modern World
Nav 2 2 80 0.92 Terrestrial and Coastal
Navigation 1
Second Nav 4 2 80 0.88 Celestial Navigation
Nav 5 2 80 0.91 Operational Use of
RADAR/ARPA
Third Seam 6 2 80 0.87 Advanced Trim and
Stability
Nav 7 2 80 0.89 Voyage Planning
________________________________________________
2.4 Data Collection
The data were obtained using a cognitive
achievement, researcher-made multiple-choice test for
each course. Each course test was validated by a panel
of experts for appropriateness and correctness of the
instrument.
Tossing of coins was used to determine which
groups was the experimental or control groups. The
head was assigned as experimental group and the tail
as the control group.
Pretest was conducted during first-class session.
For experimental groups, they had undergone PBL
wherein they had given the opportunities to do
problem solving in a collaborative setting, create
mental models for learning, and form self-directed
learning habits through practice and reflection. On the
other hand, for control groups, traditional method
had applied using lecture-discussion for four months.
Posttest was done after four months of using the
blended learning modality to assess the effectiveness
of the intervention.
A qualified instructor taught both groups at the
span of four months. There were a total of six
instructors who facilitated the groups and were
assigned in every year level on their designated
course.
2.5 Data Analysis
The statistical tools used in this study were the
following: Mean was used to determine the students’
performance in the pretest and posttest. The mean
scale, descriptive rating, and indicators for
interpreting the pretest and posttest scores is shown
in Table 2. Standard deviation was used to determine
the level of students’ homogeneity in their course
performance.
Mann-Whitney test was used to determine the
significant differences in the pretests and posttests
between two groups in all courses and for the
significant difference in the mean gain of the pretest
and posttest of the experimental and control groups
set at .05 level of significance.
Wilcoxon-Signed ranks test was used to determine
the significant differences in the pretest and posttest
of within each of the groups in all courses set at .05
level of significance.
Cohen’s d effect size was used to determine the
effectiveness of problem-based learning approach in
terms of students’ performance professional courses.
This is done by using the means and standard
deviation in the posttest among the experimental and
the control groups.
Table 2. Mean Scale, Descriptive Rating, and Indicators in
Interpreting the Students’ Level of Competencies
________________________________________________
Mean Scale Descriptive Indicators
Rating
________________________________________________
36.04 – 45.0 Excellent Students have mastered all the
competencies
27.03 – 36.03 Very Good Students have mastered most of the
competencies
18.02 – 27.02 Good Students have mastered at the average
competencies
9.01 – 18.01 Fair Students have mastered few competencies
1.0 – 9.0 Poor Students have mastered very few
competencies
________________________________________________
3 RESULTS AND DISCUSSION
Table 3 shows the pretest mean score performances of
the experimental and control groups in NGEC 9 and
NAV 2 courses. Both the experimental and the control
groups’ pretest mean score performances before the
intervention is described as fair indicating that they
have mastered few competencies.
It also shows the pretest mean score performances
of the experimental and control groups in NAV 4,
NAV 5, SEAM 6, and NAV 7 course. Both the
experimental and the control groups’ pretest mean
score performances before the intervention is
described as poor indicating that they have mastered
very few competencies.
Table 3 Pretest Mean Score Performances of the
Experimental and Control Groups
________________________________________________
Mean Scale Descriptive Indicators Descriptive SD
Rating Rating
________________________________________________
NGEC 9 Experimental 15.20 Fair 5.13
Control 15.70 Fair 3.70
NAV 2 Experimental 11.13 Fair 2.40
Control 10.75 Fair 2.16
NAV 4 Experimental 8.50 Poor 2.01
Control 8.43 Poor 1.92
NAV 5 Experimental 7.95 Poor 1.32
Control 7.60 Poor 1.39
SEAM 6 Experimental 8.98 Poor 1.17
Control 9.08 Fair 1.33
NAV 7 Experimental 6.57 Poor 2.16
Control 6.85 Poor 1.70
________________________________________________
Table 4 shows the posttest mean score
performances of the experimental and control groups
652
in NGEC 9, NAV 2, NAV 4, and NAV 5 courses. Both
the experimental and the control groups’ posttest
mean score performances after the intervention is
described as very good indicating that they have
mastered most of the competencies.
It also shows the posttest mean score performances
of the experimental and control groups in SEAM 6
and NAV 7 courses. Both the experimental and the
control groups’ posttest mean score performances
after the intervention is described as excellent
indicating that they have mastered all the
competencies but the control group for NAV 7 on the
other hand is just very good.
Table 4. Posttest Mean Score Performances of the
Experimental and Control Groups
________________________________________________
Identified Group Mean Descriptive SD
Course Rating
________________________________________________
NGEC 9 Experimental 35.53 Very Good 2.03
Control 35.23 Very Good 2.71
NAV 2 Experimental 36.53 Very Good 2.02
Control 30.02 Very Good 2.30
NAV 4 Experimental 33.41 Very Good 3.12
Control 31.35 Very Good 2.37
NAV 5 Experimental 34.37 Very Good 2.69
Control 35.43 Very Good 2.65
SEAM 6 Experimental 41.18 Excellent 1.65
Control 40.45 Excellent 2.26
NAV 7 Experimental 36.48 Excellent 2.71
Control 32.05 Very Good 2.99
________________________________________________
Table 5 shows that there are no significant
differences on the pretest mean score performances
between the experimental and control groups, for
NGEC 9, U = 791.00, p = .931; for NAV 2, U = 740.00, p
= .560; for NAV 4, U = 791.50, p = .934; for NAV 5, U =
685.50, p = .254; for SEAM 6, U = 740.00, p = .542; and
for NAV 7, U = 788.50, p = .911. This means that
both groups possess the same knowledge in all
identified courses before the intervention. Thus, the
homogeneity of the groups is well established before
the treatment 30].
Table 5. Mann-Whitney Test Result on the Pretest Mean
Score Performances between the Experimental and Control
Groups
________________________________________________
Identified Compared U W Z Asymp. Sig.
Course Group (2-tailed)
________________________________________________
NGEC 9 Experimental 791.00ns 1611.00 -.087 .931
Control
NAV 2 Experimental 740.00ns 1560 -.583 .560
Control
NAV 4 Experimental 791.50ns 1611.50 -.083 .934
Control
NAV 5 Experimental 685.50ns 1505.50 -1.141 .254
Control
SEAM 6 Experimental 740.00ns 1560 -.610 .542
Control
NAV 7 Experimental 788.50ns 1608.50 -.112 .911
Control
________________________________________________
Note. ns means not significant at .05 level of probability.
Table 6 shows that there are no significant
differences on the posttest mean score performances
between the experimental and control groups, for
NGEC 9, U = 716.50, p = .414; for NAV 5, U = 637.50, p
= .115; and for SEAM 6, U = 686.50, p = .267. This
means that both groups possess the same
performance in NGEC 9, NAV 5, and SEAM 6 after
the intervention. This can be inferred that both
methods are similarly effective [31].
It also shows that there are significant differences
on the posttest mean score performances between the
experimental and control groups, for NAV 2, U =
28.00, p = .000; for NAV 4, U = 206.50, p = .000; and for
NAV 7, U = 194.50, p = .000. This means that the
experimental group performed significantly better
after the intervention. The research results support the
findings of Sadhasivam, et al. [32] and Alrahlah [14],
who found that students' posttest scores improved
significantly when compared to their pretest scores.
Table 6. Mann-Whitney Test Result on the Posttest Mean
Score Performances between the Experimental and Control
Groups
________________________________________________
Identified Compared U W Z Asymp. Sig.
Course Group (2-tailed)
________________________________________________
NGEC 9 Experimental 716.50ns 1536.50 -.816 .414
Control
NAV 2 Experimental 28.00* 848.00 -7.464 .000
Control
NAV 4 Experimental 206.50* 1026.50 -5.753 .000
Control
NAV 5 Experimental 637.50ns 1457.50 -1.576 .115
Control
SEAM 6 Experimental 686.50ns 1506.50 -1.110 .267
Control
NAV 7 Experimental 194.50* 1014.50 -5.852 .000
Control
________________________________________________
Note. ns means not significant at .05 level of probability
while asterisk (*) means significant at .05 level of
probability.
Table 7 reveals that there are significant differences
in the pretest and posttest mean score performances
of the experimental groups in all identified courses.
This means that the experimental groups’ mean score
performances after the intervention are significantly
better than before the intervention. This is supported
by the study of Oderinu et al.[33], where PBL
provides higher ability for intellectual stimulation.
Table 7. Wilcoxon-Signed Ranks Test Result on the Pretest
and Posttest Mean Score Performances of the Experimental
Group
________________________________________________
Identified Course Compared Test Z Asymp. Sig. (2-tailed)
________________________________________________
NGEC 9 Pretest -5.52* .000
Posttest
NAV 2 Pretest -5.32* .000
Posttest
NAV 4 Pretest -5.52* .000
Posttest
NAV 5 Pretest -5.52* .000
Posttest
SEAM 6 Pretest -5.53* .000
Posttest
NAV 7 Pretest -5.53* .000
Posttest
________________________________________________
Note. Asterisk (*) means significant at .05 level of probability.
Table 8 reveals that there are significant differences
in the pretest and posttest mean score performances
of the control groups in all identified courses. This
simply shows that the control groups’ mean score
posttest performances are significantly better than
their pretest performance. Evident to its effectivity,
control group showed promise in elevating student
knowledge [34].
653
Table 8. Wilcoxon-Signed Ranks Test Result on the Pretest
and Posttest Mean Score Performances of the Control Group
________________________________________________
Identified Course Compared Test Z Asymp. Sig. (2-tailed)
________________________________________________
NGEC 9 Pretest -5.52* .000
Posttest
NAV 2 Pretest -5.52* .000
Posttest
NAV 4 Pretest -5.52* .000
Posttest
NAV 5 Pretest -5.52* .000
Posttest
SEAM 6 Pretest -5.54* .000
Posttest
NAV 7 Pretest -5.53* .000
Posttest
________________________________________________
Note. Asterisk (*) means significant at .05 level of probability.
Table 9 presents the mean gains of the
experimental and control groups. It shows that the
mean gains of most identified courses is higher in the
experimental group than the control group. It can be
inferred that the experimental group showed
significantly better performance as compared to the
control group. This was also inferred by the study of
Delucci [35], where knowledge is already present
however, the one with a better intervention can
effectively widen the gap. However, in NAV 5, the
mean gain in the control group is higher than the
experimental group. It can be gleaned that the control
group is as effective as the experimental group. Given
the established fact that PBL is effective on other
subjects, it is inferred that the most effective
instruction is interchangeable. Furthermore, the
subject requires simulation and immediate support
[36].
Table 9. Mean Gains of the Experimental and Control
Groups
________________________________________________
Identified Compared Pretest Posttest Mean Gain
Course Group
________________________________________________
NGEC 9 Experimental 15.20 35.53 20.33
Control 15.70 35.23 19.53
NAV 2 Experimental 11.13 36.53 25.40
Control 10.75 30.02 19.27
NAV 4 Experimental 8.50 33.41 24.91
Control 8.43 31.35 22.92
NAV 5 Experimental 7.95 34.37 26.42
Control 7.60 35.43 27.83
SEAM 6 Experimental 8.98 41.18 32.20
Control 9.08 40.45 31.37
NAV 7 Experimental 6.58 36.48 29.90
Control 6.85 32.05 25.20
________________________________________________
Table 10 shows that there are no significant
differences in the mean gains of the experimental and
the control groups for NGEC 9, U = 737.50, p = .546;
for NAV 5, U = 608.50, p = .063; and for SEAM 6, U =
663.50, p = .182. This suggests that both intervention is
effective in delivering instructions across three
subjects. According to Sniegocki [37], Nav 5
(Operational use of RADAR/ARPA) requires
systematic and closely guided instruction. The NGEC
9 and Seam 5 on the other hand, focuses on
achievement rather than application as attested in the
study Laurens et al. [38]. Mustaffa et al. [39] largely
disproves these results as NGEC 9 and SEAM 5 shares
the same roots. Nevertheless, traditional instruction is
as effective as the PBL as shown by the results.
While there are significant differences in the mean
gains of the experimental and control groups for NAV
2, U = 150.00, p = .000; for NAV 4, U = 146.50, p = .000;
and for NAV 7, U = 226.50, p = .000. This means that
one of the groups perform better than the other
groups in NAV 2, NAV 4, and NAV 7 after the
intervention. The experimental group having the PBL
approach is significantly better as compared to the
control group as shown on the mean gains. It can be
inferred that the intervention which is the PBL
approach is effective than the traditional method.
Since PBL focuses on student-centered education, the
application across three subjects denote appropriate
approach in scaffolding student cognition and critical
thinking [40] [41].
Table 10. Mann-Whitney Test in the Mean Gains of the
Experimental and the Control Groups
________________________________________________
Identified Compared U W Z Asymp. Sig.
Course Group (2-tailed)
________________________________________________
NGEC 9 Experimental 737.50ns 1557.50 -.604 .546
Control
NAV 2 Experimental 150.00* 970.00 -6.280 .000
Control
NAV 4 Experimental 146.50* 966.50 -6.308 .000
Control
NAV 5 Experimental 608.00ns 1428.00 -1.857 .063
Control
SEAM 6 Experimental 663.00ns 1483.00 -1.335 .182
Control
NAV 7 Experimental 226.50* 1046.50 -5.546 .000
Control
________________________________________________
Note. ns means not significant at .05 level of probability while
asterisk (*) means significant at .05 level of probability.
The effectiveness of the PBL in terms of students’
performance in NGEC 9 is quantified using the
Cohen’s d effect size. The value of the effect size is 0.2.
This means that the effect size is small and the
intervention is slightly effective compared to the
traditional method which is lecture-discussion. NAV 2
is 3.01. This means that the effect size is very large and
the intervention is very effective compared to lecture-
discussion. This means that the effect size was very
large and the intervention was more than a 100%
effective [42]. NAV 4 is 0.7. This means that the effect
size is medium and the intervention is moderately
effective compared to the lecture-discussion. NAV 5 is
0.4. This means that the effect size is small and the
lecture-discussion is slightly effective compared to the
intervention applied. SEAM 6 is 0.4. This means that
the effect size was small and the intervention is
slightly effective compared to the lecture-discussion.
NAV 7 is 1.55. This means that the effect size is large
and the intervention is effective compared to the
lecture-discussion. This means that the effect size is
large and the intervention was more than a 100%
effective [43].
654
Table 11. Effect Size, Descriptive Rating, and Interpretation
________________________________________________
Course Effect Descriptive Interpretation
Size Rating
________________________________________________
NGEC 9 0.2 Small PBL is slightly effective compared
to lecture-discussion
NAV 2 3.01 Very Large PBL is very effective compared to
lecture-discussion
NAV 4 0.7 Medium PBL is moderately effective
compared to lecture-discussion
NAV 5 0.4 Small Lecture-discussion is slightly
effective compared to PBL
SEAM 6 0.4 Small PBL is slightly effective compared
to the lecture-discussion
NAV 7 1.55 Large PBL is effective compared to the
lecture-discussion
________________________________________________
4 CONCLUSIONS
The experimental group appeared to have learned
significantly better in most identified courses after
having been subjected to the PBL approach than the
control group. It was shown that the PBL approach
was an effective teaching styles in almost all identified
courses.
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