Enhancing Students’ Interest in Physics Concepts with a Low-Cost STEM Tool Focused on Motivation in Rural Areas of Developing Countries

Abstract

Physics concepts are considered an essential component of STEM (science, technology, engineering, and mathematics) education and fundamental for economic and technological development in the world. However, there can be student academic underperformance, such as the school environment, learning media and infrastructure, student interest and emotions, as well as social and economic development factors in communities. These problems are even more acute in rural areas of developing countries, where poverty is high and teachers often lack the necessary technological skills. The aim of this study was to evaluate the impact of a low-cost STEM tool focused on motivation in learning, in terms of five variables of interest in physics in rural areas, as well as the durability of the tools used to learn 12 physics concepts. A quasi-experimental study was conducted with the participation of 78 high school students, with an average age of 15.82 years, in a rural area of Guerrero, Mexico. The results showed that using the STEM tool significantly increased students’ interest in learning methodology, active participation, and attitude towards physics, facilitating the teacher’s work. In addition, the 3D construction kit used in the experimentation, besides being low-cost, proved to be affordable and durable, making it ideal for use in rural areas.

1. Introduction

Science, technology, engineering, and mathematics (STEM) skills drive innovation, economic growth, and societal wellbeing (Sellami et al., 2023). Despite the growing importance of STEM education, there has been a decline in the number of students graduating from STEM disciplines (Ahmad et al., 2023). One of the main reasons for this decline is students’ lack of interest in STEM courses (Lytle & Shin, 2020). The problem is exacerbated in rural areas of developing countries due to a lack of technological infrastructure, as well as a shortage of teachers and students with technological knowledge and low economic conditions (Manikutty et al., 2019).

Physics is a fundamental subject in STEM (Saleh et al., 2020), playing a vital role in global technological advancements and economic development (Simeon et al., 2020). Unfortunately, the PISA test, which assesses the academic level of 15-year-old students worldwide, reveals that more than 50% of Mexican students perform poorly in physics and science (OECD, 2023). Disinterest in these subjects and the reduced supply of STEM careers influence student enrollment in STEM-related courses (Addido et al., 2023). Mexico still has too few students with the skills necessary to thrive in the digital age, as evidenced by its average PISA scores in reading, math, and science being below the OECD average (OECD, 2022). As discussed in the World Economic Forum’s Future of Jobs 2023 report, these data contradict the world’s current needs. The report predicts that between 2023 and 2027, up to 75% of companies are expected to adopt technologies such as artificial intelligence, big data, and cloud computing. In Mexico, 55% of new jobs are projected to be related to technology (WEF, 2023).

Previous studies have indicated that motivation plays a crucial role in academic performance, particularly among high school students. Motivational factors have a more substantial impact on science performance than cognitive and metacognitive strategies (Ortega-Torres et al., 2020). The implementation of active methodologies, such as gamification, the flipped classroom, and STEM approaches, significantly improves student motivation, academic performance, and participation and plays a crucial role in preventing school dropout (Fan & Wolters, 2014; Gaitan & De la Cruz, 2024).

1.1. STEM Learning Methodologies

Students perceive physics concepts as challenging to understand and find the subject boring (Simeon et al., 2020); therefore, some studies have attempted to address this issue through STEM education. A methodology that promotes constructivist learning through play, the arts, exhibitions, lectures, and workshops on physics topics may increase students’ interest but not necessarily their learning (Souza & Duarte, 2015). Project-based learning can enhance the learning of physics topics, such as Newton’s laws; however, student performance is not closely monitored when only the final product is assessed, as the project’s success depends directly on the teacher’s commitment (Saleh et al., 2020). The combination of collaborative STEM education and computational thinking tools could enhance physics learning; however, a lack of skills in using these tools may prove to be a disadvantage in implementing this methodology (Hutchins et al., 2020).

Artificial intelligence (AI) in education offers potential benefits such as improving personalized learning experiences, boosting student engagement, and optimizing academic performance (Katiyar et al., 2024). However, studies also indicate that the integration of AI can hinder critical thinking, encourage overdependence, and affect student retention in the long term (Talgatov et al., 2024). Furthermore, studies indicate that AI-driven tools are often developed from a computer science perspective, overlooking the active involvement of teachers and educational theory (Chichekian & Benteux, 2022). In addition, ethical considerations such as data privacy and algorithmic bias must be addressed (Sasikala & Ravichandran, 2024).

1.2. STEM Tools Focused on Motivation with the LEGO Mindstorms EV3^® Kit

In STEM education, robotics kits such as Lego Mindstorms^® can enhance students’ learning in physics by allowing them to design, build, and test experiments with 3D parts (Church et al., 2010). Using these kits in the educational process improves students’ cognitive processes and is associated with high motivation in the classroom (Ospennikova et al., 2015). D’Amico et al. (2020) proposed an intervention to measure the impact of a STEM tool on physics learning, reporting improvements in physics problem-solving. Addido et al. (2023) proposed an intervention to measure the impact of using a STEM tool for physics learning and interest in STEM education and careers. The study reported an increase in physics learning and interest in STEM education and careers. Both studies were carried out in urban areas.

1.3. Low-Cost STEM Tools Focused on Motivation in Rural Areas in Developing Countries

In developing countries, rural areas are defined as those outside urban areas (Lerner & Eakin, 2011). The academic literature characterizes rural areas as lacking technological infrastructure, providing poor training for teachers and students, and experiencing high levels of poverty (Miah & Omar, 2012). Manikutty et al. (2019) conducted a study with Indian students that aimed to measure intrinsic motivation using a low-cost STEM kit. However, some difficulties arose due to the students’ and teachers’ limited knowledge of technology, robotics, programming, and electronics. Simeon et al. (2020) proposed an intervention to measure the impact of design-thinking methodology on physics learning, in which students in Nigeria designed their sketches and prototypes. Badeleh (2021) proposed an intervention to measure the effect of a STEM tool on the learning and creativity of physics students. While the experimental group demonstrated increased creativity and physics learning, issues such as a lack of technological infrastructure, limited internet speed, limited access to academic resources, and the high cost of training courses and robotics materials were encountered. Ngugi et al. (2023) proposed an intervention to measure the impact of low-cost educational robotics on the interest of physics students in Kenya. The materials used in all interventions were not affordable, durable, or reusable.

1.4. Purpose and Significance of Research

The significance and primary purpose of this study is to apply a reusable and easy-to-assemble kit in a physics class to motivate and improve physics learning in rural community schools. Some other opportunity areas were identified in previous interventions, such as the lack of student interest that caused absenteeism and internal conflicts, the limitations of the technological infrastructure for computer equipment and access to educational resources, as well as the lack of a learning methodology that required prior knowledge of robotics, electronics, and programming for teachers and students. In rural areas of developing countries, a high rate of poverty often prevents schools from having the necessary resources to foster learning and interest in physics. This study evaluated the impact of a new low-cost and easy-to-use STEM tool focused on motivation to increase participation, attitude, and interest in physics concepts among high school students in rural areas for the first time in a curricular course with groups previously enrolled in the physics class.

1.5. Research Question

The research question posed for this study is the following:

What is the impact of using a new low-cost STEM tool focused on motivation to increase interest in physics concepts compared to traditional physics instruction among high school students in rural areas in developing countries?

2. Materials and Methods

2.1. STEM Tool Focused on Motivation

The STEM tool, focused on motivating students to learn physics (Figure 1), consists of five elements: (1) a STEM classroom that guides students through a didactic methodology for learning physics concepts; (2) an environmentally friendly yet affordable and low-cost 3D parts kit for physics experiments; (3) electronic parts: a geared motor, a switch, and a 9-volt rechargeable battery; (4) the free Phyphox^® mobile application for measuring physical quantities in experiments; and (5) visual and audiovisual educational material freely available on the Internet. The tool evaluates 12 physical concepts: motion, distance, displacement, velocity, speed, uniform rectilinear motion (URM), friction, acceleration, inclined plane, and Newton’s first, second, and third laws. Both teachers and students can use the tool without prior knowledge of robotics, electronics, or programming.

2.1.1. STEM Class

The proposed STEM class structure begins with a pre-test to assess students’ previous knowledge of physics and their interest in the subject. When assessing interest, five variables are measured: content, learning methodology, active participation, perceived relevance in the class, and general attitude toward the class. Next, teams of 4 to 5 students are formed so that they all interact with the STEM tool. Each member has a specific role within the team’s activities, which changes as the class progresses. The proposed didactic materials guide the students in understanding and becoming interested in physics concepts during class. At the same time, they can be used as visual and audiovisual instructions for assembling the experiments using the 3D kit, the mobile application, and the electronic parts. At the end of the intervention, a post-test is used to re-evaluate knowledge and interest.

2.1.2. 3D Parts Kit and Electrical Components

The 3D parts kit is an original proposal for assembling physics experiments. It consists of 21 3D-printed parts made of PLA (polylactic acid) filament, a natural polymer that is biodegradable, compostable, and easy to recycle. In addition, the parts are durable and drop-resistant, allowing students to manipulate them without damaging, breaking, or deforming them. The kit also includes two rubber bands of different sizes. The proposal does not require the use of a microcontroller. The only electronic components used are a 38 rpm double-shaft L-type geared motor to generate motion, a 1-pole and 2-position toggle switch to turn the circuit on or off, and a 9-volt rechargeable battery to power the circuit, along with a battery holder.

Figure 2 illustrates the 27 components that comprise the kit. The parts are designed to be reused throughout all experiments. If a part is damaged or lost, it can be quickly reprinted using a low-cost 3D printer. The average print time for each part is 30 min, varying depending on the size and weight. The kit was designed to be easy to use, developing both kinesthetic and logical–mathematical skills, thereby stimulating learning and interest in physics. For this reason, the experiments are planned to be conducted in accessible spaces, without obstacles, and at ground level, where the student can feel comfortable and imagine that they are playing, rather than taking a science class. The student connects the parts using Dupont cables, and there are no additional tools required.

2.1.3. Phyphox^® App

The proposal can work with some free mobile applications, such as Arduino Science Journal^®, Phyphox^®, etc., which utilize the mobile phone’s microprocessor and sensors to measure physical quantities and present the results graphically and numerically to the student through a user-friendly interface. In the present study, we utilized the free mobile application Phyphox^® to measure and analyze the acceleration of a moving object.

2.1.4. Educational Didactic Material

The proposal considers that each student has a different learning style; so, visual and audiovisual didactic materials are included. Short videos with clear easy-to-understand language are used to help students grasp physics concepts. For the assembly of the experiments, assembly instructions and videos of each experiment were designed and uploaded to YouTube^®. Figure 3 shows the visual didactic material used to set up the experiment of a multi-position ramp, facilitating an understanding of the topics of the Inclined plane and Newton’s laws. Figure 3a shows the initial step that explains how all the sections of the multi-position ramp are first joined together, while Figure 3b shows how all the structures are later assembled to put the ramp upright.

2.2. Sample

A total of 78 students participated in this study, comprising 39 in the control group and 39 in the experimental group, which corresponded to the total number of students enrolled in the second year of high school at the Colegio de Bachilleres del Estado de Guerrero, located in southern Mexico.

The characteristics of the groups (control and experimental) are shown in

Table 1. Scholar groups in which the intervention with the STEM tool to learn physics was carried out.

Classroom	Group	Specialty	Total Male	M Age Male	SD Male	Total Female	M Age Female	SD Female	Total Students
402	control	information technology	12	15.92	0.51	6	15.83	0.41	18
403	experimental	information technology	11	15.82	0.40	5	16	0.71	16
405	control	architectural drawing	9	15.67	0.50	12	15.67	0.49	21
406	experimental	architectural drawing	12	15.83	0.83	11	15.82	0.40	23

M: Mean, SD: standard deviation.

. Prior to the intervention, the school administration at the center determined the composition of the groups based on the specialty chosen by the students during enrollment, which explains the gender imbalance in the groups. The students taking physics came from the computer science and architectural drawing groups, which represent the total available sample. A control group and an experimental group were taken from each specialty. All groups were taught on the morning shift. The mean age of the students was 15.82 years, with a standard deviation of 0.54 years.

2.3. Study Design

A quasi-experimental study was conducted. To make the intervention more personalized, the experimental and control groups were divided into two equal parts, creating four groups. The control group received traditional physics instruction, while the experimental group received physics instruction using our STEM tool for physics learning. To control homogeneity in the level of instruction, the intervention was delivered by the same teacher. The physics concepts for both groups were 12: motion, distance, displacement, velocity, speed, URM (uniform rectilinear motion), friction, acceleration, inclined plane, and Newton’s first, second, and third laws. The experimental and control groups were given pre-test and post-tests to measure learning and interest.

2.4. Data Collection Instruments

This study used 2 data collection instruments: a questionnaire to measure learning and a survey to measure interest. Both instruments were the same for the pre-test and post-test groups. Before and after the intervention, each group was administered a 10-item multiple-choice questionnaire to measure knowledge based on the structure of the science items of the PISA 2015 test (OECD, 2016). The knowledge score ranged from 0 to 10 and was calculated by summing the correctly answered items. A sample of two questions from the test to measure learning is shown in

Table 2. A sample of two questions from a set of ten was used to measure learning.

A toy cart with a mass of 0.5 kg travels along a straight 5 m stretch divided into two consecutive surfaces: Section 1: fine sand. Section 2: smooth asphalt. Question 1 Which of the following statements is most likely to be true about the average speed of the cart in each section? (A) The average speed will be higher on fine sand. (B) The average speed will be higher on smooth asphalt. (C) The average speed will be the same in both sections. (D) It cannot be determined without knowing the force applied.

Question 2 Which of the following options best describes how friction between the wheels of the cart and the surface of each section influences the average speed obtained? (A) The greater the friction, the lower the average speed. (B) The greater the friction, the higher the average speed. (C) Friction does not alter the average speed if the mass is constant. (D) Friction only affects the final speed, not the average speed.

. To measure interest in the subject, a questionnaire with a Likert scale of 25 items was used, divided into five dimensions: (1) content interest, (2) learning methodology, (3) active participation, (4) course relevance, and (5) general attitude. The survey referenced some concepts of measuring interest in science by Lamb et al. (2012). The interest rating was scaled from 5 to 25 and was obtained by averaging the scores of the five sections. The questionnaires to measure learning and interest are available in Appendix A and Appendix B, respectively.

2.5. The Study Process

Figure 4 shows the complete structure of the study process. The topics were developed over five two-hour sessions, each spanning two weeks, within the physics curriculum (

Table 3. Proposed distribution of physics concepts to be covered per 2 h session.

Session 1	Session 2	Session 3	Session 4	Session 5
Motion Distance Displacement	Velocity Speed URM	Friction Acceleration	Inclined Plane Newton’s First Law	Newton’s Second Law Newton’s Third Law

). In the first session of the proposed STEM class, teams of four to five members were formed to allow everyone to work actively.

Each student was assigned a role within the team: project leader (1 student), assembler (1–2 students), and data analyst (1–2 students). This assignment also allowed them to be exposed to all elements of the STEM tool.

Each team was provided with an electronic file containing the instructions for each session, links to videos, and assembly diagrams for each experiment. Students could view the files and videos from either a computer or a smartphone. They were also provided with a box containing the 3D kit and electronic parts. They also installed the Phyphox^® application on their smartphones to measure and analyze the physical quantities.

At the beginning of each session, the students watched a short video about an essential event in the history of physics related to the topics to be covered. At the end of the video, each team was asked to do a group reflection. Within the electronic file, the students could watch a video that explained each of the physics concepts. The teacher coordinated a group reflection that also served to clarify any doubts that students may have had. The next stage of the session involved practicing the concepts previously explored through experimentation. To do this, students could watch the assembly videos or refer to the assembly diagrams for each experiment. In the first two sessions, students experimented using parts of the 3D kit and electronic components. They used a prototype of an electric car (Figure 5a) to identify concepts such as motion, MRU, distance, and displacement; they also calculated the speed and velocity using the relevant physics formulas. Students also used a flexometer to measure the displacement of the electric trolley and a smartphone stopwatch to measure time. These activities were performed on the classroom floor.

In the third session, the students replaced the wheels of the electric cart and drove it on uneven terrain to understand the concept of friction. In the same session, the students set up an experiment using a garter-driven trolley powered by rubber bands, which could hold a cell phone inside (Figure 5b). The students placed the cell phone and measured the car’s acceleration with the Phyphox^® application. In the fourth session, the students set up the experiment of a ramp with different inclinations to understand the concept of an inclined plane (Figure 5c). In the last two sessions, the ramp, electric cart, and cell phone cart were combined to perform several exercises that helped understand Newton’s three laws.

2.6. Data Analysis

The collected data were first coded and transferred to the SPSS 21.0 program. Then, a normality analysis was performed on the datasets obtained using the Kolmogorov–Smirnov test, as the number of participants exceeded 50. The results of the Kolmogorov–Smirnov test indicated that the data gathered were normally distributed. Then, the parametric paired samples t-test was used to compare the pre-test and post-test datasets, which showed a normal distribution. The analysis had a significant level of 0.05. The results of the analyses in which a significant difference was found were examined to determine the effect size by calculating Cohen’s d, where effect sizes of 0.2, 0.5, and 0.8 are considered small, medium, and large (Cohen, 2013).

3. Results

3.1. Findings on the Student’s Learning

Table 4. Comparison of physics learning between the control and the experimental group.

	Pre-Test		Post-Test
Group (n)	M	SD	M	SD	p	Cohen’s d
Control (39)	3.26	1.09	4.21	1.54	0.0005 *	0.71
Experimental (39)	2.92	1.4	3.97	1.86	0.0010 *	0.64

M Mean, SD standard deviation. * p < 0.05.

presents the effects on students’ learning in the traditional class of the control group and the STEM class that used the STEM tool for physics learning in the experimental group. The results of the t-test analysis for the corresponding samples indicate significant differences in the increase in learning between the control and experimental groups (p = 0.0005 and p = 0.0010). The mean learning score of the students in the control group was observed to be 3.26 (SD = 1.09) and increased to 4.21 (SD = 1.54) at the end of the study, indicating a significant increase in student learning. At the same time, it was observed that the mean learning score of the students in the experimental group was 2.92 (SD = 1.4) at the beginning of the study and increased to 3.97 (SD = 1.86) by the end of the study; this finding also indicates a significant increase in student learning. Examining Cohen’s d coefficients, it can be observed that there is a significant difference with a median effect size in the control and experimental groups (0.5 < |d| > 0.8).

3.2. Findings on the Student’s Interest

Table 5. Comparison of physics interest between the control and experimental groups.

	Pre-Test		Post-Test
Group (n)	M	SD	M	SD	p	Cohen’s d
Control (39)	16.57	1.31	16.65	0.99	0.4855 *	-
Experimental (39)	17.7	0.95	19.94	1.04	0.0138 *	2.25

M Mean, SD standard deviation. * p < 0.05.

shows the effects on the students’ interest in traditional classes in the control group and STEM classes using the STEM tool for physics learning in the experimental group. The results of the t-test analysis for the corresponding samples show significant differences in the increase of interest in the experimental group (p = 0.0138); however, there were not in the control group (p = 0.4855). The mean interest score of the students in the control group was 16.57 (SD = 1.31) and increased to 16.65 (SD = 0.99) at the end of the study; this finding does not indicate a significant increase in student interest. At the same time, it was observed that the mean learning score of the students in the experimental group was 17.70 (SD = 0.95) and increased to 19.94 (SD = 1.04) at the end of the study; this finding indicates a significant increase in student interest. Examining the Cohen’s d coefficients reveals a significant difference with a large effect size in the experimental group (|d| > 0.8). Meanwhile, the control group did not exhibit a significant difference; therefore, the effect size was not calculated.

3.3. Findings from the Comparison of Learning Gains and Interest Gains Between the Control and Experimental Groups

The t-test analysis of learning gains revealed significant improvements for both groups in physics, with the control group (p = 0.0005) and experimental group (p = 0.0010) showing significant differences. Regarding interest, the control group did not show significant improvement (p = 0.4855), whereas the experimental group did (p = 0.0138). A t-test comparing normalized learning gains between the experimental group and the control group showed that the experimental group did not score significantly better on learning (p = 0.7502), but the experimental group did score significantly better on interest (p = 0.0184).

3.4. Findings from a Detailed Analysis of Student Interest in the Experimental Group

The results of a detailed analysis of the five dimensions of interest in the experimental group are shown in

Table 6. Comparison of the experimental group’s interest in physics in all dimensions.

	Pre-Test		Post-Test
Interest Dimensions	M	SD	M	SD	p	Cohen’s d
Content Interest	18.97	2.94	19.69	3.25	0.2762	-
Learning methodology	18.23	4.06	20.69	2.98	0.0025 *	0.69
Active participation	16.59	3.37	18.28	3.96	0.0451 *	0.46
Course relevance	17.69	2.97	18.21	3.63	0.5024	-
General attitude	17	3.89	19.33	3.99	0.0127 *	0.59

M Mean, SD standard deviation. * p < 0.05.

. The results of the t-test analysis show that the interest in a new learning methodology marked a significant difference (p = 0.0025). It was observed that the mean score for the learning methodology among students was 18.23 (SD = 4.06) at the beginning of the study and increased to 20.69 (SD = 2.98) by the conclusion of the study. This finding indicates a significant increase in interest in the learning methodology. At the same time, the active participation in class (p = 0.0451) and general attitude towards physics education (p = 0.0127) showed a significant increase at the end of the study. The mean score for active participation was 16.59 (SD = 3.37) at the beginning of the study and 18.28 (SD = 3.96) by the end of the study. Meanwhile, the mean score for general attitude started at 17 (SD = 3.89) and increased to 19.33 (SD = 3.99) at the end of the study. Although there was an increase in content interest in physics and course relevance in the class, this increase was not statistically significant (p = 0.2762, p = 0.5024). Cohen’s d coefficients examined the significant differences in learning methodology and general attitude, which had a medium effect size (0.5 < |d| > 0.8). At the same time, active participation had a small effect size (0.2 < |d| > 0.5). Content interest and course relevance did not show a significant difference; therefore, the effect size was not calculated.

Figure 6 shows the kit printed and placed in a box given to the students to conduct the experiments (Figure 6a) and also shows part of Didactic Sequence 3 (Figure 6b), where students performed experiments that demonstrated the concept of friction by changing the rear tires of the electric cart to all-terrain tires on an irregular surface and comparing the results of speed and displacement that the electric cart had when rolling on a regular surface with standard tires; it also shows part of the didactic sequence 5 (Figure 6c), where students tested Newton’s laws. The figure shows the use of a smartphone with the Phyphox^® mobile application to measure the acceleration of a moving object. The average assembly time decreases from 30 to 15 min as the student acquires the practice.

4. Discussion

We presented a quasi-experimental study, which was the most robust and ethical way to evaluate an intervention in a real classroom setting. This approach did not alter the natural structure of the student groups or disrupt the normal course of the subject. It also reflected authentic classroom conditions, such as the schedule, teachers, group dynamics, and curricular pressures. This approach yielded results of greater practical relevance, allowing us to make recommendations that could be adopted in other educational settings. It also avoided any procedures that could generate inequity or confusion among students, such as randomly selecting some students to receive the intervention and others not, within the same class (Samsudin & Sulaiman, 2022; Zurita-Cruz et al., 2018). Unlike other research that conducted extracurricular interventions (Addido et al., 2023; Badeleh, 2021; D’Amico et al., 2020), this intervention was in curricular classes within the class schedule established for the subject, which was taken into account for the official evaluation of the students; in addition, to avoid internal conflicts between students in the same group that influenced the work of the other members, as mentioned by D’Amico et al. (2020), the head teacher supervised the teams punctually and informed the students about the rules of respect inside the classroom.

As the first specific contribution, we state that our low-cost STEM tool focused on motivation covers 12 physics concepts: motion, distance, displacement, velocity, speed, URM (uniform rectilinear motion), friction, acceleration, inclined plane, and Newton’s first, second, and third laws, which are more than those reported in previous studies for instance, they only covered the concepts of velocity and acceleration (D’Amico et al., 2020), electricity and magnetism (Badeleh, 2021), and Newton’s third law (Addido et al., 2023). In addition, the concept of electrical circuits was also covered indirectly by interconnecting the electronic parts to provide movement to the electric cart. All these concepts were covered throughout five two-hour sessions, resulting in a total of 10 h per group.

We present as a second specific contribution the materials used in the novel 3D parts kit. The kit was designed to allow the same pieces to be reused in all the experiments. With 27 parts, students can observe at least 12 different physics concepts, which reduces the cost of materials. The 3D parts kit is biodegradable and does not require the use of any adhesives to join the pieces, as they are easily assembled. Over the past two years, this kit has been used for several dozen pilot tests. During this intervention, 78 students used the kit for 20 h, and no parts were damaged; therefore, the cost of the kit remained unchanged. The many hours of use suggest that the same kit can function for 5 to 10 years, benefiting several generations of students and schools with limited budgets. Any damaged or lost part can be reprinted using a 3D printer, making our proposal more affordable. The low-cost materials proposed by Souza and Duarte (2015), Manikutty et al. (2019), Simeon et al. (2020), and Ngugi et al. (2023) were not intended to be reused for all the proposed experiments; so, the schools had to invest in new materials for each practice, which in some cases made it impossible to continue the experiments.

The third specific contribution of this work is the provision of functionality for rural areas in developing countries. Our low-cost STEM tool, focused on motivation, did not require the use of high-capacity laptops or high-speed internet connections on-site, as students can access all the didactic material and scientific resources through their cell phones using a Bluetooth connection to share files from a local laptop computer. The low-cost STEM tool does not require a processor, as it can be used with any mobile phone to measure physical quantities. In addition, the proposed STEM tool does not require students to have prior technical knowledge of electronics, programming, or robotics. Its manufacturing cost is around USD 35, almost 97% less than the LEGO Mindstorms EV3^® kit, the world’s most widely used 3D construction kit for learning physics, used by Addido et al. (2023) and D’Amico et al. (2020), which costs around USD 1150.

Rural area teachers considered the low-cost STEM tool to be a fundamental instrument for creating more creative and motivating learning environments that generate interest in physics. They mentioned that the physics topics covered with the STEM tool captured the class’s attention for extended periods and made the teacher’s work more rewarding.

Some observations made during testing of the low-cost tool were that students learned leadership skills, social participation, and teamwork, which was corroborated by the active participation measure. This generates more potential among the students and leads to a more significant generation of ideas and creativity.

Although there was no significant difference in learning between the control and experimental groups, a notable increase in interest was observed in the experimental group compared to the control group. Shin et al. (2019) emphasize that curiosity and interest are powerful driving forces for learning, positively impacting students’ motivation, creativity, and overall well-being. Although students may not always be interested in the school curriculum, interest significantly influences students’ motivation and subsequent learning outcomes (P. Li, 2018). Therefore, fostering interest and motivation in educational settings is crucial to improving learning experiences and outcomes.

Implications, Limitations, and Recommendations

The intervention was conducted in curricular classes within the established timetable for the subject, with the evaluation taken into account in the students’ official grades. During the intervention, some inconveniences were observed, including absenteeism and punctuality issues among some students, as well as changes in group assignments. Some teams were late in assembling the prototypes, and occasionally, school activities interrupted the intervention or distracted the experimental group, requiring adjustments to class schedules on some occasions. Therefore, we consider that further research in more controlled environments is necessary to prevent these unforeseen events, as well as to conduct a longitudinal study with longer intervention times to evaluate the flexibility and retention of knowledge by students.

Additionally, some students experienced delays in the assembly process and required the support of their classmates. Hence, a pending task for future interventions is to analyze and improve the didactic materials, specifically in the assembly of the experiments. Although the results of the curricular intervention showed a significant increase in interest and collaborative work, they did not show a significant increase in learning in the control group, suggesting the need to improve the instructions for assembly and handling of the tool, as well as the activities necessary for the development of the established competencies.

5. Conclusions

The results confirmed the findings of previous studies indicating that STEM education with the integration of hands-on experiences, 3D construction kits, and multidisciplinary approaches can effectively boost interest and participation among high school students, especially in rural areas, reducing the technology gap (Y. Li et al., 2021; Idris et al., 2023; Gugole et al., 2023; Maqruf & Dasari, 2024). Furthermore, this work represents a significant contribution to the existing body of knowledge in STEM science education in rural areas because a dozen physics concepts could be taught with a single tool, in addition to presenting a novel, low-cost, affordable, biodegradable, and durable kit with 3D parts; above all our proposal focused on rural areas where teachers and students do not require prior knowledge of robotics, electronics, and programming and do not need high-cost technological infrastructure such as specialized computer equipment and fast internet connections.

This study focuses on the application of a new low-cost STEM tool that emphasizes motivation and its impact on the learning and interest skills of rural students who have not received the same attention as those in other approaches applied to urban students. Another important reason for conducting the study was that play-based learning and STEM careers have received limited attention, and high school students need more knowledge about STEM careers. The results showed a surprisingly significant increase in interest in physics, which significantly influenced the dimensions of learning methodology, active participation, and general attitude towards the class, thereby favoring learning environments that improve the academy. Thanks to the low cost of the 3D construction kit and its affordability, a series of spare parts could be printed that, at the time of damage or loss of a part, could be replaced without affecting school activities. Using mobile phones and mobile applications as a fundamental part of the tool kept the interest of students and teachers, rather than being a distraction from learning. The learning experience was universal, as students and teachers did not require prior knowledge of robotics, programming, or electricity. The learning methodology of the proposed tool encouraged logical–mathematical, interpersonal, and kinesthetic intelligence (Gardner & Hatch, 1989); the latter caused students and teachers to remember their childhood play moments, forgetting that they were in a physics class. Didactic materials were designed for visual and audiovisual learning, and the ease of assembling the kit, combined with the simple language of the didactic materials, facilitated a straightforward learning process. The interest generated by this low-cost STEM tool facilitated the teacher’s work and significantly improved the participation and attitudes toward science classes. The social experience and learning obtained in this intervention will allow students to prepare for future job opportunities since knowledge of science and technology and collaborative work are necessary in today’s global market, may reduce the technological gap between developed countries and rural areas in developing countries, and help to meet the UN-mandated Sustainable Development Goal 4: Quality Education (United Nations, 2023).