Arduino-Based Experiments: Leveraging Engineering Design and Scientific Inquiry in STEM Lessons

Abstract

Organizing STEM activities based on scientific inquiry and engineering design processes is recommended for competency-based education in many countries, including Vietnam, to develop vital 21st-century practices. However, one of the challenges in the scientific inquiry process is the lack of equipment for conducting experiments. Therefore, there is a need for cost-effective and flexible instrument initiatives that students and teachers can design, create, and operate on their own. Additionally, real-world contexts like designing experiments for studying are also essential to engage students in engineering design processes. With its open-source platform, user-friendly interface, and limitless creative potential, Arduino is a valuable tool for STEM education. Hence, this study aims to develop Arduino-based experiments and suitable lesson plans to facilitate the implementation of STEM lessons following scientific inquiry and engineering design processes. In this study, we have proposed three Arduino-based experiments, followed by instruction plans, that students can build through engineering design processes to study several Physics concepts. The results show that microcontroller systems combined with common sensors are a low-cost yet effective approach with acceptable accuracy, allowing students to quantitatively and professionally investigate the relationship between physical quantities. In addition, 21st-century practices such as STEM literacy and design thinking are also concentrated in the context of working with the solutions for STEM problems.

Full text

International Journal of STEM Education for Sustainability, Vol 4, No.1, 2024, pp. 38-53
e-ISSN 2798-5091. DOI. 10.53889/ijses.v4i1.317
38
Arduino-Based Experiments: Leveraging Engineering Design and Scientific Inquiry in
STEM Lessons
Submitted 7 October 2023 Revised 25 October 2023 Received 25 October 2023
Nguyen Duc Dat1, Nguyen Van Bien2*, Nguyen Thi To Khuyen3, Nguyen Thi Viet Ha4, Hoang Thi Thai An5,
Ngo Thi Phuong Anh6
1,2,3,4,5,6Faculty of Physics, Hanoi National University of Education, Hanoi, Vietnam
Corresponding Email: *biennv@hnue.edu.vn
Abstract
Organizing STEM activities based on scientific inquiry and engineering design processes is recommended for
competency-based education in many countries, including Vietnam, to develop vital 21st-century practices.
However, one of the challenges in the scientific inquiry process is the lack of equipment for conducting
experiments. Therefore, there is a need for cost-effective and flexible instrument initiatives that students and
teachers can design, create, and operate on their own. Additionally, real-world contexts like designing
experiments for studying are also essential to engage students in engineering design processes. With its open-
source platform, user-friendly interface, and limitless creative potential, Arduino is a valuable tool for STEM
education. Hence, this study aims to develop Arduino-based experiments and suitable lesson plans to facilitate
the implementation of STEM lessons following scientific inquiry and engineering design processes. In this
study, we have proposed three Arduino-based experiments, followed by instruction plans, that students can build
through engineering design processes to study several Physics concepts. The results show that microcontroller
systems combined with common sensors are a low-cost yet effective approach with acceptable accuracy,
allowing students to quantitatively and professionally investigate the relationship between physical quantities.
In addition, 21st-century practices such as STEM literacy and design thinking are also concentrated in the
context of working with the solutions for STEM problems.
Keywords: STEM classroom, Engineering design, Scientific Inquiry, Arduino-based experiments
INTRODUCTION
STEM, an acronym for Science, Technology, Engineering, and Mathematics, is
frequently associated with strategies for advancing a nation's progress in these domains (Assefa
& Rorissa, 2013; MacIsaac, 2016; Silva et al., 2020). In the context of education, the reference
to STEM underscores the education system's concentration on Science, Technology,
Engineering, and Mathematics disciplines by highlighting the incorporation of cross-
disciplinary STEM subjects (e.g. Kelley & Knowles, 2016; Madden et al., 2013), real-life
applications (e.g. Kefalis & Drigas, 2019; Nikitina & Ishchenko, 2022), as well as the
enhancement of students' qualities and competencies (e.g., Fajrina et al., 2020).
According to Kennedy & Odell (2014), effective STEM education programs and curricula
should embody 11 key characteristics, including two notable features: the promotion of
engineering design and problem-solving and inquiry-based learning (Kennedy & Odell, 2014).
In addition, the engineering design process (EDP) provides the opportunity for students to
embark on scientific inquiry (SI) and open discovery (Hafiz & Ayop, 2019). On the other hand,
using EDP, such as in science education, will allow the students to apply science knowledge

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and SI in an authentic context and learn mathematical reasoning to make decisions (Kelley &
Knowles, 2016).
However, one of the challenges in the SI process is the lack of equipment for conducting
experiments (Kranz et al., 2023). Therefore, there is a need for cost-effective and flexible
instrument initiatives that students and teachers can design, create, and operate on their own.
Furthermore, real-world contexts like designing experiments for studying are also essential to
engage students in EDP.
Arduino, with its open-source platform (O'Sullivan & Igoe, 2004), user-friendly interface
(Thompson, 2011), and limitless creative potential, serves as a valuable tool for STEM
education (e.g. García-Tudela & Marín-Marín, 2023; Plaza et al., 2018). Regarding knowledge
comprehension, research demonstrated the usefulness of Arduino and 3D printing in teaching
STEM concepts in educational robotics classes (Souza & Sato, 2019). Regarding skills and
competencies, it was found that integrating Arduino into STEM activities improved students'
skills in establishing cause-effect relationships (Arı & Meço, 2021). Similarly, Vexler et al.,
(2022) developed an interdisciplinary course on circuit design using Arduino, which enhanced
students' scientific and technological capabilities (Vexler et al., 2022). Overall, studies
highlighted the potential of Arduino-based experiments for improving STEM Education.
One of the approaches involves introducing educational projects where students employ
Arduino to construct products like robots and machines, thus gaining knowledge, honing their
abilities, and nurturing their passion for learning (e.g., Di Giacomo & Sandri, 2022; Morze,
2018). Moreover, Arduino can be a cost-effective platform for creating devices or conducting
experiments that align with the scientific inquiry processes within STEM education (e.g., Sari
& Kirindi, 2019).
Building upon the mentioned information, it becomes evident that STEM-integrated
lessons have the potential to cultivate students' competencies and instill 21st-century practices,
viewed through the lens of EDP applied to the creation of instruments for SI. Currently, there
are several studies on Arduino-based experiments in STEM Education, but the majority of them
primarily employ Arduino as a teaching tool (Çoban & Erol, 2021, 2022; Galeriu et al., 2014)
or a remote initiative (Cvjetković & Stanković, 2017; Martin et al., 2021) rather than delving
into how it can serve as a study object in students' educational processes. Hence, this study
aimed to develop Arduino-based experiments that aim to facilitate the development of 21st-
century practices of students in STEM classrooms. The study goal is equivalent to the following
research questions:

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1. How can Arduino-based experiments be designed to be implemented in STEM lessons for
students?
2. How can we implement developed Arduino-based experiments to leverage Engineering
Design Processes and Science Inquiry Processes in STEM lessons?
METHOD
Developing Arduino-based experiments
To ensure that the Arduino-based experiments are customizable, under control, cost-
effective, easy to maintain, and accessible for teachers and students, we based on the procedure
encompassing six design principles to develop open-source hardware designs for scientific
equipment proposed by Oberloier & Pearce (2018).
Firstly, we study existing experiments used to investigate Physics concepts. These
experiments either involve expensive measuring instruments or need a more precise approach
comparable to modern scientific measurement methods.
After that, we consider alternatives of using the Arduino board combined with sensors as
measurement instruments. For example, current sensors can help to measure the power of
electrical devices, or temperature sensors can replace thermometers. After that, we develop
experiments, including apparatus setup, programming, and executing procedures. This design
process follows design principles including:
• Open-Source Approach: Free and open-source software tool chains and open hardware are
prioritized throughout fabrication, promoting accessibility and collaboration.
• Simplicity and Efficiency: Efforts are made to minimize both the number and variety of
parts in the device and the complexity of the required tools, ensuring ease of assembly and
maintenance.
• Resource Conservation: The design seeks to minimize material usage and production costs,
promoting sustainability and cost-effectiveness.
• Digital Fabrication: Components that can be digitally manufactured using widely available
tools like the 3D printer are favored, enhancing accessibility and reducing production
barriers.
• Customization Capability: Parametric designs with pre-designed components are
employed, allowing flexibility and customization to suit specific needs and requirements.

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• Global Accessibility: Components that cannot be economically produced using existing
open hardware methods are sourced from off-the-shelf parts, ensuring availability and
accessibility worldwide.
Then, developed experiments are tested to verify the quality of functions, accuracy, and
whether they are validated for the targeted functions.
Finally, the experiments' design, manufacture, assembly, calibration, and operation were
documented and ready to be shared in the open-access literature.
Developing lesson plans
There are several approaches when designing STEM lessons, there are different
approaches, including silo, embedded, and integrated (Roberts & Cantu, 2012). The silo
approach involves the separation of STEM components. It is considered the most traditional,
primarily focused on teacher-driven activities, often neglecting the real-world problem-solving
aspect of learning (Breiner et al., 2012). Conversely, the embedded approach is well-known for
emphasizing acquiring knowledge by studying real-world problems and problem-solving
techniques within social, cultural, and functional contexts (Chen, 2001). Lastly, the integrated
approach blurs the boundaries between individual subjects, teaching science, technology,
engineering, and mathematics as a unified whole (Wang et al., 2011). In this study, in the
context of organizing curriculum content based on subjects, the most suitable approach is
embedded (Roberts, 2012). A STEM lesson, where teachers contain regular classroom lessons
to teach subject content in a STEM approach, can be implemented using the SI and EDP
processes as outlined in Figure 1. In this study, we constructed a teaching plan based on
organizing learning activities that incorporate both processes.
Firstly, we assessed the compatibility of Arduino-based experiments with the learning
objectives or specific knowledge units. Then, we developed an SI process for the targeted
learning objectives or knowledge units, starting from the phases of problem definition, idea
development, planning, problem-solving, and drawing conclusions. In this SI process, Arduino-
based experiments were used during the problem-solving phase for students to investigate or
verify scientific hypotheses. Constructing these experiments required students to follow the
EDP, beginning with defining the product, developing ideas, planning, and moving on to
designing and presenting solutions.

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Figure 1. STEM learning activities following SI and EDP
RESULTS AND DISCUSSION
Arduino-based experiments
Following the mentioned steps, we have proposed three Arduino-based experiments.
Determining the specific capacity of liquids
The setup of our Arduino-based experiment to determine the specific capacity of liquids
(Figure 2) includes a calorimeter with a heating resistor, a DS18B20 temperature sensor, an
ACS712-20A current sensor, a DC voltage sensor module (0-25V), and an Arduino Uno to read
sensor values and transmit them to computer software. The wiring connections of these sensors
are depicted in Figure 2. The experiment can be powered by a 12V battery system or a DC
power supply to operate the equipment and monitor sensor values through computer software.

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Figure2. Set up an Arduino-based experiment to determine the specific capacity of liquids.
A short Arduino programming code snippet is necessary to collect experimental data.
First, the computer will compile this program and then send it to the Arduino board via a USB
cable. The Arduino board will execute the code and continuously send the values of the three
sensors back to the computer. These values are sent to the computer every 1000 ms. The list of
experimental measurements is displayed on the software interface as a table and can be saved
as a Microsoft Excel spreadsheet.
The data analysis (Figure 3) initially involved extracting specific values suitable for
simple calculations suitable for K-12 students. The data obtained indicates that the temperature
value did not change significantly due to limitations in the smallest division of the measuring
device; the energy varied continuously. Therefore, the energy value at a given temperature can
be calculated as the average of the maximum and minimum energy values. This analytical
approach yielded the specific heat capacity of water, ranging from 3970 J/kg.K to 4379 J/kg.K,
which deviates by a maximum of 5.11% from the theoretical value of 4184 J/kg.K. Further
analysis utilized Origin 2021, a robust software application designed specifically for scientific
computations. We employed a fitting function, which yielded the specific heat capacity of water
as about 4183 J/kg.K. The R-square value is remarkably close to one, providing additional
evidence that the linear model accurately describes the experimental data.

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Figure 3. Data analysis of Arduino-based experiment to determine the specific capacity of
water.
Verifying the law of conservation of momentum
In this Arduino-based experiment (Figure 4), we employed Arduino Uno and Doppler
Radar to determine the velocity of an object. The HB100X10.525GHz obstacle sensor is a
Doppler module operating in the X-band. It includes a dielectric resonator oscillator (DRO)
integrated with antennas for signal transmission and reception. The sensor emits a 10.525GHz
signal with a range of up to 20 meters. Notably, this sensor's operation is unaffected by external
factors such as noise and humidity and is designed to resist strong radio frequency interference.
Additionally, the module incorporates amplification and comparison circuits using the
LM6482 IC to improve data acquisition accuracy. During experiments, an ultrasonic sensor
was also utilized to detect collision between two carts. In this setup, distance and Doppler radar
sensors were placed at either end of the experiment. The Doppler radar read the velocity of cart
A throughout the investigation. At the same time, the distance sensor emitted pulses to measure
the distance of cart B, facilitating the separation of data before and after the collision. Before

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the collision, as the distance remained constant, the velocity before the collision was calculated
and displayed on the screen. When the two carts collided and moved toward the distance sensor
(resulting in decreased B's distance), the post-collision velocity was calculated and displayed
on the screen.
Figure 4. Set up an Arduino-based experiment to verify the law of conservation of
momentum.
Throughout these experiments, only the velocities immediately before and after the
collision were observed, effectively assuming the system was a closed system. Momentum
calculations were performed for each measurement (Figure 5). In the first measurement, with
both A and B having a mass of 0.1 kg, the post-collision momentum of the system differed by
less than 1.33% from the pre-collision momentum. In the second measurement, where A's mass
was increased to 0.15 kg by adding a 50g weight, the post-collision momentum differed by less
than 11.29% from the pre-collision momentum. In the third measurement, with A's mass
increased to 0.15 kg and B's mass at 0.1 kg, the post-collision momentum differed within the
range of 3 - 11.11% from the pre-collision momentum.

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Figure 5. Data analysis of Arduino-based experiment to verify the law of conservation of
momentum.
Compared to traditional experiments measuring velocity using optical gate barriers,
where the obtained velocity represents the average velocity of the cart during the light barrier
activation period, this approach reduces significant experimental errors attributed to energy loss
due to friction. The analysis and data acquired from the sensors align well with verifying the
conservation of momentum law and K-12 students' comprehension.
Investigating the light interference phenomenon
The experimental setup (Figure 6) includes the following components. The light source
is a red laser with a wavelength (λ) range of 630 - 670nm. A distance of a=0.8mm separates
two slits. To collect data and control the system, we use an Arduino Uno. Light intensity data
is collected using the BH1750FVI, a digital ambient light sensor that communicates via I2C.
This sensor has a wide operating range with high resolution (1 - 65535lx), providing high
accuracy.
Additionally, the sensor has low power consumption due to its auto-power-off feature.
With this sensor, there's no need for an additional resistor as they are already pull-up resistors
on the Arduino board connected to the 3.3V output, reducing complexity in the experiment
setup. A Stepper Motor and its accompanying A4988 Driver, powered by a 12V supply, are
used to support the movement of the BH1750FVI light sensor to different measurement
positions.

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Figure 6. Setup of Arduino-based experiment to study the light interference phenomenon.
The system with two slits splits the light source (S) into two sources (F1 and F2) with the
same wavelength and in-phase, with a constant phase difference over time. The light from
sources F1 and F2, when they converge at various positions (x), creates an interference pattern.
The 12V power supply powers the stepper motor and its driver. The stepper motor rotates in
small increments (∆φ = 1.8o/32 = π/320 radians) with a diameter of the rotating shaft (d) being
12mm. This rotation results in the linear movement of the conveyor in discrete steps (∆x). The
light sensor is attached to the conveyor and, controlled by the stepper motor, the sensor moves
a small distance (∆x) within a short time interval (∆t). This allows for measuring light intensity
(I) at corresponding positions (x). The obtained data provides interference patterns to be
calculated and applied in various problem-solving scenarios.
Figure 7. The graph of light intensity regarding position.

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According to the theory, the dark fringes in interference patterns should have zero light
intensity. However, the measured experimental graph (Figure 7) shows non-zero values for
these dark fringes because the sensor calculates the average light intensity over the entire sensor
area instead of at a specific position. The experimental graph also exhibits discrepancies when
compared to the theory due to other factors such as environmental influences or light scattering.
Nevertheless, the obtained results clearly illustrate the rise and fall of the graph, explaining the
formation of bright and dark fringes on the screen.
Based on the graph of light intensity obtained, we can calculate the fringe width (i), the
distance between two consecutive bright or dark fringes. From the graph, we can calculate the
fringe width as follows: i = n.∆x = 40. ∆φ.r = 40.∆φ.d/2 = 40.(π/320).6.10-3 = 2,35.10-3(m). The
LED used has a wavelength in the range of 640nm - 760nm, the distance from the slits to the
screen is approximately 1.55 meters, and the separation distance between the two slits is 0.5
millimeters. Theoretically, the screen's fringe width (i) should be between 1.92 and 2.36
millimeters. Therefore, the experimental results show an error in i ranging from 4% to 18%. If
we consider the experimentally determined fringe width (i) as accurate, we can reverse-
calculate the precise wavelength of the laser light source to be 758.10-9 m.
Instruction plans.
After developing and testing Arduino-based experiments, we design equivalent
instruction plans based on strategies to create engaging learning activities utilizing these
experiments to leverage Engineering Design Processes and Science Inquiry Processes in STEM
lessons, including activities with learning materials like worksheets and videos. These teaching
plans are developed based on the two frameworks we have mentioned. In these plans, students
will acquire lesson knowledge through the SI process, and the EDP will be integrated into it
through activities involving the design of experiments to investigate or verify students'
scientific hypotheses. Figure 8 below is an example of a lesson plan using this approach to teach
about specific heat capacity.

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Figure 8. Teaching processes for a STEM lesson with Arduino-based experiment to study
specific heat capacity
Overall, developed experiments allow the experiment to be conducted fluently and make
precise measurements while ensuring the differences in the physical quantities between
experimental results and the actual value are small enough to be acceptable for K12
experiments. Moreover, the total expenditure of the experimental prototype of the project is
suitable for Vietnamese students. The cost can be reduced by designing the microcontroller
board instead of using the Arduino board directly.
The designed lesson plans for STEM education in this study are believed to satisfy both
pedagogical principles and the specific requirements of a STEM lesson because we have
considered the following aspects. Effective STEM lesson plans must harmoniously integrate
pedagogical principles that encourage active learning (Herreid, 2006; Srinath, 2014),
differentiation (Balgan et al., 2022), and assessment (Karakaya & Yılmaz, 2022; Potter et al.,

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2017). Furthermore, these STEM lesson plans should captivate students through hands-on
activities (Cloutier et al., 2016; Wysocki et al., 2013) aligned with learning objectives to
promote inquiry-based learning while connecting classroom knowledge to real-world
applications (Rennie et al., 2017). Additionally, a STEM lesson plan should emphasize
interdisciplinary collaboration and developing 21st-century skills (Fajrina et al., 2020),
ensuring that students acquire subject knowledge and the skills and mindset necessary for
success in STEM fields and beyond.
CONCLUSION
In this study, we have proposed Arduino-based experiments, followed by instruction
plans, that students can carry out to study several Physics concepts. Those experiments have
acceptable degrees of accuracy, and the instruction plans have the potential to develop students'
practices.
Limitations of the research
Despite having developed Arduino-based experiments and lesson plans based on STEM
teaching organization principles, additional intervention research is still needed to investigate
the effectiveness of these impacts on students. Subsequent studies may incorporate these lesson
plans into real classroom settings or apply these Arduino-based experiments to other learning
activities.
ACKNOWLEDGEMENT
The Authors thank to the Vingroup Innovation Foundation which funded this research
through the Scholarship Programme of Vingroup Innovation Foundation (VINIF), code
VINIF.2022.ThS.022.
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