-
Comparative Analysis of Two Instructional Strategies and Their
Impacts on Selected University
Engineering Students Performances in Particle Technology
Kevon R. McAnuff & Simon M. Yalams University of
Technology
Kingston, Jamaica
Abstract This study examined the effects of active learning and
traditional lecturing on the academic performance of Particle
Technology students in order to identify the more effective
teaching strategy. Two active learning models, namely, cooperative
and collaborative learning were used. The population of the study
consisted of thirty-eight third year students enrolled in the
Bachelor of Engineering in Chemical Engineering program in one of
the universities in one of the Caribbean Island. The post-test only
control group experimental design was employed for the study while
the instruments used to collect data were midterm tests and a final
examination. The data collected was subjected to an independent
t-test analysis ( = 0.05), using the SPSS statistical software
application. The findings indicated that students taught with
traditional lecturing performed significantly better (mean P =
0.01) than those taught using active learning strategies. Males and
female participants taught with traditional lecturing also
performed better than their counterparts taught with active
learning. Based on the findings of the study, it was recommended
that students be better sensitized about new teaching strategies
being implemented, Particle Technology teachers recognize the value
of traditional lecturing, appropriate measures be implemented to
achieve comparable attendance among study groups and future studies
should focus on understanding the characteristics of female
students which results in them exhibiting enhanced learning
compared to their male counterparts.
Keywords-comparative;engineering; instructional; strategies;
performances; particle technology
I. INTRODUCTION Active learning strategies are viewed by many as
a
fundamental change from traditional teaching methods. As such it
has received substantial attention over the past several years.
However, there remains some uncertainty as to the necessity for
these methods in engineering education since students are already
active through practical homework assignments and laboratory
experiments. Beside, many engineering educators lack the interest
to examine the educational literature for answers and consequently
do not always appreciate the difference between the common forms of
active learning. There are also drawbacks for engineering faculty
expecting to select a few articles to see the effectiveness of
active learning strategies. Readers must take care to understand
the subject of the study as well at the
authors methods of data collection and interpretation. However,
the subject of the study might not necessarily be obvious as a
result of the broad range of methods which are presented as active
learning. This process cannot be eliminated but its complexity can
be greatly reduced if one focuses on the fundamental aspects of
common active learning methods. According to [1], in order to
assess what works, care must be taken in interpreting data, various
learning outcomes must be considered and reported improvement
should be properly quantified. While the use of statistics assist
in the presentation of learning outcomes, it does not eliminate the
need for interpretation when evaluating for significance. Educators
should not expect that simply adopting a particular educational
method will result in similar learning outcomes to those reported
in educational studies as the practical limitations of these
studies must also be considered. This approach is supported by [1]
who opined that educational studies only tell us what worked, on
average, and specifically for the populations examined.
Nevertheless, according to [2], if the data supporting a particular
learning model is extensive and a teachers students also resemble
the test population, there is a greater possibility that similar
results will be obtained. Alternatively, educators should also view
the findings presented in literature as a means to identify the
variables involved in educational studies.
Teaching models which incorporate active learning strategies
continue to receive widespread support from modern literature on
classroom instructional modes which suggest that these strategies
result in more meaningful learning when compared to traditional,
passive lectures with regards to retention of material, motivating
students and developing thinking skills [3]. This was supported by
[4] who went further to state that active learning also improved
students performance, as measured by traditional tests, and also
created positive students attitudes towards the learning process.
Moreover, the multiple learning styles included in active learning
strategies conform to educational models based on theories of
learning and motivation. However, not all of these supports for
active learning are compelling. For example, [5] conceded that the
measured improvements of learner-centered over instructor-centered
instructional strategy on students learning in two online courses
were small, and concluded that
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the principles lack substantial evidence with respect to
empirical support for active learning. Nonetheless, active learning
models continue to receive huge support from educational
literature. Still, given the range of instructional methods
presented as active learning, what is being endorsed by the
literature is not always apparent and therefore it can be quite
confusing interpreting the findings of educational studies.
Consequently, active learning should be thought of as an approach
and not as a method and so the various methods are best assessed
independently.
Active learning can be achieved by introducing students activity
into the traditional lecture sessions. Reference [2] highlighted
the use of one such approach called the concept tests method in
their Unified Engineering class. This involved incorporating brief
multiple-choice conceptual questions into lectures to test students
knowledge of the material. Additionally, the lecturer only
introduced new material when a majority of the class did well on a
question. On the other hand, students were placed in small groups
to work out the answer to the question when the concept tests
revealed conceptual problems or misunderstandings. When students
were asked to compare the active learning techniques to the
traditional lecture format, their responses reflected an overall
positive attitude towards the active learning techniques.
Specifically, some students commented on the effect of the active
learning techniques on improving their learning and understanding
of the content, and in stimulating their thinking and classroom
participation. Another important component of active learning
highlighted by [4] is the type of activity, as this influences how
much material students retained. Essentially, students should be
thoughtfully engaged and activities designed around important
learning outcomes. There is little doubt as to the significance of
students engagement as there is substantial evidence to support its
effectiveness on a wide range of learning outcomes.
1) Collaborative Learning Model Collaborative learning may be
used to describe any
instructional method in which students work together in small
groups to accomplish a common task. Consequently, this model can be
viewed as encompassing all group-based instructional methods,
including cooperative learning [7]. Reference [4] however, stated
that some authors indeed distinguish between collaborative and
cooperative learning as having distinct historical developments and
different philosophical roots. Interpretation aside, it is
important to understand that the principal element of collaborative
learning is students interactions and not solely learning. There is
strong agreement among the findings of various educational studies
probing the question of how collaboration influences learning
outcomes. In a review of 168 studies, [8] found that cooperation
improved learning outcomes relative to individual work across the
board. Similar results were found by [9] who looked at 37 studies
of students in science, mathematics, engineering and technology. In
a related study investigating the effect of incorporating small,
medium and large amounts of group work on achievement, [9] sought
to determine if the benefits of group work improve with frequency.
The positive effect sizes associated with low, medium and high
amount of
time in groups were found to be 0.52, 0.73 and 0.53,
respectively. Interestingly, the highest benefit was found for
medium time in groups and not for large time in groups. On the
contrary, evaluating the effects of frequency of group work on
promoting positive students attitudes revealed that more time spent
in groups did however produce the highest effect. The effect sizes
reported were 0.37, 0.26, and 0.77 for low, medium and high amount
of time in groups respectively. These attitudinal results must
however be interpreted with caution as the authors admitted that
they were based on a relatively small number of studies.
2) Cooperative Learning Model According to [4], this model can
be defined as a
structured form of group work where students pursue common goals
while being assessed individually. The cooperative learning model
proposed by [1] is the most common found in the engineering
literature [1]. This model is characterized by five specific
tenets, namely, face-to-face promotive interaction, mutual
interdependence, appropriate practice of interpersonal skills,
individual accountability, and regular self-assessment of team
functioning. The principal feature among the different cooperative
learning models highlighted by [7] is a focus on cooperative
incentives as oppose to competition to promote learning. Increased
higher-order thinking skills and improved students performance are
among the benefits of cooperative group learning outline in the
findings of much of the educational research. Cooperation has also
been credited with fostering self-esteem, promoting interpersonal
relationships and improving social support. Still, the rather
stringent criteria and time needed for successful learning causes
many instructors to hesitate when considering the use of
cooperative learning models. The fact that cooperative learning
models create a setting which promotes interpersonal skills and
effective teamwork would also interest engineering faculty. In
addition, engineering program accreditation bodies such as the
Accreditation Board for Engineering and Technology (ABET) call for
engineering students to acquire these skills [6]. The lack of team
skills displayed by engineeering students was also noted as a
frequent concern among employers. Therefore, the development of
these skills in engineering students could also lead to better
integration in the industry. Furthermore, it would be quite
difficult to put forth an argument that individual work such as
that taking place in traditional lecture classes helps to build
team skills given that practice is a precondition of learning any
skill. It is not always easy to ascertain whether cooperative
learning effectively develops interpersonal skills as how one
defines and measures team skills must be taken into consideration.
Even so, strong arguments are put forward by [8] to support the
view that cooperative learning is indeed effective in this area.
Additionally, when cooperative learning groups are used, they
recommend that students be explicitly trained in the skills
required to be effective team members. Since traditional
instruction focuses on individual learning and typically does not
include explicit instruction in teamwork, it is fair to assume that
it would be less effective than the opportunity to practice
interpersonal skills while getting explicit instructions in these
skills. Empirical evidence to support this conclusion was provided
by [10] who studied the effects of competitive
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and cooperative learning strategies on academic performance of
Nigerian students in mathematics. Furthermore, the authors went on
to state that cooperative strategies resulted in a greater increase
in social skills when compared to competitive or individual
situations. These findings are in agreement with a study conducted
by [11] which reported an increase in students interpersonal skills
necessary for effective teamwork as a result of employing
cooperative learning strategies.
In one of the Islands in the Caribbean, many of our educational
institutions employ passive learning through traditional lecturing
and as a result active learning strategies are sparsely used. In
contrast, many researchers support the use of active learning which
they have found to increase retention, foster team building and
develop higher level thinking skills [3]. The main problem that the
study sought to investigate was which of these learning strategies
will bring about better performances from the students enrolled in
the Particle Technology module. The study was guided by the
following questions: 1.) Which of the two instructional approaches
(active learning and traditional lecturing strategy) used for
teaching Particle Technology students yields better students
academic performance? 2.) Do Particle Technology students
significantly differ in their academic performances based on the
two methods of teaching (active learning and traditional lecturing
strategy) used? and 3.) Do Particle Technology students taught with
active learning strategies and traditional lecturing significantly
differ in their academic performances based on gender?
II. METHODOLOGY The experimental design adopted for this study
was
the Post-test Only Control Group Design. This design was chosen
because of its strength against single-group and multiple-group
threats to internal validity [12]. Typically, a pre-test is used to
assess whether the groups are comparable at the beginning of the
program. However, since random assignment was used in the formation
of the groups, it then could be assumed that the two groups are
probabilistically equivalent initially and therefore the pre-test
was not required. In this design, the primary focus of the
researchers was determining whether the two groups are different
after the program. The groups performance on three assessments were
measured and then compared by testing for the differences between
the means using a two-tailed independent t-test with a 95%
confidence interval ( = 0.05). This t-test was done using the SPSS
statistical analysis software and the t-value (t), degrees of
freedom (df) and p-value (Sig. (2-tailed)) reported. The t-value is
the ratio of the difference between the mean of both groups and the
standard error of the difference. The degree of freedom is
calculated by adding the two sample sizes then subtracting two when
equal variance can be assumed. If equal variance cannot be assumed
it is then calculated using the Satterthwaite formula. The p-value
is the two-tailed probability obtained from the t distribution
which gives the probability of observing a t-value of equal or
greater absolute value under the null hypothesis. The null
hypothesis being that there is no significant difference between
the mean score of both groups.
1) Participants The study was conducted in the chemical
engineering
program at a popular university in one of the Islands in the
Caribbean. The participants in this study were 38 third-year
students (16 females and 22 males between the ages of 21 and 24).
These students were enrolled in the compulsory Particle Technology
module. Particle Technology is a three (3) credit module designed
to give students a clear understanding of the characteristics of
particles and how these characteristics determine such prosperities
as its density and conductivity, the surface per unit volume and
the interaction between particles and fluids. The module also
focuses on some physical unit operations involving particle
enlargement, reduction, separation and blending as well as the
design and analysis of several equipment involved in these
processes. The module consisted of a two hours lecture session in
addition to two one-hour tutorial sessions per week. The lecture
sessions were attended by all students while the class was divided
into two groups, A and B, with each group attending a single
tutorial session per week.
2) Instruments The instruments used to assess students
performance
were two midterm tests and a final examination. The first
midterm tests was given at the end of the second unit and assessed
major concepts covered in units one and two while the second
midterm test was given at the end of the fourth unit and assessed
major concepts covered in units three and four. Both tests had
duration of two hours and comprised of three problems in the form
of short answer and restricted essay items in which the students
had to carry out numerous calculations. At the completion of the
module, students were given a summative assessment in the form of a
comprehensive final examination, which was used to test students
overall understanding of the major concepts covered in the module.
The examination comprised one short answer item and three
restricted essay items and required students to perform various
calculations. Students were required to answer all questions within
the allotted duration of two hours. A formula sheet was also
provided. In order to determine whether the research instruments
truly measure that which they were intended to measure or how
truthful the research results are, the instruments were assessed
for face and content validity. The content validity was done using
a method advocated by [13] for gauging agreement among raters or
judges regarding how essential a particular item is. This formula
yields values, which range from +1 to -1. The content validity
ratio for individual test items ranged from 0.2 to 1.0 and 0.47 to
0.87 for the overall test instruments. This indicates that the
instruments had sound content validity as positive ratios mean that
more than half of the expert raters rated the knowledge being
measured by the items as being essential. In order to assess the
reliability of the instruments, the inter-rater method was used.
The reliability of individual test items ranged from 0.6 to 1.0 on
a scale of 0.0 to 1.0. This indicates that the research instruments
had good reliability, as there was at least 60% agreement between
the expert raters. The reliability for the overall test instruments
were even higher ranging from 0.73 to 0.93.
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3) Procedure Firstly, the third year chemical engineering
class
which consists of 38 students was initially randomly divided
into two groups of equal size, groups A and B. Therefore, there was
no sampling error as the entire population was used for this study
based on the small size of the groups. However, due to absenteeism
of some participants in both groups, the group sizes had to be
revised to capture those who actually took part in the study. That
is, those who were present for at least half of the sessions. In
the final analysis Group A was reduced to 17 members while Group B
reduced to 14 members. Both groups had two hours of joint lecture
and one hour of separate tutorial sessions each week. It is in
these tutorial sessions that the variation in instructional
strategies was employed. Group A was used as the traditional
lecturing group while Group B was the active learning group. In the
traditional lecturing sessions, there were no active learning
exercises or cooperative/collaborative group activities. PowerPoint
slides presentation was used to deliver lessons and one of the
researchers solved all examples on the whiteboard. Socratic
questions were asked during lecture and volunteer answers
solicited. Conversely, in the active learning sessions for group B,
active learning strategies in the form of cooperative and
collaborative exercises were employed. Students worked together on
problems in a small group setting until all members of the group
understood the problem and completed it. The main class activities
used included the jigsaw method, think-pair-share, round robin,
brainstorming and debates to name a few. In order to assess
students performance two midterm tests and a comprehensive final
examination were administered. The first midterm test was given at
the end of the second unit and the other at the end of the fourth
unit while the final examination, which covered the entire module
content, was given at the end of the module.
III. RESULTS
a) Research question 1: Which of the two instructional
approaches (active learning and traditional lecturing strategy)
used for teaching Particle Technology students yields better
students academic performance?
To answer this question, the mean of participants score on each
instrument was calculated for each group and then compared. Fig. 1
presents a comparison between the mean score of group A and group B
participants on each of the instruments.
As can be seen in Fig. 1, the results indicate that students
taught with traditional lecturing (group A) yielded better academic
performances than those taught with active learning strategies
(group B) on all the instruments. The largest difference between
the mean performance of each group was observed in test 2 (20.9
percentage points) while the difference in the mean performance of
both groups in test 1 and the final examination were approximately
equal (18.1 percentage points on test 1 compared to 18.4 percentage
points on the final examination).
Fig. 1. Mean scores for group A and group B participants on each
test instrument.
b) Research question 2: Do Particle Technology students
significantly differ in their academic performances based on the
two methods of teaching (active learning and traditional lecturing
strategy) used?
To answer this question, participants performances on the
various test instruments were subjected to an independent t-test
analysis to establish whether the difference between the
performances of participants taught with traditional lecturing
(group A) and those taught with active learning strategies (group
B) was significant. This analysis was carried out using the SPSS
software applications with a confidence interval of 95% ( =
0.5).
As can be seen in Table 1, there was a significant difference in
the scores for group A and group B participants on all three
assessments, with group A participants recording higher scores than
those in group B. These results suggest that active learning
strategies do not have a positive effect on participants
performance. Specifically, the results suggest that when
traditional lecturing is used, participants performance
improved.
TABLE 1: T-TEST ANALYSIS OF PARTICIPANTS SCORE ON EACH
ASSESSMENT
Ass
essm
ent
Gro
up
N
Mea
n
Std.
Dev
.
t df
Sig.
(2
-tai
led)
A 17 56.12 17.87 Test 1
B 14 38.04 18.58 2.75 29 0.010
A 17 82.82 11.77 Test 2
B 14 61.93 19.84 3.47 20.25 0.002
A 17 66.24 14.42 Final Exam B 11 47.82 19.31 2.89 26 0.008
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c) Research question 3: Do Particle Technology students taught
with active learning strategies and traditional lecturing
significantly differ in their academic performances based on
gender?
In order to establish whether the observed differences between
the mean performances of male and female participants taught with
traditional lecturing (group A) and those taught with active
learning strategies (group B) was significant, the data was
subjected to an independent t-test analysis using the SPSS software
application with a confidence interval of 95% ( = 0.5).
Table 2 presents the results of the statistical analysis
conducted on the mean scores of female participants in groups A and
group B on each assessment. As can be seen, there was a significant
difference between the scores of group A and group B female
participants on midterm Test 1 and the Final Examination. These
results suggest that female participants taught with traditional
learning performed significantly better than their counterparts
taught with active learning strategies. However, for midterm Test
2, there was no significant difference between the scores for group
A (M=89.43, SD=8.87) and group B (M=75.50, SD=18.35) female
participants; t (11) = 1.789, p = 0.101. This suggests that there
is no significant difference between the performance of female
participants taught with traditional learning and those taught with
active learning strategies.
Table 3 presents the results of the statistical analysis
conducted on the mean scores of male participants in groups A and B
on each assessment. As can be seen, there was a significant
difference in the scores for group A and group B male participants
on all three assessments with group A participants recording higher
scores than those in group B. These results suggest that active
learning strategies do not have a positive effect on male
participants performance. Specifically, the results of the analysis
suggest that male participants taught with traditional learning
performed significantly better than their counterparts taught with
active learning strategies.
TABLE 2: T-TEST ANALYSIS OF FEMALE PARTICIPANTS SCORE ON EACH
ASSESSMENT
Ass
essm
ent
Gro
up
N
Mea
n
Std.
Dev
.
t df
Sig.
(2
-tai
led)
A 7 70.29 12.98 Test 1
B 6 46.33 21.66 2.465 11 0.031
A 7 89.43 8.87 Test 2
B 6 75.50 18.35 1.789 11 0.101
A 7 69.86 12.56 Final Exam B 6 54.00 13.16
2.220 11 0.048
TABLE 3: T-TEST ANALYSIS OF MALE PARTICIPANTS SCORE ON EACH
ASSESSMENT
Ass
essm
ent
Gro
up
N
Mea
n
Std.
Dev
.
t df
Sig.
(2
-tai
led)
A 10 46.20 13.78 Test 1
B 8 31.82 14.24 2.169 16 0.045
A 10 78.20 11.67 Test 2
B 8 51.75 14.64 4.273 16 0.001
A 10 63.70 15.72 Final Exam
B 5 40.00 24.29 2.266 13 0.041
IV. DISCUSSION From the results, it can be seen that the
test
instruments showed a high level of content validity and
reliability. This can be attributed to the fact that all
instruments were constructed to be in close agreement with the
module outline. Therefore, individual test items were designed to
assess one or more specific objectives to determine if the
participants have satisfied the desired learning outcomes. The
statistical analysis conducted on both mid-semester examinations as
well as the final examination found p values ranging from 0.001 to
0.01 which indicates that there was a significant difference
between the mean of both groups. In all three instances, the mean
for Group A (ranging from 56.12 to 82.82) was found to be higher
than that of Group B (ranging from 38.04 to 61.93). These findings
indicate that participants taught with traditional instructional
strategies performed better than those taught with active learning
strategies. Since these assessments were announced well in advance,
participants had sufficient time to build on the concepts they were
introduced to in the various sessions. Therefore, the results could
be interpreted to suggest that participants in the active learning
group (Group B) did not sufficiently grasp the basic concepts being
conveyed and therefore could not make significant addition to their
knowledge base. These findings disagreed with that of [6] who
examined the performance of over 90 students in five chemical
engineering courses and found significantly improved performance
for students in classes with extensive use of active and
cooperative learning techniques as opposed to students taught using
the traditional approach. The active learning group outperformed
the control group on several measures among which are retention and
graduation in chemical engineering. Additionally, a significantly
larger number of the graduates in this group opted to pursue
further study in chemical engineering. It must be noted however,
that [6] conducted a longitudinal study, which spanned the entire
period of the participants course of study. This would have given
the participants the opportunity to fully develop an appreciation
for the active learning strategies. This argument is supported by
[8], who provided strong arguments to suggest that training
participants to be effective team member will increase the
probability of success when using cooperative learning groups.
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The data analysis also revealed that male and female
participants taught with traditional lecturing (group A) performed
better than their counterparts taught with active learning
strategies (group B). Female students taught with traditional
lecturing achieved up to 24.0 percentage point higher academic
performance when compared to their female counterparts taught with
active learning strategies. Similarly, male participants taught
with traditional lecturing achieved up to 26.4 percentage point
higher academic performance when compared to their male
counterparts taught with active learning strategies. These findings
are in contradiction to that conducted by [5] which examined the
impact of instructor-centered versus learner-centered instructional
strategy on students learning in two online courses and found no
significant difference across treatment groups. The lower academic
performance witnessed among participants taught with active
learning strategies could be due to the fact that this was the
first time they have been involved with the use of active learning
strategies on such an extensive basis. Reference [9] conducted a
study in which the effect of utilizing large, medium and small
amounts of group work on achievement was investigated and found
positive effect sizes associated with large, medium and small
amount of time in groups to be 0.53, 0.73 and 0.52, respectively.
Interestingly, the highest achievement was not found for large time
in groups but for medium time in groups. This suggests that the use
of extensive group work will not necessarily result in higher
performance. Rather a balance between group and individual work
should be sought. One possibility is the fact that, too much group
work can lead to some members not being given a chance to process
the material in their own time (self-discovery) but rather being
told the solutions by other members. This could then lead to some
members of the group not being able to properly develop their
critical thinking capabilities. In addition, the participants were
being exposed, almost exclusively, to traditional instructional
methods over their previous two years at the university. Even
during the period of this study, participants were enrolled in
other module in which instructors also used traditional methods.
Since these methods allow participants to remain passive, they
could view active learning strategies in a negative light by
requiring them to do more work. This could also explain the lower
level of attendance recorded for the active learning group (Group
B) when compared to the group exposed to traditional methods (Group
A). Additionally, the introduction of different active learning
strategies could also have resulted in some of the participants
being more fascinated and grossly involved with the social
interaction aspects so much that they lost tract of the main
objectives of the lesson, thus achieving lower academic
performances.
Another important factor, which could greatly influence the
performance of the participants, is their average class attendance.
As was presented in the results, the average attendance for
participants taught with traditional learning strategies (Group A)
was found to be 66% while that observed for the participants taught
with active learning strategies (Group B) was 58%. Therefore, the
consistently higher scores recorded by Group A participants (male
and female) when compared to their counterparts in group B could be
attributed to their higher rate of class attendance which resulted
in them
having a longer contact time with one of the researchers who in
this case was the lecturer directly involved with the module. This
low average attendance observed for participants in this study can
also be linked to the universitys policy, which regards students as
adult learners capable of making responsible decision, and
therefore does not mandate students to attend class.
While these results contradicts many of the studies conducted as
seen in the review of the literature for instance, [1] cautioned
that educational studies only tell us what worked, on average, and
specifically for the populations examined. Educators should not
expect that simply adopting a particular educational method will
result in similar learning outcomes to those reported in
educational studies as the practical limitations of these studies
and the complex nature of the learning process must also be
considered. This complexity of interpreting research finding was
highlighted by [5] who measured small improvements of discussion
over lecture in his study but still conceded that the principles
lacked substantial evidence with respect to empirical support for
active learning.
V. CONCLUSION AND RECOMMENDATIONS Although the increasing body
of educational research
seems to suggest that active learning strategies prove to be
more effective than traditional lecturing methods, whether that
premise holds for teaching engineering modules is yet to be
determined. In this study, active learning strategies were
evaluated with a view to determine if they were, indeed, more
effective than traditional lecturing in improving students academic
performance in an engineering module and, if so, to what extent.
The research findings revealed that there is a significant
difference between the academic performances of Particle Technology
students based on the two methods of teaching (active learning and
traditional lecturing strategy) used, which favors traditional
lecturing. The revelation persisted even when students academic
performances were compared based on gender. Interestingly though,
male and female Particle Technology students taught with
traditional lecturing approach significantly differ in their
academic performances while male and female students taught with
active learning strategies did not differ significantly in their
academic performances. Thus, the findings of this study provide
empirical evidence contrary to common beliefs about the greater
effectiveness of active learning strategies compared with
traditional lecturing in developing students engineering
skills.
Based on the findings of this study, the following
recommendations were made:
1. Students should be sensitized as to the nature of active
learning strategies as well as possible benefits in order to
alleviate concerns of additional workload and limited supports.
2. Particle Technology teachers should not rely completely on
active learning strategies but rather recognize the value of
traditional lecturing as an effective learning strategy in order to
improve students performances.
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3. Future studies should be conducted with appropriate measures
in place to achieve comparable attendance among the students in
both study groups. This would convincingly remove any potential
confounding effects associated to attendance, and would reaffirm or
refute this finding.
4. Again, because this approach has not been tried on other
engineering modules other than Particle Technology, doing so is
highly recommended especially on varied population and sample size
in order to authenticate further this finding.
5. Further research in this area is also warranted which should
focus on understanding the characteristics of female students that
possibly resulted in them exhibiting enhanced learning under both
models when compared to their male counterparts.
6. The study also recommends that a replication of this
experiment be done in other occupational education areas such as
Technical and Vocational Education modules which share certain
characteristics with engineering in order to confirm or refute
these findings.
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978-1-4673-6109-5 /13/$31.00 2013 IEEE Technische Universitt
Berlin, Berlin, Germany, March 13-15, 20132013 IEEE Global
Engineering Education Conference (EDUCON)
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