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Educational technology for the formation of project competence for engineering students

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Vol. 11 (2024)

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Articles

Educational technology for the formation
of project competence for engineering students

Liudmyla V. Hapon-Baida[0000-0003-0352-9447]

and Tetiana M. Derkach[0000-0003-1087-8274]

Kyiv National University of Technologies and Design,

2 Mala Shyianovska Str., Kyiv, 01011, Ukraine

[email-masked], [email-masked]

Abstract. Project competence is essential to the professional education
of engineering students. It synchronously affects all three components
of future professional activity, forming the ability to be creative,
carry out scientific research and apply modern technological solutions.
However, there often is a lack of attention to master projecting in
educational programs, especially for junior undergraduate students. The
article describes the developed educational technology for organising
project-based learning (PjBL) in the actual educational process
conditions to mould engineering students’ project competence. It was
based on incorporating a short module dedicated to mastering the basic
principles of PjBL into the existing curriculum. During the module,
students developed, executed and publicly defended their projects. The
choice of topic was up to the students, provided the project was dedicated
to waste management. The mastery of the seven PjBL essential elements
was considered an indicator of the level of project competence formation.
Conducting research in the current educational process put forward
strict limitations regarding the project execution time, their permanent
adjustment through feedback, and timely evaluation. Short daily surveys
via Google Forms devoted to each lesson topic let one organise permanent
feedback between the teacher and students. The effectiveness of the
applied technology was evaluated by two more detailed surveys at the
beginning and after the end of the training. The understanding of PjBL
elements was noticeably improved. The improvement was statistically
significant for four elements, while for the remaining three, it was
borderline.

Keywords: project-based learning · project design elements · learning
styles · survey using Google Forms · development of reflexivity

1 Introduction

The needs of the modern world require producers and consumers to be economical
with the consumption of natural resources and switch to other types of materials,
resources, and technologies to reduce the burden on the environment and human
health. It is related to the idea of conscious consumption or the idea of sustainable
development [26, 35].

Almost ten years ago, the UN formulated 17 sustainable development goals to be
achieved by 2030 [15, 17]. Subsequently, the goals were structured into four main
types of sustainability: human, social, economic, and environmental. In turn,
socioeconomic changes place specific requirements on engineering education. Namely,
they require from future specialists new knowledge, abilities, skills and professionally
important internal qualities that contribute to the ability to quickly adapt to changes
caused by technological advances, such as the appearance of new materials, devices
and technical processes, as well as satisfy the demands of consumers and the labour
market.

In other words, multidisciplinary training comes to the fore when the learner
simultaneously and synchronously acquires skills and abilities that ensure the
fulfilment of the UN’s human, social, economic and environmental tasks. The
fulfilment of these tasks requires the simultaneous development of three main
components of professional activity: creative, scientific and technological.
The creative component is oriented (first of all but not only) to achieving
human and social goals of sustainable development. The development of the
scientific component is closely related to the economic aspect of sustainable
development, which consists of innovation, the financial income of companies without
harming the environment, and the development of conscious production in
balance with conscious consumption. The technological component is based
on the processes of development, manufacture, and processing of products
and industrial waste following established technological and environmental
requirements. Accordingly, the ecological tasks of sustainable development are
primarily related to technologies, their development level, and specialists’
training.

The synchronous development of these main components of professional activity is
a complex problem and depends strongly on educational programs and current
education standards. The imbalance of these documents often prevents the
achievement of desired learning outcomes. Even though the concept of the
competence approach dominates in Ukraine, it is not always supported by relevant
defined skills and abilities in the context of individual specialities. In particular,
insufficient attention is paid to developing the ability to design for many engineering
and technological study fields [25].

For example, graduates of creative specialities must demonstrate a pronounced
creative component (due to mastered creativity) along with the practical component
of their activity. It is a requirement of the modern labour market. However, there is a

discrepancy between this requirement and the approved educational standards. For
one speciality, competence “creativity” is defined as being without competence in
project activity, and in another related program, on the contrary, there is projecting
without creativity. In training for a bachelor in the speciality “Professional Education
(by specialisation)”, such competencies as creativity and the ability to design are not
defined.

Purposeful correction of the training content cannot be done without
preliminary studies to identify the effectiveness and feasibility of proposed
changes. It is especially relevant for the modern conditions of the development
of information and communication technologies when new, more and more
sophisticated technologies and approaches to the learning process appear every year
[21, 30, 31, 37, 41].

Traditional long-term pedagogical research takes years, which is not always
acceptable when changes in the pedagogical process, primarily due to developing
new technologies, occur much faster. There is a demand for designing and
conducting short-term studies to help solve the problems of adjusting training
courses.

The research, aimed at bringing professional competencies to the modern
requirements of the labour market by optimising the content of educational
disciplines, helps to overcome this challenge and, therefore, is a topical scientific
problem. It is known from the literature that project-based learning (PjBL) is quite
popular and has certain advantages over traditional learning methods. Project-based
learning contributes to the long-term preservation and development of knowledge,
skills, and abilities [34]. It also contributes to a better understanding of the
educational material, increases self-motivation, activates the learning process, and
develops creativity [7, 8]. Intellectual skills are formed: skills in the subject field of
expertise (subject competencies), intellectual skills of critical thinking (search for
information, awareness, analysis, synthesis, application, and evaluation), and
communication skills (skills of joint activities, the ability to lead a discussion, and
make decisions [2].

According to traditional teaching methods, students must memorise a certain
amount of knowledge. Instead, using PjBL, the student should understand the basic
principles of projecting from the stage of its development to implementation and
public defence and learn to apply them to various situations in life and study. Thus,
we are talking about possessing tools that will help solve new, unknown tasks in the
future.

At the same time, using project-based learning as the main educational technology
is very rare. The writing of term papers and qualifications can be mentioned, while
the academic disciplines are mostly taught using more traditional approaches. They
are mainly aimed at mastering some specific issues, some of which have a technical
orientation, and others are socially oriented [1, 32]. Usually, there is a lack
of disciplines that would consolidate knowledge at a higher, generalising
level.

Such a situation contradicts the requirements of training specialists to
work in conditions of sustainable development when awareness of the task

at different levels comes to the fore. It requires appropriate technological,
ecological and economic knowledge and skills in landscape restoration and
nature-based solutions [6, 9]. Moreover, even when subjects that seem aimed at
forming a more general picture are considered, the situation remains similar
[4].

The educational programs are fully loaded and scheduled. Therefore, to improve
them, for example, using project-based learning, the tactics of incorporating short
dedicated modules into existing educational components is most promising. Initially,
such modules are temporarily integrated into existing academic disciplines. In the first
attempts, they are used for experiments to optimise the training content. When stable
positive results are obtained, new modules will be permanently introduced into the
curriculum.

There is a problem with conducting research using project-based learning in a real
educational process when experimental tasks “fit” into the program on the go and do
not have particular preferences. The need to intervene in the existing educational
process imposes several restrictions. First, the investigation must be balanced over
time because the integrity of the student’s perception of the material is preserved.
Secondly, the experimental module, which is not foreseen in the curriculum,
must be short enough to avoid interfering with the implementation of the
current curriculum. Thirdly, it is most suitable to organise experimental
training within hours-long disciplines to minimise relative changes in the
curriculum. The most likely fact is the small sample of involved respondents since
the limited investigation time allows us to work with students of only one
group.

Thus, it is critical to develop a small experimental block of lessons that must be
conducted quickly. When implementing experimental training, one needs to
constantly assess the effectiveness of the intervention and monitor the students’ daily
progress. Operational feedback is essential for success when content optimisation and
corresponding performance research are conducted in the real learning process and in
real-time. Such an educational technology technique allows one to work out the
changes required in the content of academic disciplines in the conditions of the actual
educational process. It does not require sophisticated electronic resources
and is not limited to the context used. Moreover, it can be extended for
more in-depth research and has the potential for further development and
expansion.

The research goal is to develop a technology for the organisation of
experimental training to form project competence using the project method in the
conditions of the ongoing educational process. The proposed approach is based on the
development, execution and defence of students’ projects in waste management. Two
types of specially developed questionnaires using Google Forms will provide either
daily feedback to correct learning content quickly or evaluation of general training
effectiveness at the end of the training compared to its beginning. The evaluated
degrees of mastering the seven basic elements of the design project indicate the
formation of project competence.

2 Research methods

2.1 The main elements of the project design

The main task of the PjBL module is to master the principles on which it is built.
Another essential aspect of mastering PjBL is learning while formulating and
implementing projects.

There are many definitions regarding the principles of PjBL. An educational
organisation, PBL Works, created a comprehensive model and formulated seven
primary project design elements, known as the “gold standard of projecting” [23].
Mastering these elements, briefly listed in table 1, is necessary for successfully
using the PjBL method. Therefore, the idea of familiarising students with
the seven “golden” design elements and mastering them in implementing
projects developed personally is the basis of the educational material in the
experiment.

Table 1: The main elements of the project design taken over from [23].

No

Full and

abbreviated name

What the element describes

and its brief description

1

Challenging
Problem or
Question (CP)

Process. A challenging and exciting challenge makes
learning more meaningful. Students do not just
acquire knowledge to memorise but learn with a real
need for knowledge to use in the future

2

Sustained Inquiry
(SI)

Mode of action. When faced with a complex problem,
students ask questions, find the resources needed to
answer them, and then ask deeper questions until the
answer is found

3

Authenticity and
Originalities (AO)

The nature of the task. The project should have a real
context – solve real problems, and have an impact on
solving real issues

4

Student Voice and
Choice (SV)

Students’ skills. Having a voice gives students a
sense of ownership and improves project stewardship.
Otherwise, students feel like they are just doing an
exercise or following the instructions of others

5

Reflection
and Thoughtfulness
(RT)

Deliberation. Students and teachers must consider
what they are learning and how and why during the
project. Reflecting on the content of the acquired
knowledge helps students consolidate this knowledge

6

Critique and
Revision (CR)

Teamwork. Thoughtful criticism and refinement are
the keys to high quality. Constructive feedback
with peers, teachers, and experts improves project
processes and work products

7

Public Product
(PP)

Product characteristics. Publicising the results of
project work is an effective way to increase motivation,
performance quality and communication with others

2.2 The scheme of the experiment

A significant drawback of the existing curriculum is insufficient attention to forming
professional design competence, lack of appropriate methodology and clearly defined
expected learning outcomes. A complicating factor is a need to eliminate the
listed shortcomings in the conditions of the educational processing process,
which does not provide time and conditions for experimentation. Under such
conditions, the most reliable option is to incorporate a relatively short academic
module into the curriculum to ensure the necessary knowledge and skills
mastery.

Students in the fourth year of the Faculty of Fashion and Arts of Kyiv National
University of Technologies and Design participated in the experiment. The group
consisted of 8 people: students specialising in professional education in technologies.
In the fourth year, the discipline “Creative Learning Technologies” is studied,
which contains 180 hours (6 ECTS credits). The developed experimental
module dedicated to PjBL comprises lectures and practical classes for 18
hours.

The proposed scheme of the experiment includes three main stages (figure 1).
The first two stages are characteristic of pedagogical experiments. They are
called ascertaining and formative stages; the third focuses on analysing the
results.

Fig. 1: The scheme of the experiment.

The purpose of the ascertaining stage was to determine the level of student
knowledge regarding PjBL as of the beginning of the experimental study. First,
students listened to lectures and practical classes (8 hours total), where they got
acquainted with the basic concepts and components of problem-based and
project-based learning. Before these lessons, students had yet to meet using any
projecting. Then, students were surveyed using a questionnaire specially developed by
the authors to assess their initial level of knowledge.

The second formative stage included experimental training using the developed
methodology. A new educational module of 18 hours (9 lessons) was incorporated into
the existing discipline. The module’s topic is “Mastering the PjBL Methodology using
the Example of Individual Projects “Decorative Painting of Fabrics as a Technology of
Textile Upcycling”.

The independent creation of student projects was preceded by practising the skills
of working on individual elements of the project methodology under the guidance of a
teacher. In the experiment, students were not limited in choosing design objects
within the specified subject. It was considered mandatory to apply the idea of
recycling used items and use one of the upcycling techniques for this, namely
decorative fabric painting. During the development and implementation of the
project, the teacher mainly played the role of a consultant.

Table 2 illustrates the main stages of the performance of experimental
training.

Table 2: Stages of the experimental training by PjBL.

Stages

Activity

Time, h

1. Problem-targeted

To justify the purpose and choice of the design object.
Determine the
intended purpose of the future product. Formulate
ergonomic, aesthetic, technological, economic, and
environmental requirements. Describe the expected
results.

2

2. Development
of the technical
task

Develop the design part, determine the technological
sequence of manufacturing the product, justify
the selection of materials and tools, examine the
techniques of product execution and processing
methods, make the necessary economic calculations,
and draw up a planned schedule for project
implementation.

2

3.1-3.4 Practical
implementation

Produce a design object and follow the rules for
using tools and materials. Since all projects were
individual, it is impossible to determine a single time
frame for the sequence of works.

8

4. Preliminary
defence

Discuss the work results with the teacher and fellow
students, and correct the identified shortcomings.

2

5. Public
presentation of
results &
summary

Present the design result, analyse the achievement of
the set goal and reflect on the success of the chosen
ways of solving the set tasks.

2

In experimental training, students had to master the main elements of project
design. A short, special survey was conducted after each class to operationally correct
the content of new classes and the applied methodology. The survey results were
processed to correct the educational materials the next day. The content of the daily
surveys varied depending on the training content. The second stage ended with a
second survey using the same methodology as before the start of the experimental
training.

The third stage aims to assess the effectiveness of the experimental training. For
this purpose, the results of surveys after the first and second stages were compared.
Individual learning styles of students were also determined using the Felder-Soloman
method. Determining students’ preferred learning styles allowed one to reveal
the existing educational advantages of the group. Adjustment of training
based on the results of daily surveys was aimed at the optimal use of training
resources in experimental training and the development of training benefits
that would contribute to a better assimilation of the principles of project
activity.

2.3 Survey methods

The study’s primary method of obtaining quantitative data was the survey method,
which was applied to three objects. Three different questionnaires were used to
conduct the survey. The authors developed two types of questionnaires, and the third
type, known from the literature as the Learning Styles Tool, was available for free
use.

Very short deadlines for conducting the research and the need to constantly
maintain feedback between teachers and students throughout the experiment led to a
specific form of questionnaire implementation. The specificity consisted of
using Google Forms to prepare questionnaires [22]. The forms were stored on
the university’s Google Drive, and their access was implemented through
QR codes. This significantly expanded the students’ ability to use various
devices (tablets, smartphones, and others) to perform research tasks and
promptly transfer their impressions to the teacher. Ensuring quick response of
students to teachers’ demands in wartime conditions was only possible with
this.

An example of a filled-in Google Form related to questions about understanding a
Challenging Problem or Question (CP) is shown in figure 2. The more often feedback
is used, the greater immersion in work and increased motivation among students.
Simultaneous assessments by the teacher and student self-assessment of educational
results are carried out. Surveys to adjust the content of individual educational blocks
were repeated before each lesson. Depending on the purpose of the block, their
structure (types and number of questions) differed. Although Google Forms is used
only as a well-known technical toolkit in this study, it is an indispensable foundation
for the developed technology. It is an excellent example of the use of information

technology in pedagogical research.

Fig. 2: A completed Google Form for determining the degree of mastery of
project elements (an example to master a Challenging Problem or Question
(CP)).

Thus, surveys with the help of Google Forms can be components of educational
technology when students become, as they were, organisers of the process, realise the
goals of studying a particular topic and are responsible for the result. It can
encourage students to better reflect on each stage of their activity. The teacher can
store statistical data in Google spreadsheets and process them using data analysis and
visualisation methods [11]. The survey at the beginning and the end of the
experimental lessons allows one to assess the experiment’s effectiveness and adjust the
teaching method promptly.

The questionnaire developed in the paper to determine the degree of design
element mastery was used twice in ascertaining and formative experiments. The
questionnaire covered all seven design elements and consisted of 49 questions. It is
aimed at assessing how well students understand the essence and importance of
individual design elements of the project. Seven questions or statements were
formulated for each element, and the respondents had to express their attitude to
each problem. Seven answer options were available, from which only one had to be
chosen.

Such a result evaluation scheme corresponds to a 7-point Likert scale [19]. The
points available for answers range from 1 to 7 and have the following meaning: 1 –
strongly disagree with the statement in the question, 2 – disagree, 3 – somewhat
disagree, 4 – no clear opinion (that is, it is a neutral or zero position), 5 –
somewhat agree, 6 – agree, 7 – agree entirely with the statement in the question.
Some statements were formulated in direct order (as explained above), and
some in reverse order to avoid simple guessing without understanding the
question’s essence. For the reverse statement, 1 point corresponds to the option
to agree entirely and 7 – to completely disagree. In further analysis of the
results, the scale for reverse questions was converted into a scale for direct
questions.

The model of R. Felder and L. Silverman [12] was used to determine students’
preferred learning styles. For the practical application of the model, R. Felder and
B. Soloman developed a tool called Indices of Learning Style [13]. This tool helps
determine the individual preferences that respondents have in education. Four
dimensions determine the division of learning styles, each combining two oppositely
directed styles.

The first dimension is the perception of information, which includes a sensing
(sen) style – oriented to facts, specifics, and practice, and opposite an intuitive (int)
style, oriented to intuition, theories, and abstract concepts.

The second concerns sensors for information perception. They are based on the
visual (vis) style, which gives preference to illustrations, and the verbal (vrb) style,
which prioritises verbal explanation (both oral and written).

Comprehension of information includes an active (act) style – orientation to
activity in work and experimentation, and reflective (ref) – based on reflection and
observations.

The learning pattern includes sequential (seq), which is aimed at step-by-step
understanding, convergent thinking, analysis, and global (glo) style, which is focused

on systemic thinking and synthesis.

The Felder-Soloman method helps determine the direction and degree of
educational preferences of students according to the above styles with the help of
particular questionnaires, in our case, via Google Forms. The questionnaires contain
44 questions, 11 for each dimension, which help to determine educational preferences
in four areas: sen/int; vis/vrb; act/ref; seq/glo. Each answer to the question adds +1
or -1 point for this dimension, and their sum determines the presence of one or
another preference.

2.4 Statistical treatment of the results

Statistical methods were used to analyse the obtained results. All calculations
were made using the statistical package IBM SPSS Statistics, version 21
[27]. The statistical study aimed to solve two main problems: assessing the
reliability of the developed survey methods and comparative evaluation of
the figures demonstrated by students at the first and second stages of the
experiment.

One of the survey methods used in the research, namely, the Felder-Soloman
method, was developed by other authors and repeatedly used in many published
studies [14, 24]. Accordingly, the level of reliability of this technique was checked
many times. The reliability, expressed through Cronbach’s alpha coefficients, varies
between 0.55-0.76 according to the results of different authors [14, 24]. Such a value
demonstrates a sufficient level of reliability of the Felder-Soloman model,
taking into account the extensive database of verified questionnaires (more
than 1000 units). Therefore, the model itself does not require additional
checks.

The results of daily surveys, aimed at prompt correction of teaching methods,
were not used for formulating general conclusions but for quick application in the
educational process. Therefore, the most critical criterion for the reliability of this
technique is the type of changes in the educational process that result from the
practice of conducting classes.

The third questionnaire method, developed by the authors, aims to determine
students’ mastery of the main design elements. The reliability of this technique was
assessed by calculating Cronbach’s alpha [27, p. 246–254]. This characteristic
evaluates the reliability of the method as the internal consistency of the test. In other
words, it measures how partial measurements (answers to individual questions
regarding the same element of the project) agree. The Cronbach’s alpha coefficient
value ranges between 0 and 1 if the test is unreliable and reliable, respectively. The
border between reliable and unreliable tests is often the subject of scientific debate.
However, in most cases, a value of 0.55-0.6 and above is considered the reliability
limit.

The reliability testing results are given in table 3 based on the results of applying
the developed questionnaire at the beginning and after the end of the experimental
training.

Table 3: The results of Cronbach’s alpha test based on student’s answers in the
ascertaining (1) and formative (2) experiments.

No

Element

Cronbach’s alpha (1)

Cronbach’s alpha (2)

1

CP

0.011

0.704

2

CI

-0.174

0.785

3

AO

0.701

0.847

4

SV

0.721

0.791

5

RT

0.581

0.811

6

CR

0.75

0.801

7

PP

0.606

0.862

In the first testing, before the start of PjBL, students often did not fully
understand the questions, affecting the results obtained. Out of 7 project design
elements, the results of Cronbach’s alpha calculations met the reliability criterion in
only 5 cases – they were higher than 0.58 (Cronbach’s alpha index (1) in
table 3). However, the results improved significantly after the students received
the experimental training (Cronbach’s alpha (2) in table 3). In this test,
Cronbach’s alpha exceeded 0.7 for all elements examined. Such a result allows one
to say that the developed questionnaire provides reliable results when the
respondents already have a stable idea about the nature of the investigated
elements.

Another statistical analysis task focuses on a statistically significant difference
between the sets of respondents’ answers at the stages of ascertaining and formative
experiments. The answer to this question allows one to assess the proposed
teaching technology’s effectiveness quantitatively. In addition, it is essential
to determine the presence of a statistically significant difference between
learning styles among different groups of respondents. To choose the optimal
statistical model, one should consider the characteristics of the studied data
array:

1.

All survey results are rank values.

2.

As the Kolmogorov–Smirnov test results show, not all samples follow a
normal distribution (table 4). It especially applies to the first stage results
showing no normality in all 7 cases.

3.

Because the questionnaires were anonymous and not all students
participated in the two surveys being compared, it is necessary to use
statistics for independent samples.

4.

The work examines small samples (a small group of students was
interviewed). Therefore, it is necessary to use statistics that provide the
best results specifically for analysing small samples.

Table 4: The results of the Kolmogorov-Smirnov test (*) for the presence of
normal data distribution.

Elements

CP

SI

AO

SV

RT

CR

PP

Ascertaining experiment

Kolmogorov-Smirnov Z

1.205

1.023

1.104

1.318

.966

1.344

1.266

Asymptotic significance (2-tailed), p

.110

.246

.174

.062

.308

.054

.081

Formative experiment

Kolmogorov-Smirnov Z

1.327

1.191

1.534

1.639

1.641

1.662

1.788

Asymptotic significance (2-tailed), p

.059

.117

.018

.009

.009

.008

.003

(*) The null hypothesis to be tested is a sample under study has a normal distribution

Summarising points 1-4 above, one can conclude that the Mann-Whitney U
criterion best meets the experiment conditions and the nature of the data obtained
[27, p. 152]. Namely, this test is designed to analyse rank variables in small
independent samples. The number of elements in the compared samples may differ,
but not less than three. The Mann-Whitney test is non-parametric. Therefore, this
method does not require the presence of a normal distribution and the equality of
variances.

3 Results and discussion

3.1 Study of project design elements

All students coped with successfully designing, implementing, and defending the
developed projects. Therefore, the proposed educational technology has prospects for
further development. As mentioned earlier, the student’s understanding of the main
project design elements was examined twice through a questionnaire – before the
beginning and after the end of the experimental study. The results in the form of
ratings of average scores are shown in figure 3.

Fig. 3: Average scores for individual design elements based on the results of
ascertaining and formative experiments.

In the first stage, the respondents’ average scores exceeded 5 points (Somewhat
agree) only for four out of seven elements. For two elements, SI and CP, the
respondents’ opinions varied between 4 (I do not have a clear view) and 5 points. For
these two elements, Cronbach’s alpha, calculated based on the first stage results, was
far from the level characteristic of a reliable scale. This fact may confirm our
assumption that respondents did not fully understand the nature and role of these
elements but only tried to guess adequate answers.

The situation was significantly different according to the survey results at the
second stage of work (figure 3). For all elements, the average scores confidently
exceeded 5 points. For two elements (CR, CP), they came close to 6 points (Agree);
for SV, they even transcended this line. It should also be noted that the most progress
in promotion in the rating was characteristic of the elements of CP (previously the
most problematic) and SV. Conversely, the SI element was the only one that
remained at the bottom of the rating. All other elements stayed again in the middle of
the rating.

Fig. 4: Comparison of the average scores of individual design elements based on
the results of ascertaining and formative experiments.

The values of average scores increased after the respondents underwent
experimental training for all elements, without exception (figure 4). If the average
scores ranged between 4.75 and 5.4 during the initial testing, the values of all scores
increased to 5.54–6.23 after training.

At the qualitative evaluation level of the results, the training seemed to improve
the respondents’ understanding of the essence of the project activity in all directions.
However, the data given is not enough to formulate final conclusions. An open
question remains whether the obtained difference reflects a real improvement in the
perception of project elements or whether the observed difference results
from statistical error. Special statistical testing is necessary to solve this
issue.

3.2 Comparative analysis of the results of ascertaining and formative
experiments

The degree of understanding and ability to use individual design elements are
indicators of project competence formation. The applied approach improved
the knowledge of PjBL and clarified its importance and individual element
roles. The degree of progress achieved differs for different project design
elements. It may be related to teaching deficiencies and students’ perceptions of
various educational materials. Determining the availability of statistically
significant improvement remains essential because it may not occur in all
cases.

The Mann-Whitney U test was used to compare survey results at the first and
second experimental stages. The null hypothesis of the Mann-Whitney U test is that
the differences between the samples for the ascertaining and formative experiments
are random (or do not exist at all). An alternative statistical hypothesis is that such
differences exist. Acceptance of the alternative hypothesis gives reason to believe that
the differences between the groups are statistically significant at the p <0.05 level.
The results of calculating the asymptotic values (2-tailed) of p are given in
table 5.

Table 5: Mann-Whitney U test statistics (*) to compare average scores
for individual design elements calculated in the ascertaining and formative
experiments.

Elements

CP

SI

AO

SV

RT

CR

PP

Mann-Whitney U test
statistics

457.500

559.000

560.000

387.000

541.500

566.000

526.500

Z

-2.913

-1.844

-1.845

-3.695

-2.050

-1.804

-2.214

Asymptotic significance
(2-tailed), p

.004

.065

.065

.000

.040

.071

.027

(*) The null hypothesis of the test is that the differences between the two samples are not
significant

For CP, SV, RT and PP elements, the Mann-Whitney test predicts the presence of
a significant difference between the results of ascertaining and formative experiments
(figure 5). For the other three elements, SI, AO and CR, the calculated p parameter
slightly exceeds the value of 0.05, which is accepted as a threshold value. For
example, for SI and AO, the p-value is 0.065; the probability that the compared
groups are identical is 6.5%, slightly higher than the accepted threshold of
5%.

Fig. 5: The difference between the results of the formative and ascertaining
experiments expressed in the average ranks for each design element with the
determination of the level of statistical significance p.

The content of experimental learning can cause significant progress in
understanding the role of different design elements. After completing the
training, individual training lessons were analysed from the point of view of how
many and which design elements were considered. The analysis results in a
diagram are shown in figure 6. We see a significantly different load on design
elements from the point of view of their use at different stages of experimental
projecting. Thus, the SV element in one form or another was considered in
all eight practical lessons (4 stages consisted of 1 lesson each, and 1 stage
covered four lessons). We do not consider the first of 9, the introductory
lesson. In contrast, attention was paid to the SI element in only one lesson.
The SV element took first place in the rating at the stage of the formative
experiment, and the SI element dropped from the penultimate to the last place
(figure 3).

Fig. 6: Study of individual design elements at stages 1-5 of the experimental
study: stage 1 – problem-targeted, 2 – technical task, 3.1-3.4 – practical
implementation, 4 – pre-defence, 5 – product presentation & summary.

Obviously, allocating a certain minimum of time is necessary for successfully
mastering the element. Later, with increasing time (within the conducted short-term
experiment), the level of understanding increases in most cases. However, this
condition is insufficient, and two elements fall out of this pattern. The elements
of RT and CR (used in five and four lessons) show slightly less progress
than expected. In both cases, one needs to find logical explanations for this
fact.

Only the classes of the third stage (table 2), during which the product was
manufactured, are devoted to the CR element. It should be emphasised that all
projects were individual. At the same time, as we know, the CR element is focused on
teamwork. It includes constructive feedback from peers, teachers and experts, which
improves project processes and work products. However, this is impossible when
implementing individual projects; students can only exchange opinions with the
teacher. The dotted connections for CR in figure 6 illustrate their incomplete
performance. Thus, restrictions on the progress of the CR element were already
designed in the structure of the experimental curriculum, and they were reflected in
the obtained results.

The RT element, by default, implies deliberation. Students and teachers must
consider what they are learning and how and why during the project. Reflecting on
the content of the acquired knowledge helps students consolidate this knowledge. On
the one hand, developed reflective thinking is the key to successfully mastering the
element of RT. On the other hand, it is impossible to say a priori how much reflective
thinking is developed among the respondents. Studying students ’ learning styles can
provide additional information on this issue. For example, within the Felder-Soloman
model of learning styles, students use active or reflective styles of understanding
information.

3.3 Individual learning styles

The learning style preferences among all participating students were determined
using the Felder-Soloman method. Separately, similar research was done for
three teachers related to teaching the discipline in which the experiment was
conducted. The average profiles for the student group and teachers are shown in
figure 7.

Fig. 7: Average learning profiles of students and teachers who participated in
the experiment. For clarity, the red line separating shaded inside and unshaded
outside areas corresponds to the balance of styles in all four dimensions (5.5
points on a scale from 0 to 11 points).

The Mann-Whitney U test was applied again (table 6) to clarify in which cases
the difference in styles is statistically significant. A significant difference between the
teaching styles of teachers and students was observed only in the act/ref dimension (p
= 0.035). In other dimensions, the value of p is far from the threshold value of
0.05.

Table 6: Mann-Whitney U-test (*) statistics for comparing the learning styles
of teachers and students.

Parameters

Act

Sen

Vis

Seq

Ref

Int

Vrb

Glo

Mann-Whitney U-test
statistics

6.500

16.000

15.500

21.000

6.500

16.000

15.500

21.000

Z-value

-2.104

-.796

-.857

-.134

-2.104

-.796

-.857

-.134

Asymptotic significance
(2-tailed), p

.035

.426

.391

.893

.035

.426

.391

.893

(*) The null hypothesis to be tested is that the two populations being compared have
identical distributions

The perception of the concept of learning styles is still debatable due to the
complexity of the object itself. On the one hand, some authors deny the
value of using learning styles for the educational process [28]. On the other
hand, most authors positively perceive the idea of educational preferences
[5]. The situation is complicated by many style models that do not always
agree with each other [5]. Active discussions concern the presence [38, 40] or
absence [29, 33] of a correlation between styles and the level of academic
achievement.

It is known from the literature that acquired educational advantages are pretty
stable and, therefore, practically do not change during undergraduate studies [7]. At
the same time, student profiles become more balanced when transitioning from
bachelor’s to master’s [20]. Many publications emphasise a significant difference
between the learning styles of students of different study fields [7] and nationalities
[16], and students and teachers [36, 39].

Usually, teachers are more reflective and have global learning patterns than more
active and sequential students. The inconsistency of styles is partly related to possible
differences in the attitude of both parties to the educational process [7]. As already
mentioned, the preference for an active learning style is typical of all undergraduate
engineering majors. Further, in the master’s degree – postgraduate studies –
teachers series, accents gradually shift towards the preference of the reflective
style. The difference contributes to the efficiency of the assimilation of the
material.

Typically, models of learning styles do not divide learning preferences into good
and bad. Nevertheless, a certain balance between learning and teaching styles will
contribute to the material’s effectiveness mastering. The optimal organisation of the
educational process should be aimed at balancing teaching and learning styles
rather than achieving absolute consistency between each teacher’s actions
and students’ educational preferences. The balance creates conditions for
students to develop the necessary learning styles in a group and does not lead
to cognitive overload, discomfort in learning, fatigue, negative emotions,
etc.

The current study confirmed teachers’ higher level of reflectiveness compared to
students. Comprehension of information was the only statistically significant among
the four dimensions of learning styles. The other three dimensions, including
perception of information, sensors for information perception, and learning
patterns, show no difference. As already mentioned, the preference for an active
learning style is typical of all undergraduate engineering majors. However,
the difference may also appear in other dimensions when studying larger
samples.

Several works [3, 10, 18] prove the existence of a direct correlation just between
the level of reflectivity and academic achievements. Thus, the importance of
meaningful reflection for academic achievement is recognised. Therefore, excessive
activity and, at the same time, an undeveloped ability to reflect on the results

obtained and planned, as well as failures in the implementation of projects, inhibit the
formation of project competence. The relatively restrained progress achieved in the
study of the RT element is probably related to the weak development of reflective
thinking in bachelor students, which was found experimentally. It indicates an
underestimation of this factor’s possible influence on currently active and developed
experimental programs.

It is necessary to develop educational programs to strengthen students’ reflection
in the learning process, improve academic success, and better prepare them for the
future profession. To enhance the reflexivity of active students during training, one
needs to apply reflective exercises: 1) survey after each stage of projecting to
understand one’s activity; 2) keeping a diary in which observations of positive and
negative moments in the design process are entered, to find solutions and improve the
work; 3) at the beginning of each design stage, repeat the knowledge gained at the
previous stages; 4) living project activity on one’s own experience, which solves a real
problem.

4 Conclusions

1.

Educational technology has been developed to mould students’ project
competence. The technology is based on a short-term training course (18
hours), organised as an academic module and incorporated into one of the
active disciplines. During training, students independently choose a project
topic from waste management, develop, execute and defend it. The final
effectiveness of the approach is evaluated through two surveys using specially
designed questionnaires at the beginning and end of the training.

2.

The proposed technology focuses on mastering the seven basic elements
of PjBL, which are considered indicators of project competence formation.
An essential part of the module is the organisation of regular and prompt
feedback between students and teachers using short daily surveys via Google
Forms. This tool allows teachers to adjust the training content and accents
in time, depending on each lesson’s effectiveness. The proposed methodology
significantly improved students’ understanding of the basic principles of
PjBL. Statistically significant improvement was observed for four of the seven
elements (CP, SV, RT and PP); for the other three (SI, AO and CR), progress
was also observed but did not exceed the 0.05 significance level.

3.

The general trend of progress in learning was that the more classes
were devoted to one or another projecting element, the more remarkable
improvement was observed. In other words, minimal but sufficient attention
to each element is necessary for achieving progress in its study. The SI
element in the developed module was not given enough attention, so this
element ended up in the last place in the progress rating.

4.

However, a certain level of attention seems necessary but insufficient for
achieving appreciable progress in learning individual project elements.
Progress was less than expected for two elements, which received quite a
high level of attention during training. The non-ideal organisation of project
learning and the unaccounted feature of the student’s learning style inhibited
the mastery of some design elements, namely CR and RT.

5.

Mastery of the CR element includes active discussion among all participants.
However, the chosen format of individual projects was not entirely favourable
to broad discussions, limiting the possibilities of exchanging ideas in
contrast to group projects. Accordingly, implementing group projects should
contribute to a better understanding of the CR element.

6.

Studies of learning styles have shown the advantage of students’ active style
of information comprehension over a reflective one. Developing reflective
thinking is vital for mastering the RT element. This factor has become
the reason for slowing down progress in mastering RT. The development of
reflexivity due to the implementation of the proposed special exercises in the
educational process is promising for eliminating the identified deficiency.

7.

The developed educational technology is not limited to the studied topic and
has the potential for further development and expansion. Subsequent studies
will aim to eliminate the shortcomings identified and listed in the previous
item. In future, more respondents will be involved in the analysis to obtain
more precise results.

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