TEM Journal. Volume 14, Issue 1, pages 602-611, ISSN 2217-8309, DOI: 10.18421/TEM141-53, February 2025.

Project-Based Learning Combined with

Inquiry-Based Learning Using Solver Tools
to Promote Computational Thinking
Among Undergraduate Students
Narongsak Sangpom 1, Wasukree Sangpom 2
1
Faculty of Industrial Education, Rajamangala University of Technology Suvarnabhumi,
Suphanburi, Thailand
2
Faculty of Science and Technology, Rajamangala University of Technology Suvarnabhumi,
Suphanburi, Thailand

Abstract – This research aims to 1) Study the 2) The combined Project-Based Learning and
management of learning units on linear programming Inquiry-Based Learning model using Solver tools
for undergraduate students, 2) Develop and verify the included principles, objectives, learning management
quality of the learning model, and 3) Examine the effects processes, measurement and evaluation, and essential
of the model on 24 undergraduate students at the conditions for successful implementation. The model
Rajamangala University of Technology Suvarnabhumi was of high quality with an effectiveness index of 0.561;
using purposive sampling. This research was a research 3) Implementing the model significantly increased
and development study. The research tools included the students' computational thinking skills in all five areas
learning management model, lesson plans, classroom with a statistical significance level of 0.001.
observation forms, and computational thinking
assessment tools. Data were analyzed using percentage, Keywords – Project-Based Learning (PjBL), Inquiry-
mean, standard deviation, and t-test. The research Based Learning (IBL), Solver Tools, computational
findings were as follows: 1) The learning management thinking (CT)
was characterized by collaborative learning, studying,
planning, practicing, expanding students' concepts to 1. Introduction
summarize mathematical concepts, and assessing the
results. The instructor guided, stimulated learning, In the 21st century, teaching and learning
supported, facilitated, and reinforced learning. management has become more learner-centered,
reducing the emphasis on lecturing, demonstrations,
and direct instruction. Teachers now play a role in
stimulating students to learn independently through
DOI: 10.18421/TEM141-53
hands-on activities or learning by doing, where
https://doi.org/10.18421/TEM141-53
practical experiences and active engagement in real-
Corresponding author: Wasukree Sangpom, world environments are crucial. This approach is
Faculty of Science and Technology, Rajamangala University based on the belief that everyone can understand and
of Technology Suvarnabhumi, Suphanburi, Thailand develop according to their interests and abilities [1],
Email: wasukree.s@rmutsb.ac.th [2], [3]. Project-Based Learning (PjBL) provides
Received: 27 June 2024. learning experiences where students create tangible
Revised: 22 January 2025. outcomes through projects, emphasizing the learner at
Accepted: 06 February 2025. every stage of the process and enhancing learning
Published: 27 February 2025. effectiveness in various fields. This approach can be
applied at all educational levels, focusing on in-depth
© 2025 Narongsak Sangpom & Wasukree
learning processes [4], [5], [6]. Students learn from
Sangpom; published by UIKTEN. This work is licensed
problem-solving activities by discussing methods and
under the Creative Commons Attribution-NonCommercial-
strategies, while teachers support and facilitate
NoDerivs 4.0 License.
learning [7]. This method also encourages students to
The article is published with Open Access at develop new and diverse ideas, ultimately enhancing
https://www.temjournal.com/ learning outcomes [8], [9].

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 TEM Journal. Volume 14, Issue 1, pages 602-611, ISSN 2217-8309, DOI: 10.18421/TEM141-53, February 2025.

Inquiry-Based Learning (IBL) is a process where This enhances meaningful and in-depth learning,
students seek or research knowledge independently. It enabling students to apply what they have learned in
begins with students forming questions from real-life practice, become skilled graduates, and be prepared to
situations and seeking answers through investigation, face future challenges.
hands-on activities, self-created knowledge, analysis,
and presenting their results while supporting their 2. Methodology Section
ideas with evidence [10], [11], [12]. Teachers support
this learning process to guide students towards This research is a research and development
independent learning and sharing of knowledge. This (R&D) study using a quantitative research
helps develop skills in thinking, reasoning, and methodology in the form of experimental research. It
decision-making to solve problems systematically follows a one group pretest-posttest design, with the
[13], [14]. These processes can lead to the research divided into four steps as follows.
development of students' computational thinking. IBL Step 1: Research (R1) involves studying and
is a popular teaching method used by universities, analyzing basic data (analysis: A). The researcher
especially in the United Kingdom, which has conducted a study and analysis of basic data as
successfully developed students with the desired follows:
attributes according to curriculum and societal needs.
The Excel Solver tool is a Microsoft Excel add-in • The results of after action review (AAR) were
program. Efficient warehouse layout planning studied and analyzed after conducting classroom
requires tools that are quick, accurate, and convenient, research with second-year students in the
which Solver achieves by rapidly and effectively Industrial Business Innovation and Data
zoning products. Using spreadsheets facilitates easier Management program, Faculty of Science and
operation and presentation of profitable solutions to Technology, academic year 2022. This was done
problem situations [15]. Mathematical modeling aids to summarize the outcomes after collaboratively
in planning and allocating warehouse space developing the learning management process. The
efficiently, maximizing space utilization and instructor participated in classroom observation,
operational benefits. Linear Programming assists in result discussion, and improvement of learning
making optimal decisions about resource use under management, as well as summarizing effective
constraints, guiding investment decisions for problem-solving methods for student learning. It
maximum profit within existing limitations. Today, was found that there was a need to promote skills
Linear programming is applied in various fields, in algorithmic thinking, critical thinking, higher-
including production, nutrition, education, physical order thinking, and computational thinking.
sciences, and social sciences.
• Relevant research was reviewed both
Computational thinking (CT) is a fundamental skill
related to problem definition, problem-solving, and domestically and internationally.
scientific reasoning [16], [17]. It can be integrated into • Study and synthetisation were conducted for the
curricula from elementary to higher education, components of the learning management model of
particularly in STEM education and (PjBL), due to its [22], which were then defined as the components
potential to enhance students’ understanding of of the learning management model, including
content and problem-solving abilities [18], [19], [20]. principles, objectives, learning management
According to [21], a computational thinking processes, measurement and evaluation, and
assessment has been developed to show levels essential conditions for successful
according to expected standards. [17] identified five implementation.
components of computational thinking: creativity, • The concept of combining Project-Based
algorithmic thinking, cooperativity, critical thinking, Learning with Inquiry-Based Learning using
and problem solving. Solver tools was analyzed and synthesized to
Combining Project-Based Learning with Inquiry- define principles, objectives, and learning
Based Learning is a significant method for promoting activities.
effective learning in higher education, particularly • The content was analyzed according to the
computational thinking, which is a goal of Bachelor of curriculum of the Industrial Business Innovation
Science programs. This approach helps students
and Data Management program to determine the
develop essential 21st-century skills. Given its
subject matter, measurement, and evaluation.
novelty, the entire education system must adapt its
learning management methods. The Project-Based • The desired learning management model was
Learning combined with Inquiry-Based Learning have studied by conducting depth interviews with key
been implemented using Solver tools to promote curriculum stakeholders from the Faculty of
computational thinking among undergraduate Science and Technology, responsible for teaching
students. This approach prioritizes student-centered the Industrial Business Innovation and Data
learning, with teachers understanding each student’s Management program.
needs in a fun and friendly learning environment.

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The interviews covered learning management The computational thinking scale by [21] used a 5-
issues, teaching methods, content, tools used in level Likert scale (1 meaning least, to 5 meaning
learning management, and methods for measuring most), consisting of 21 items with a Cronbach’s Alpha
and evaluating computational thinking. reliability of 0.788. It was translated into Thai by
Interviews were conducted with three instructors, language experts and tested again for reliability,
experts, and students to gather information about resulting in a Cronbach’s Alpha of 0.885, indicating
classroom learning management. high reliability.
Step 2: Development (D1) design and development • The draft learning management model was tested
(D&D) involved designing and developing a Project- with 20 students in the Industrial Business
Based Learning model combined with Inquiry-Based Innovation and Data Management program during
Learning using Solver tools to promote computational the first semester of the 2023 academic year. This
thinking. group had similar characteristics to the sample to
conduct a try out and determine the effectiveness
• Data from studies and analysis, including results index (E.I.) of the learning management model.
from after action reviews, learning management The effectiveness index criterion was set at no less
processes, theoretical concepts, interviews with than 0.50 or 50%, indicating effectiveness.
instructors and experts, and student surveys were Statistical analysis included percentage, mean,
summarized to draft the learning management and standard deviation.
model. Step 3: Research (R2) The implementation of the
• A draft of the Project-Based Learning combined teaching model with the sample was carried out as
with Inquiry-Based Learning model using Solver follows:
tools to promote computational thinking was • The learning management model was
created and its validity was checked. implemented with 24 students in the Industrial
• 3.Learning management plans were developed for Business Innovation and Data Management
using the combined Project-Based Learning and program during the first semester of the 2023
Inquiry-Based Learning model with Solver tools academic year (July-October), using purposive
to promote computational thinking among sampling. The combined Project-Based Learning
second-year students in the Industrial Business and Inquiry-Based Learning model was applied
Innovation and Data Management program, with with the following components:
each session lasting 3 hours, totaling 18 hours. 1) Principles:
• The appropriateness of the learning management The learning process focused on practical
model and plans was reviewed by seven experts. exercises, student participation, problem
• The results of the model and plan evaluations identification, collaborative analysis, exploring
were analyzed using mean (𝑥𝑥̅), standard deviation solutions, self-constructed knowledge, and jointly
(S.D.), and adjustments were made according to creating artifacts to solve problems.
expert feedback. 2) Objectives:
The model aimed to serve as a tool for promoting
• Tools used to measure computational thinking
computational thinking among undergraduate
[17] defined five components of computational
students in the Industrial Business Innovation and
thinking: Data Management program through PjBL
- Creativity: The ability to solve problems to combined with IBL.
achieve objectives using new and unrestricted 3) Learning Process:
methods, leading to innovative discoveries. - Define problem situations, motivate, and provide
- Algorithmic thinking: The ability to create clear, necessary foundational knowledge and skills.
rational step-by-step problem-solving processes - Understand, analyze, and link the problem
and establish relationships to solve problems. situations.
- Cooperativity: The ability to work with others or - Plan problem-solving strategies.
in groups collaboratively and willingly, taking - Implement problem-solving and practice skills.
responsibility to achieve goals. - Synthesize knowledge, review, and evaluate the
- Critical thinking: The ability to think rationally, work.
analyze, and connect to make decisions for - Explore, research, and expand knowledge.
- Develop and disseminate the work.
reasonable answers.
4) Assessment and Evaluation:
- Problem solving: The ability to understand
- Computational thinking (CT) was assessed
problem situations, gather information, design before and after the course.
methods, choose options, and effectively solve - Projects and assignments were evaluated during
problems in all dimensions. the course.

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5) Role of the Instructor: • Students collaborate to discuss and derive the

- The instructor's responsibilities included objective equation, as it is essential for
preparing students with prior knowledge, setting determining the values that yield the highest
up the laboratory environment, and ensuring that benefit or efficiency, along with the constraints.
Microsoft Excel was installed and connected to
the internet for research purposes. The learning Step 2: Analyzing and linking to identify the
management followed active learning principles, problem.
collecting students' ideas to summarize into • The activities are conducted individually, but
overarching concepts, facilitating, guiding, and discussions are held collectively due to the limited
using diverse strategies to stimulate and promote number of students. Each student records their
learning. responses in the activity sheet.
6) Role of the Students: • Each student analyzes and links to identify the
- Students were expected to engage in analytical problem, designing a solution method by applying
thinking, be enthusiastic and cooperative in their knowledge of Microsoft Excel and the Solver
activities, have strong computer skills, tool, and records their findings in the activity
particularly in Microsoft Excel, and enhance their sheet.
analytical thinking. They were also expected to be
• The instructor and students jointly analyze the
creative in presenting information, have good
teamwork skills, and collaboratively analyze, and problem scenario and present the data in a simple
connect the content learned previously. format as shown in Table 1.

2.1. Learning Management Plans Included Table 1: Data from the problem scenario
Type Machine Labor Profit Number
Plan 1: Introduction to linear programming. of Time Time (baht/ Produced
Plan 2: Solving linear programming with graphical Sink (hours/ (hours/ sink) per Day
methods. sink) sink)
Plan 3: Solving linear programming with the A 2 1 30 x≥0
simplex method. B 1 3 40 y≥0
Plan 4: Solving linear programming using
software. Step 3: Planning problem-solving strategies
Example: Unit of learning: Linear Programming. • Each student collaboratively plans problem-
Learning Management Plan 2: Solving linear solving strategies and records their answers on the
programming with graphical methods, 5 hours.
activity sheet. The basic concept is that linear
Step 1: Motivating and providing essential programming helps in making decisions about
knowledge and skills. problems with limited resources to maximize
• The instructor assigns students to review content benefits or efficiency for the decision-maker.
knowledge, including linear equations, straight- Solving linear programming problems involves
line graphs, graphing linear equations, finding the minimum or maximum values under
inequalities, finding maximum and minimum certain constraints by creating a linear
values, and solving equations and inequalities. programming model. The linear programming
Students are also asked to study the capabilities of model consists of two parts:
Microsoft Excel, particularly the Solver tool. - The part that needs to find the maximum or
• Students study the information sheet on solving minimum value, is represented by an equation
linear programming problems using graphical called the "objective equation" or "objective
methods. function."
• The instructor presents a problem scenario titled - The part representing limited resources,
“Fun with Linear Programming.” expressed as inequalities showing constraints or
The scenario involves Siwa group, which produces limitations, is called "constraint inequalities" or
two types of sinks: type A and type B. Every type A "constraint conditions."
sink requires 2 hours of machine time and 1 hour of
• Each student collaboratively creates a model on
labor, yielding a profit of 30 baht per sink. Every type
B sink requires 1 hour of machine time and 3 hours of the linear programming model activity sheet,
labor, yielding a profit of 40 baht per sink. Given that defining variables based on the problem scenario
the maximum machine time available per day is 6 as follows:
hours and the maximum labor time available per day - Let P represent the quantity specified by the
is 8 hours, students are asked to determine the optimal problem scenario, which is the minimum or
number of each type of sink the company should maximum value, and x and y represent
produce daily to maximize profit and to create a linear quantities that P depends on within the
programming model. constraints.

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- Read the information from the problem statement • Students and instructors collaboratively translate
and summarize it into simple data. the problem scenario into a mathematical problem
- Create the objective equation, as it is necessary and solve it using various methods. This scenario
to find the maximum or minimum value. The uses graphs to find the solution:
objective equation will be P = ax + by where - Plot the graph of the system of constraint
inequalities to show all points in the shaded area
- Create the constraint inequalities, as they that comply with the system of constraints.
represent limited resources expressed as - Identify the corner points in the shaded area.
inequalities showing constraints. The constraint - Substitute each corner point into the objective
inequalities will be in terms of x and y. equation:
If there is only one minimum (or maximum) value,
Step 4: Implementing problem-solving and skill then that value is the minimum (or maximum) of the
practice: objective equation.
• Students carry out the tasks based on their analysis If there are two corner points that yield the same
and designed problem-solving methods. minimum (or maximum) value for the objective
- Let P represent the quantity being sought for the equation, then every point along the line segment
minimum or maximum value. connecting these corner points represents the
- P represents the total profit, and x and y are minimum (or maximum) value of the objective
quantities that P depends on. equation, indicating an infinite number of solutions.
- X represent the number of type A sinks produced • The instructor guides the application of
in one day. knowledge using Microsoft Excel and the Solver
tool.
- Y represent the number of type B sinks produced
Using Solver steps:
in one day.
Create the objective equation: P = 30x + 40y 1. Enable Solver Add-in (if not already
Creating Constraint Inequalities enabled): Go to File -> Excel Options -> Add-
Time used by machines to produce type A sinks: 2x ins -> Go… -> Check Solver Add-in.
Time used by machines to produce type B sinks: y 2. Create formulas to establish relationships:
Create a model that links the variable inputs,
Since the machine operates no more than 6 hours a
constraints, and objective outputs. Ensure that
day, therefore, 2x + y ≤ 6 is obtained.
when the input changes, the output changes
Time used by labor to produce type A sinks: x hours
correctly.
Time used by labor to produce type B sinks: 3y hours, 3. Use Solver: Specify whether to maximize or
therefore, x + 3y ≤ 8 is obtained. minimize the objective output. Select which
The number of sinks must not be negative, therefore, variable inputs to change under the given
x ≥ 0 y ≥ 0 is obtained. constraints.
• Students and instructor collaboratively create the • The instructor integrates positive reinforcement,
model from the problem scenario highlighting the advantages of using technology
- The objective equation, representing the for problem-solving, and the learning of minimum
maximum profit, is: P = 30x + 40y and maximum values, solving linear equations,
- The constraint inequalities are: and linear graphs.
2x+ y ≤ 6 • The instructor encourages collaborative learning
x+3y ≤ 8 and teamwork.
x, y ≥ 0, • The instructor facilitates learning and practical
Thus, a summary table can be written as shown in work, gathers students' ideas for group discussion
Table 2. to form comprehensive concepts, practices
problem-solving skills, and provides feedback on
Table 2: Data from the problem scenario
solving problem scenarios.
Type Machine Labor Profit Number Step 5: Reviewing and evaluating problem-solving
of Time Time (baht/sink) Produce
Sink (hours/sink) (hours d per • Students present their problem-solving process
/sink) Day and steps using the Solver tool.
• Students evaluate the problem-solving process
A 2 1 30 x≥0 using the problem-solving evaluation form.
B 1 3 40 y≥0 • Students and the instructor discuss topics such as
translating the problem scenario into
mathematical language, finding maximum and
Limit 2x + y ≤ 6 x + 3y ≤ 8 P = 30x + 40y
minimum values, creating the objective equation,
ations
and the equations or inequalities that represent
constraints.

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Step 6: Exploring and expanding knowledge: The scenarios were contextually relevant to the
• Students research linear programming, which is students’ professional field.
crucial in planning and operations across various The instructor acted as a facilitator, gathering
fields such as scientific research, technology, students’ ideas for discussion and summarizing them
engineering, marketing, and more. The possible into comprehensive concepts, knowing the tools
steps for this process include: students would use to solve the problem, and
- Setting Objectives: Helps to have clear goals reinforcing, and evaluating based on actual
and direction. performance.
- Exploring the Situation: Identify what the The approach engaged students with familiar
scenario specifies, constraints, or limitations. professional contexts to help them understand
- Defining the Scope of Research: Identify problem scenarios and connect them to prior
necessary information to obtain useful and knowledge, thus motivating and providing a positive
reliable data. learning experience. The instructor integrated
- Creating a Linear Programming Model: mathematical concepts, stimulated, and reinforced
Consists of linear equations and inequalities learning with questions, encouraging students to
to model the problem scenario. engage in Inquiry-Based Learning activities. This
- Collecting Data: Gather data according to the allowed students to practice thinking, observation,
defined plan while ensuring accuracy and presentation, analysis, critique, and knowledge
reliability. expansion, focusing on developing problem-solving
- Analyzing Data: Analyze the collected data, skills and promoting higher-order thinking. Project-
such as summarizing information, statistical Based Learning emphasizes experiential learning,
analysis, and organizing data. providing students with direct experience, problem-
solving practice, planning skills, leadership, and the
Step 7: Developing and publishing work. ability to present and publish their work, ultimately
• Each student presents their thinking process and enhancing their computational thinking.
work. 2. Model Development and Quality Assessment
• Each student brainstorms, researches further, The learning management model is called "Project-
plans, and develops their work to apply to other Based Learning combined with Inquiry-Based
problem scenarios. Learning." It consists of five components:
• The instructor and students reflect on and 1) Principles
summarize the problem-solving process. 2) Objectives
• The study used a one group pretest-posttest design 3) Learning management process, which includes:
over 4 weeks, with students completing a Step 1: Motivating students to engage with the
computational thinking assessment before and problem scenario, providing essential knowledge and
after the learning activities. The effectiveness of skills.
the learning management model was assessed Step 2: Analyzing and identifying the problem.
using statistical methods, including percentage, Step 3: Planning problem-solving strategies.
mean, standard deviation, dependent t-test, and Step 4: Implementing problem-solving and practicing
content analysis. The tools used included the skills.
learning management model and learning Step 5: Reviewing and evaluating performance.
management plans. Step 6: Exploring and expanding knowledge.
Step 8: Development (D2) This step involves Step 7: Developing and publishing work.
evaluating the effectiveness of the learning 4) Measurement and evaluation
management model. The researcher used the 5) Key conditions for successful implementation
evaluation results to review and improve the entire The results of the expert evaluation on the
learning management system. appropriateness of the learning management plan
show high appropriateness ( = 4.43, S.D. = 0.17). The
3. Results overall learning management model is highly
appropriate ( = 4.58, S.D. = 0.24), and the learning
1. Learning management of the linear management plan is deemed the most appropriate ( =
programming unit. The approach combined PjBL with 4.54, S.D. = 0.22).
IBL to promote computational thinking among The effectiveness index of the learning
undergraduate students in the Industrial Business management model was 0.561, equivalent to 51%.
Innovation and Data Management program. The results are summarized in Table 3.
The learning management was characterized by
collaborative discussions on problem scenarios,
analysis, planning, practice, evaluation, development,
and dissemination of work.

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Table 3: Effectiveness Index (E.I.) of the model From Table 3, it was found that the effectiveness
index of the model is 0.561, indicating that the model
Number Full Total Score E.I. increases students' computational thinking by 56.1%.
of Score 3. Results of using the model on computational
Students Before After thinking skills of students in the Industrial Business
Learning Learning Innovation and Data Management Program before and
after learning, as shown in Table 4.
24 25 331 482 0.561

Table 4: Computational thinking skills of students in the Industrial Business

Innovation and Data Management Program before and after learning

***p < .001

From Table 4, it was found that the computational This is because the researcher thoroughly reviewed
thinking skills of the students in the Industrial related documents, theoretical concepts, and relevant
Business Innovation and Data Management program, research papers to determine the components of the
who were exposed to the enhanced learning model, learning management model.
showed a statistically significant improvement at the These components include principles, objectives,
0.001 level in all five aspects, namely: Creativity (t = the learning management process, measurement and
-16.58, p <.001) algorithmic thinking (t = -11.55, p evaluation, and essential conditions for successful
<.001) cooperativity (t = -12.24, p <.001) critical implementation. These components and details
thinking (t = -13.11, p <.001) problem-solving (t = - comprehensively cover learning management, where
18.84, p <.001). the instructor stimulates students' interest in research
activities, allowing them to work at their own skill
4. Discussion levels and leading to increased knowledge through
hands-on practice [24]. The selection of lessons helps
The combination of PjBL and IBL using Solver instructors manage Project-Based Learning with real-
tools to promote computational thinking among world problem scenarios [25], [26].
undergraduate students was found to be highly
appropriate.

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However, the context of this learning management The developed learning management model for
is a blend of students' professional fields in Industrial computational thinking, based on self-assessments
Business Data Management with real-world before and after learning, showed significant
scenarios. The learning management model and plans improvement in all five components of computational
were evaluated by experts to ensure quality. The thinking at the 0.001 level (Table 3).
model was piloted with a representative group of This indicates that the learning management model
students to assess its practical applicability, resulting effectively enhanced students' computational thinking
in an effectiveness index (E.I.) of 0.561 or 56.1%, skills as follows:
exceeding the 50% criterion, indicating that the 1) Creativity: Students displayed increased self-
developed model is feasible for actual
confidence, diversity in thinking methods, courage to
implementation.
think differently, determination, and the ability to
The design of activities for each learning unit
solve problems and apply problem-solving methods
emphasizes diverse methods involving creativity,
when facing new situations.
algorithmic thinking, collaboration, critical thinking,
and problem-solving. Technology aids students in 2) Algorithmic thinking: Post-learning
seeing results and understanding mathematical improvements showed that students could
concepts quickly and clearly. The systematically demonstrate problem-solving approaches related to
designed and developed learning management model, their professional field and daily life and present
tested for effectiveness, can help students achieve the solutions to problem scenarios.
specific objectives of the model [22]. In Thailand's 3) Cooperativity: Enhanced post-learning skills
higher education context, PjBL combined with IBL indicated that students could engage collaboratively
aims to develop systematic computational thinking, with group members, exchange knowledge, and work
the ability to use technological tools to solve together to achieve assigned tasks successfully.
problems, and effective collaboration and 4) Critical thinking: Students found it enjoyable
communication. This teaching approach focuses on and challenging to plan problem-solving, think
developing essential skills for contemporary learners. systematically, and create options for decision-
Combining these two methods enhances critical making in complex problem situations.
thinking, problem-solving, and collaboration skills, 5) Problem solving: Improved problem-solving
which are crucial for future careers. abilities showed that students could devise solutions,
The effectiveness index (E.I.) of the developed create feasible alternatives, present problem-solving
learning management model was 0.561, equivalent to methods, make decisions, and apply sequential
56.1%. This is because the researcher analyzed what problem-solving methods, enhancing their thinking
students had previously learned, anticipated their skills in a Project-Based Learning environment, thus
problem-solving methods in advance, studied and improving their computational thinking skills [28],
learned how to use the Solver tool, and designed [29].
learning activities in each plan. These activities linked In recent years, there has been extensive discussion
the students' process skills and experiences in a and research on computational thinking [30], yet
sequential manner, from easy to difficult content. development at the higher education level remains
Individual and group activities were conducted, with somewhat limited. Higher education strives to
students gathering to discuss problem scenarios cultivate thinking methods that encourage students to
together under COVID-19 prevention guidelines, solve problems critically [31]. Computational
ensuring no rights were violated or harm caused to thinking is considered a fundamental and essential
students. Students were also required to complete a skill for the 21st century [32], [33], encompassing a
computational thinking assessment before learning for wide range of skills in "solving problems, designing
2 hours, followed by learning using the developed systems, and understanding human behavior by
model. The combined PjBL and IBL supported drawing on computer science concepts" [34]. Good
students' creativity, the application of new concepts to empirical thinking boosts 21st-century skills such as
problem-solving, and active participation in learning creativity, algorithmic thinking, collaboration,
activities. It provided opportunities for students to communication, critical thinking, and problem-
practice observation, present their thought processes, solving [23], [35], [21], [23]. In other words,
to analyze and critique, and build knowledge developing these skills can be linked through
independently. enhancing students' computational thinking.
Emphasizing problem-solving skills through
research and inquiry helped students develop higher-
order thinking skills [26], [27].

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5. Conclusion [5]. Rahman, S., Yasin, R. M., & Yassin, S. F. M. (2012).

Project-based approach at preschool setting. World
The Project-Based Learning combined with Applied Sciences Journal, 16(1), 106-112.
[6]. Burlbaw, L.M., Ortwein, M.J., & Williams, J.K.
Inquiry-Based Learning using Solver tools to promote
(2013). The Project Method in Historical Context.
computational thinking among undergraduate STEM Project-Based Learning. SensePublishers,
students can be summarized as follows: Rotterdam.
1. The learning management involved collaborative [7]. Hmelo-Silver, C. E. (2004). Problem-based learning:
analysis, planning, practice, evaluation, What and how do students learn?. Educational
psychology review, 16, 235-266.
development, and dissemination of work using
Doi: 10.1023/B:EDPR.0000034022.16470.f3
locally relevant problems. The instructor acts as a [8]. Guo, P., et al. (2020). A review of project-based
facilitator, guiding, assisting, and reinforcing. The learning in higher education: Student outcomes and
learning management model included the measures. International journal of educational
following components: principles, objectives, and research, 102, 101586.
the learning process, which consisted of defining Doi: 10.1016/J.Ijer.2020.101586.
the problem scenario, understanding and [9]. Musa, F., et al. (2012). Project-based learning (PjBL):
analyzing it, linking and identifying issues, Inculcating soft skills in 21st century
workplace. Procedia-Social and Behavioral
planning solutions, implementing and practicing Sciences, 59, 565-573.
skills, synthesizing knowledge, reviewing and Doi:10.1016/J.Sbspro.2012.09.315.
evaluating work, exploring and expanding [10]. Wu, H. K., & Hsieh, C. E. (2006). Developing sixth
knowledge, developing and disseminating work, graders’ inquiry skills to construct explanations in
and measurement and evaluation. Key conditions inquiry‐based learning environments. International
for successful implementation are also journal of science education, 28(11), 1289-1313.
considered. [11]. Marks, D. B. (2013). Inquiry Based Learning: What's
Your Question?. National Teacher Education
2. The model was of high quality, with an
Journal, 6(2).
effectiveness index of 0.561. [12]. Avsec, S., & Kocijancic, S. (2016). A path model of
3. Using the model, students showed significant effective technology-intensive inquiry-based
improvement in the components of computational learning. Journal of Educational Technology &
thinking, namely creativity, algorithmic thinking, Society, 19(1), 308-320.
cooperativity, critical thinking, and problem [13]. Alfieri, L., et al. (2011). Does discovery-based
solving, with statistical significance level of instruction enhance learning?. Journal of educational
0.001. psychology, 103(1), 1.
[14]. Kahn, P. and O’Rourke, K. (2003). Learning based on
Acknowledgments the process of enquiry. Proceedings of the 1-2
September 2003 conference. Manchester: University of
I would like to express my gratitude to the Rajamangala Manchester
University of Technology Suvarnabhumi for providing [15]. Saengprakai, S. (1999). Applying Optimization to
support to the first author to initiate this study. We are also find expenses in postal transportation. Faculty of
thankful to the research participants for their participation Information Technology, King Mongkut's University
in this study. of Technology Thonburi. [Masters dissertation]
[16]. Wing, J. M. (2008). Computational thinking and
References: thinking about computing. Philosophical Transactions
of the Royal Society A: Mathematical, Physical and
[1]. Panmanee A. 2014. Thinking practice for creative Engineering Sciences, 366, 3717-3725.
thinking. Bangkok: Chulalongkorn University [17]. ISTE (2015). Computational Thinking Leadership
Printing. Toolkit. ISTE. Retrieved from:
[2]. Pleumsamrankit, P. (2017). Factors Affecting https://cdn.iste.org/www-root/2020-
Learners' 21st Century Skills. Journal Valaya 10/ISTE_CT_Leadership_Toolkit_booklet.pdf
Alongkorn Review, 7(3), 141-158. [accessed: 20 June 2024].
[3]. Hillside Academy. (n.d.). Hillside AcademyPrivate [18]. National Research Council. (2011). Report of a
Christian School in Duvall, WA Workshop of Pedagogical Aspects of Computational
Preschool - 8th grade. Hillside Academy. Thinking. The National Academies Press.
Retrieved from: [19]. Abdellatif, L. M., et al. (2019). Transparency of law
https://hillsideacademy.com/teachers-role-in-project- making and fiscal democracy in the Middle
based-learning/ East. Public Sector Economics, 43(1), 49-77.
[accessed: 17 June 2024]. [20]. Yang, D., & Baldwin, S. J. (2020). Using technology
[4]. Mergendoller, J. R., & Thomas, J. W. (2000). to support student learning in an integrated STEM
Managing Project Based Learning: Principles from the learning environment. International Journal of
Field. Annual Meeting of the American Educational Technology in education and science.
Research Association, New Orleans.

610 TEM Journal – Volume 14 / Number 1 / 2025.

 TEM Journal. Volume 14, Issue 1, pages 602-611, ISSN 2217-8309, DOI: 10.18421/TEM141-53, February 2025.

[21]. Korkmaz, Ö., Çakir, R., & Özden, M. Y. (2017). A [29]. Law, K. E., Karpudewan, M., & Zaharudin, R. (2021).
validity and reliability study of the computational Computational thinking in STEM education among
thinking scales (CTS). Computers in human matriculation science students. Asia Pacific Journal of
behavior, 72, 558-569. Educators and Education, 36, 177-194.
[22]. Joyce, B., & Weil, M. (1999). Model of teaching (6th [30]. Tang, B., et al. (2020). Estimation of the transmission
ed.). Allyn & Bacon. risk of the 2019-nCoV and its implication for public
[23]. Durak, H. Y., & Saritepeci, M. (2018). Analysis of the health interventions. Journal of clinical medicine, 9(2),
relation between computational thinking skills and 462.
various variables with the structural equation [31]. Alfaro-Ponce, B., Patiño, A., & Sanabria-Z, J. (2023).
model. Computers & Education, 116, 191-202. Components of computational thinking in citizen
[24]. Marta, R., et al. (2024). Innovative Learning science games and its contribution to reasoning for
Strategies: Project-Based Learning Model for complexity through digital game-based learning: A
Excelling in Visual Programming. TEM framework proposal. Cogent Education, 10(1),
Journal, 13(1). 2191751.
[25]. Birgili, B. (2015). Creative and critical thinking skills [32]. Voogt, J., Fisser, P., Good, J., Mishra, P., & Yadav,
in problem-based learning environments. Journal of A. (2015). Computational thinking in compulsory
Gifted education and creativity, 2(2), 71-80. education: Towards an agenda for research and
[26]. Saad, A., & Zainudin, S. (2022). A review of Project- practice. Education and information technologies, 20,
Based Learning (PBL) and Computational Thinking 715-728. Doi:10.1007/s10639-015-9412-6
(CT) in teaching and learning. Learning and
[33]. Wing, J. M., & Stanzione, D. (2016). Progress in
Motivation, 78, 101802.
computational thinking, and expanding the HPC
Doi: 10.1016/J.Lmot.2022.101802.
community. Communications of the ACM, 59(7), 10-
[27]. Prananda, M. R., et al. (2020). Improving higher order
thinking skills (hots) with project based learning model 11. Doi: 10.1145/2933410
assisted by geogebra. Journal of Physics: Conference [34]. Wing, J. M. (2006). Computational
Series, 1467(1), 012027. IOP Publishing. thinking. Communications of the ACM, 49(3), 33-35.
[28]. Thanyaphongphat, J., et al. (2022). Promoting Doi: 10.1145/1118178.1118215
Computational Thinking with Visualization [35]. Günbatar, M. S., & Bakırcı, H. (2019). STEM
Programming through Project-Based Learning in teaching intention and computational thinking skills of
Computer Science. The 2022 WEI International pre-service teachers. Education and information
Academic Conference Proceedings. technologies, 24, 1615-1629.

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