Influence on Students’ Learning in a Problem- and Project-Based Approach to Implement STEM Projects in Engineering Curriculum

Abstract

In recent decades, a transformation in university-level engineering programs has been proposed, shifting towards active, student-centered teaching approaches such as problem- and project-based learning (P²BL). At the same time, interdisciplinary STEM education has taken on a central role in engineering instruction by fostering connections between different disciplines and enhancing the use of scientific skills. In this article, we present the design, implementation, and evaluation of a new curriculum that integrates the P²BL approach within an integrated STEM framework in the Process and Product Innovation Engineering degree at the Dual Engineering School—IMH Campus. We focus on one of the key teaching materials we have developed to structure an approach based on problem- and project-based learning: the long-term interdisciplinary STEM (iSTEM) project. This initiative has been implemented over the past three years in the first semester of the first year of the engineering degree program. We describe its design and execution, followed by an analysis of the evaluation methodology and results in relation to the defined learning objectives. Additionally, we present the evaluation tools used and the findings obtained, assessing both the iSTEM project’s ability to engage students in learning the subject and its impact on their knowledge development. The findings obtained from the various assessment instruments indicate that the implementation of the P²BL teaching methodology enables students to apply core engineering skills in problem-solving, while simultaneously fostering a deep understanding of the concepts, laws, and models from the different disciplines involved. Notably, the results also suggest that the development and application of engineering skills is a gradual process that requires time. Therefore, it is essential for students to continue engaging with the P²BL approach throughout their undergraduate studies.

1. Introduction

In recent decades, a change from a lecture-based teaching approach in undergraduate engineering courses to student-centered, problem- and project-based active teaching (P²BL) approaches has been proposed (Hmelo-Silver, 2004). This strategy is our choice for an active mind-on teaching approach that focuses on critical thinking, reflection, and deep understanding (Dolmans et al., 1994). This teaching model aligns with the learning theory we adhere to, socio-constructivism (Leach & Scott, 2003), in which problems and projects are, as much as possible, placed in real engineering contexts, and students are repeatedly encouraged to build new knowledge upon prior knowledge while interacting in small groups with other students.

On the other hand, interdisciplinary STEM education is taking center stage in engineering education (Roehrig et al., 2012). At the same time, the development of STEM curricula has become increasingly relevant in both pre-university and university education (English & King, 2019). Numerous researchers have highlighted that connecting interdisciplinary bodies of knowledge enables students to synthesize information across multiple disciplines, fostering integrative competencies in engineering education that go beyond a single field of study. The interest of the P²BL approach in a STEM scientific–technical context lies in finding ways to develop students’ content knowledge and plan appropriate learning activities and instructional strategies. However, there is little research into the impact of this teaching approach on undergraduate engineering students’ attitudinal understanding and use of scientific–technical practices, as well as their perceptions of learning using P²BL in a STEM context.

This study will first examine the design and implementation of learning activities such as “Predict and Argue” and “Design and Do” within the context of the Dual Engineering School at IMH Campus. These activities aim to integrate STEM content into the P²BL approach, fostering students’ core competencies through problem-solving processes. Secondly, we will evaluate the implementation carried out in the first year of engineering over three academic years, presenting the results on students’ conceptual, procedural, and attitudinal learning. A mixed-methods approach, combining qualitative and quantitative analysis, has been used to analyze the empirical data collected.

2. The P²BL Model of the Dual Engineering School at IMH Campus

IMH Campus is made up of companies, associations, and public institutions from the Basque Country. It is an integral part of the Advanced and Digital Manufacturing Cluster (AFM) and a key player in the Basque Network of Science and Technology. The campus is composed of two main components: the Vocational Training Integrated Center of the Basque Government and the Elgoibar Dual Engineering School, which is affiliated with the University of the Basque Country (UPV/EHU). The campus is a specialized educational institution in Advanced and Digital Manufacturing and is actively engaged in lifelong learning and applied research in collaboration with industry. It is also a pioneer in implementing dual education in higher education in Spain, with over 25 years of experience in this model.

Graduates of the Process and Product Innovation Engineering bachelor’s degree at Elgoibar Dual Engineering School—IMH Campus are highly regarded and enjoy excellent employability in the industry, largely due to the dual nature of their education. This educational model integrates academic learning with hands-on experience in industrial settings across different sectors. The curriculum is designed so that 75% of the credits are completed in the academic environment, while the other 25% is dedicated to project development within a company. Unlike traditional curricula, where the number of credits assigned to laboratory or company practices is relatively low, the dual model emphasizes the integration of theoretical knowledge with professional experience. In addition, in-person teaching is structured to strengthen skills that complement practical learning, allowing students to develop project design abilities within a business context, while fostering connections between the company and the school.

However, in recent years, some faculty members and the management of the center have identified certain areas for improvement in academic teaching. These include increased dropout rates, a higher percentage of failures in theoretical subjects, a lack of development of higher-order skills (such as metacognition and hypothetical thinking), and limited initiative or autonomy in problem-solving. To address these challenges, a working group was established during the 2022–2023 academic year. Its primary task was to investigate whether the perception of academic dissatisfaction was also shared by the managers and tutors of the partner companies involved in the degree’s curriculum. In the follow-up meetings regarding the development of competencies within the companies, the managers and tutors expressed that the students’ scientific knowledge and attitude were satisfactory. However, they emphasized the need to improve other competencies, such as teamwork, problem-solving skills, and the ability to acquire new knowledge, among others. Based on this feedback, the working group proceeded to update the degree curriculum and integrate an active learning approach into the credits delivered within the Elgoibar Dual Engineering School.

In relation to the curriculum update, the working group established the following general objectives (Process and Product Innovation Engineering degree; see https://www.ehu.eus/es/web/graduak/grado-ingenieria-innovacion-de-procesos-y-productos/verificacion-seguimiento-y-acreditacion, accessed on 2 April 2025). These objectives primarily focus on the following:

Conceptual and Procedural Competencies:

• To gain a deep and meaningful understanding of engineering design;
• To develop the ability to design and manufacture products using scientific and technical methods, enabling students to evaluate and make informed design decisions;
• To foster teamwork skills.

Attitudes:

4.

To increase students’ interest in engineering and enhance their satisfaction with the learning process;

5.

To raise awareness among students about the roles and responsibilities of engineers in society and help them recognize and address ethical issues.

Regarding the teaching approach to be implemented in the classes, the working group decided to adopt active learning techniques, which are widely supported by research in science and engineering education (Prince, 2004; Dancy & Henderson, 2007). Consequently, a problem-based and project-based learning (P²BL) approach was chosen. Problem-based learning is a pedagogical strategy that presents complex tasks through questions or problems, encouraging students to design solutions, tackle challenges, make decisions, and conduct independent research. Moreover, by working on real-world products, it seeks to enhance student motivation (Dutch, 2001; Thomas, 2009). On the other hand, project-based learning focuses on guiding students through the processes of inquiry, knowledge construction, and problem-solving, culminating in the creation of a final product (Bell, 2010). The decision to shift the curriculum towards a problem- and project-based approach is grounded in evidence from educational research, which shows that both methods complement each other in shaping the skills of future engineers. The transition to this new curriculum framework is illustrated in Figure 1.

3. Implementing the P²BL Dual Curriculum Framework to Transform the Study Plan

The engineering degree curriculum is designed around the direct connection between theoretical studies, practical design, and problem-solving and project activities. The dual training in industry, combined with the academic curriculum, enables students to integrate key aspects of design and manufacturing. However, this integration presents a significant challenge in the first year of the program, particularly in teaching problem-solving and project-based learning.

The Elgoibar Dual Engineering School at IMH Campus has a long-established track record of incorporating projects into its curriculum. For decades, various initiatives have been implemented that were primarily focused on project-based problem-solving within company training (see https://www.imh.eus/en/engineering-school/dual-model-characteristics?set_language=en, accessed on 2 April 2025). However, our previous experience centered on outcome-driven projects and problems, whereas in this new phase, we aim to focus on the development of competencies and learning objectives. Projects and problems aimed at achieving specific results—such as improving a design or creating a prototype—are primarily designed to apply previously acquired knowledge and skills. In contrast, the projects and problems in the new curriculum are intended to foster the development of specific competencies and the acquisition of new knowledge throughout the process. Therefore, defining clear learning objectives is a critical first step in designing STEM projects and problems. When designing interdisciplinary STEM projects for the new curriculum, we face the challenge of accurately defining the competencies to be developed in each project.

Most students entering our engineering program come from a traditional educational system centered around knowledge transmission through “lectures” (a teacher-centered model) and have a limited understanding of engineering. When confronted with a different teaching model, conflicts can arise between students’ established habits and expectations, often leading to frustration (Little, 1997). This presents a challenge in designing projects and problems that incorporate scaffolding activities to help students navigate the complexities of a P²BL-based approach. One of the main challenges in designing and implementing the STEM projects in the new curriculum is equipping students with the necessary skills and helping them identify the knowledge they need to acquire to successfully complete the project. This is achieved by guiding students through an effective problem-solving/project approach and offering a mentoring program integrated into the academic schedule throughout the 14-week semester.

The new first year of the curriculum is organized into two 14-week semesters, each with its corresponding evaluation (see Figure 2). Each semester includes between one and three problems in each of the four to six disciplinary subjects, along with an interdisciplinary STEM project that spans the entire semester. Student groups consist of six members for the STEM project and three students for the problems and activities in the disciplinary classes. In the context of our problem- and project-based learning (P²BL) curriculum, the learning process is primarily stimulated through small-group work. This approach provides students with the opportunity to develop collaborative skills that are essential in professional settings, such as those required in engineering teams. Furthermore, by being trained as independent learners, students engaged in PBL methodologies are expected to identify their own knowledge gaps and actively seek out the necessary resources to address them collectively (De Graaff & Kolmos, 2003; Jaques, 2000).

Long-term interdisciplinary STEM projects (12 weeks) offer several advantages, such as reinforcing a comprehensive and deep understanding of the relevant disciplinary knowledge, motivating students to develop a more professional perspective of engineering, and helping them manage their time by focusing on a limited set of topics. Additionally, these projects foster collaboration among the professors involved.

The support for training students in problem-solving and projects serves as a guide for applying scientific–technical skills, generally following five steps. However, this is not a strict heuristic that requires all steps to be applied (Guisasola & Zuza, 2024):

(1)

First, a context for the phenomenon or model to be analyzed in the project must be established. This context or problem should be accessible to students, but not obvious, and it should not necessarily have a single solution.

(2)

After the presentation, students should be encouraged to express their initial ideas and hypotheses about the project through graphics, drawings, written arguments, etc. This marks the beginning of the knowledge acquisition process.

(3)

During the process, prioritizing evidence is essential, whether through planning, evaluating, or developing a design that may be closed, structured, guided, or open.

(4)

To make the project more realistic, it is beneficial to analyze real or hypothetical data, enabling students to represent, evaluate, and connect results. This allows them to confirm or reject their initial ideas using the analyzed data.

(5)

Finally, students should resolve the project based on their learning. These conclusions must be communicated as students reflect on what they have learned, how they did it, and how their knowledge has been applied.

In this article, we will focus on the interdisciplinary STEM (iSTEM) project, which has been implemented for three years in the first semester of the first year of the engineering degree program. We will begin by outlining its design and implementation, and then present the evaluation approach and results in relation to the defined learning objectives.

Design and Implementation of an Interdisciplinary STEM Project Focused on Learning in the New Curriculum

We aim to establish a strong connection between the semester project and the concepts and challenges covered in the classroom. The project is introduced in two 4 h sessions at the beginning of the first semester. Throughout the semester, the link between the project and the course content is explicitly emphasized. At the end of the semester, two additional 6 h sessions are held to address students’ questions about the project report. To support students in their work, a structured worksheet-style guide is provided (see Figure 3). Each worksheet (WS) includes tasks related to the project’s key questions or problems that students must solve. Worksheets are an effective tool for fostering active learning through problem-solving and project-based approaches (Sujarittham et al., 2016). They help students focus on essential concepts and provide multiple representations to enhance comprehension. Worksheets are highly versatile and can be adapted to meet specific learning objectives. Students worked in groups of six, with each group being required to submit a completed worksheet.

At the beginning of the first two sessions, the objectives and methodology for project-based problem-solving are introduced. Then, the problem statement is presented, and students work on Worksheet 1 (WS1).

For example, the project is introduced with the question: “How can we achieve the most competitive machining process for a given part?” A real-world scenario is provided, featuring a company that machines a part, identified as AFX29913 (IMH, Elgoibar, Spain), using three different machines: (i) Kondia-Seaska; (ii) Danobat TM-750; and (iii) Ibarmia ZVH-38 L1600.

Each machining process follows a different workflow to produce the same part, AFX29913. The machining process data for each machine, essential for developing the project, are provided. The company’s primary goal is to determine which machine is the most competitive based on the following criteria: (1) lower energy costs; (2) machine efficiency; and (3) process speed.

After reviewing the project details, WS1 prompts students to answer the following questions to gain a deeper understanding of the project’s objectives:

• Describe the machining process under analysis. What is the initial part, and what is the final part? What process is followed to obtain the final part?
• What variables are considered to evaluate the machining efficiency of the three machines? Explain the meaning of each variable.

In the second session, guided by the questions in WS2, students share their ideas on potential solutions for the project (see Figure 3). The focus is on planning the design and identifying the disciplinary content they need to learn, thereby initiating the knowledge acquisition process. Throughout the semester, students must track their learning across different subjects, both in class and through discipline-specific problem-solving activities. To support this process, WS3 serves as a guide, explicitly outlining the conceptual content from each discipline relevant to the project (phase II; see Figure 3).

In phase III (see Figure 3), students work with WS4, which helps them analyze data, evaluate results, confirm or reject initial hypotheses, and ultimately explain their approach to solving the project based on their learning and data-driven arguments. Additionally, WS4 guides students in preparing the project report, prompting them to reflect on and answer key questions such as the following:

Project Questions

• Define the project objectives.
• Outline the steps taken to solve it.
• What hypotheses were formulated for the resolution?

Definition of Process Variables

• Analyze the influence of each variable.

Evidence-Based Arguments for the Resolution Process

Project Summary with Recommendations and Conclusions

4. Evaluation of the Learning Impact Achieved During the Curriculum Change: Evaluation of the iSTEM Project 1.1

This section presents and analyzes the evaluation and subsequent refinement of the first version of the iSTEM 1.1 project, which was implemented in the 2022–2023 academic year, and whose second version was implemented in the 2023–2024 and 2024–2025 academic years. First, the preliminary evaluation is presented, with empirical evidence that guided the improvement of the initial version. Second, the results of the implementation of the refined iSTEM 1.1 project are discussed in relation to the learning achieved, the acquisition of scientific–technical skills, and the attitude toward project-based learning.

In our research, we conducted a retrospective analysis of the implementation of the iSTEM 1.1 project, using a multiple and convergent approach to highlight the various aspects of its evaluation (Nieveen, 2009; Guisasola et al., 2023). To achieve this, we proposed an analysis of results based on three dimensions (see

Table 1. Assessment tools for the implementation of the iSTEM 1.1 project.

Instruments for detecting the viability of the design	Instruments for measuring the learning achieved through the implementation of the project	Redesign of the SEA
Teacher’s diary Report of the observations made by the teaching staff during the implementation in the tutorials of the initial and final phases of the project	- Questionnaire on the understanding of concepts and laws included in the project (pre- and post-test) - Reports on the worksheets and final report - Attitude questionnaire	- Redefinition of writing topics, analogies, approach, etc. - Redesign of worksheets - Redesign of figures, graphs, etc. - Redesign of the project’s prerequisites and its activities

):

(a)

Evaluation of the design’s feasibility, which includes the following:

(a.1)

Problems related to the clarity of activities that students must perform;

(a.2)

Problems related to the time required to complete the sequence;

(a.3)

Unexpected issues inherent in writing a new sequence with innovative content.

(b)

Quantitative and qualitative analysis of student learning, which includes the following:

(b.1)

Conceptual understanding;

(b.2)

Acquisition of engineering procedures.

(c)

Evaluation of students’ attitude and engagement with the project.

For the analysis of the design’s viability (first column of Table 1), we employed a qualitative research methodology with tools such as the teacher’s diary and the teachers’ observation reports (Carr & Kemmis, 1986). These tools are used as data sources to identify students’ difficulties in understanding the objectives of the worksheets, as well as to deepen the teachers’ understanding of the teaching methodology during the development of the projects. Our goal in this dimension is to ensure that the project’s educational material is clear to the students and easy for the teachers to handle.

The assessment of the learning process relies on two main instruments (see the second column of Table 1): (a) a pre- and post-test questionnaire, administered individually to the students in an exam-like setting, aimed at measuring conceptual learning in each of the disciplines involved in the project; (b) a final report prepared by each student group, which presents, alongside their conceptual knowledge, the scientific and technical skills they used during the development and resolution of the project. For the analysis of the pre- and post-test questionnaires, we use descriptive statistics, such as the mean and standard deviation, for each variable studied. The students’ final report is assessed using a rubric that considers the general engineering skills students should demonstrate to justify the project development and its outcomes.

To evaluate students’ attitudes toward the project’s learning process and their interest, a questionnaire with 20 statements on a Likert scale is used.

For the sake of brevity and to clearly illustrate how specific aspects of the evaluation influence the redesign, we first focus on the qualitative assessment and its impact on the reformulation of iSTEM 1.1, followed by the quantitative analysis of students’ learning and attitudes. Both sections demonstrate how decisions were made to redesign elements of iSTEM 1.1.

5. Results of the First Version and Refinement of the iSTEM 1.1 Project

In the first implementation of the iSTEM project, during the first semester of the 2022–2023 academic year, the analysis of the information recorded by the teacher in the teacher’s diary and the responses provided by students in the worksheets during the first implementation of the project showed evidence that students did not understand some of the objectives of the worksheet activities. For example, in Worksheet 3 (WS3), which student groups were supposed to fill out during phase 2, the students’ responses did not distinguish between identifying the concept and determining where in the project they should apply it. For instance, one of the teachers wrote in their notebook how they presented WS3 in their classes:

“Throughout the course, you will identify the necessary knowledge you mentioned in Worksheets 1 and 2. Now, you need to make these explicit in WS3. Once the necessary concept to develop the proposed challenge is defined, you must specify how it will be applied within the project.”

However, the same teacher explained that:

“Most students give the same response to questions 3 and 4; there is a misunderstanding of the questions, and they confuse the concept and its learning with the application of the concept in the project. They do not explain how the concept will be used and what problems it may solve.”

These difficulties were shared by all teachers and persisted in the interpretation of WT3. This led to the reformulation of WS3, changing questions 3 and 4 in Worksheet 3 (see

Table 2. Rewriting of WS3.

WS3: “Once the necessary concepts to study in order to solve the project have been identified (Worksheets 1 and 2), in this worksheet, throughout the course, you must explicitly define each concept, as well as where and how you will apply it in the development of the project”.
Initial WS3	Revised WS3
Concept Time of teaching in the course At what point in the project statement is it used? What is it applied for in the project?	Concept Time of teaching in the course How is the concept applied in the project and what problem does it solve?

). The new questions focus on improving the wording to help enhance students’ comprehension and provide better opportunities for reasoning.

The teachers’ reports also highlighted discrepancies between the learning objectives defined for each subject and some of the questions in the pre- and post-test questionnaire used to assess learning. As an example, here we present a case from the Physics I course.

The responses to certain questions in the questionnaire revealed that students did not fully understand the objectives set. A particular case was Q1, whose learning objective (LO) was to assess the mechanical work done by constant or variable forces on a system using different strategies (analytical and graphical). Students did not interpret the question correctly and failed to explain the procedure used to calculate the work. In light of this difficulty, it was decided to reformulate Q1 and adjust the learning objectives to ensure better alignment between both (see

Table 3. Refinement of the learning objectives and Q1 in the Physics I course.

Learning Objectives and their Relationship with the Pre- and Post-Test Questionnaire Questions Initial iSTEM 1.1 Project
Learning Objectives	Q1
LO2—Identifies the equation that represents the variable force in each graph and the variable position as a function of time. LO3—Plots the value of the force corresponding to each position in each section of the graph. LO4—Calculates the value of the work for each section of the graph, as well as the total work both analytically and through areas. LO6—Interprets the obtained results with scientific reasoning.	Q1. A 2.0 kg scale model car, controlled by remote, is pushed to a force Fx parallel to the x-axis as it moves along a straight track. The x-component of the force varies with the car’s x-coordinate, as depicted in the figure. Calculate the work done by the force Fx as the car moves from: (a) x = 0 m a x = 3.0 m (b) x = 3.0 m a x = 4.0 m (c) x = 4.0 m a x = 7.0 m (d) x = 0 m a x = 7.0 m (e) x = 7.0 m a x = 2.0 m

and

Table 4. Relationship between the teaching objectives and the questionnaire questions in the Applied Physics I course.

Learning Objectives and their Relationship with the Pre- and Post-Test Questionnaire Questions Initial iSTEM 1.1 Project
Learning Objectives	Q1
LO2—Identifies the independent variables in the mechanical work equation. LO3·LO4—Calculates the value of the work for each section of the graph with variable and constant force by applying the appropriate analytical equations. LO5—Calculates the value of the work for each section of the graph represented graphically from the area defined by the force and position variables. LO6—Correctly calculates the total work value based on the work definition and provides sound reasoning for the results.	Q1. A 2.0 kg scale model car, controlled by remote, is pushed to a force Fx parallel to the x-axis as it moves along a straight track. The x-component of the force varies with the car’s x-coordinate, as depicted in the figure. Calculate the work done by the force Fx as the car moves from: (a) x = 0 m to x = 2.0 m. Calculate analytically the work done by the force and justify your answer. (b) x = 2.0 m to x = 4.0 m. Calculate graphically the work done by the force and justify your answer. (c) x = 4.0 m to x = 7.0 m. Calculate graphically the work done by the force and justify your answer. (d) x = 0 m to x = 7.0 m. Calculate both analytically and graphically the work done by the force and justify your answer. (e) x = 7.0 m to x = 2.0 m. Calculate both analytically and graphically the work done by the force and justify your answer.

).

In summary, based on the empirical data obtained from the journals and observation reports of the teachers during the first implementation of the iSTEM 1.1 design, the changes made include not only the reformulation of objectives and the questionnaire but also the revision of some activities in the worksheets to adapt them so that students could better understand their purpose and stimulate their interest in learning. The revised iSTEM 1.1 project was implemented with all first-semester students in the 2023–2024 and 2024–2025 academic years.

5.1. Results Regarding Students’ Learning from the Implementation of the Revised Project During the 2023–2024 and 2024–2025 Courses

The conceptual learning of the students who participated in the project has been assessed through the results of the pre- and post-test questionnaire in each of the integrated disciplines. Data from all disciplines were collected during the 2023–2024 and 2024–2025 academic years, and statistical analysis has allowed for the determination of the impact of the iSTEM 1.1 project on student learning. Additionally, the learning and use of scientific and technical skills were evaluated through the analysis of the final report created by the student groups in the WS4 Worksheet. On the other hand, the students’ interest and attitude towards the project, its objectives, and the working methods were measured using a Likert scale with a 1–10 interval. Below, we present some of the results in each of the described sections.

5.2. Results Regarding Students’ Conceptual Understanding of the Concepts and Theories Included in the Project

Given the need for brevity in this article, we will focus on the results obtained in the Physics I course, as they are representative of the outcomes in the other subjects.

Table 5. Relationship between the aim of the question and the learning objective in the Physics I topic.

Questions	Learning Objetives
Q1	Q1. See Table 4 Ask students to analyze and calculate the work done on a car model using constant or variable forces, applying both analytical (LO3 and LO4) and graphical (LO5) strategies. They must identify the variables that influence the process (LO2) and calculate the total work by summing the work characteristics of the different parts of the trajectory (LO6).
Q2	Q2. An object on a horizontal surface with friction moves at a constant speed, pushed by a person with a force of 4 N over a distance of 3 m. Is the total work done on the object positive, negative, or zero? Explain your answer. Ask students to analyze the work done by all forces on the object and justify their response (LO3 and LO4).
Q3	Q3. A force of 100 N is applied to system A, performing 50 J of work over a time interval of 25 s. A force of 50 N is applied to system B, performing 100 J of work over a period of 25 s. Which system has greater mechanical power? Justify your answer. Test the students’ ability to identify the variables that define the mechanical power of a system and establish the relationships between them (LO7).
Q4	Q4. In several systems of units, conversion between different magnitudes is needed. Perform the following conversions: 1 dina → N 6 cm → hm 1 kW → kgm/s 8 kg → utm 4 mm → dam Test the students’ ability to recognize and use appropriate units for the phenomenon being analyzed (LO1)

outlines the connection between the four questions of the Physics I questionnaire and the defined learning objectives.

The pre- and post-test questionnaires were administered to students under exam conditions, and the results were included as part of the final grade for the subject unit. The scores from the pre-test and post-test were compared for all students in the 2023–2024 (N = 54) and 2024–2025 (N = 42) cohorts. The questions are analyzed according to a 1 to 4 scale on a rubric for achieving the learning objectives and are presented in

Table 6. Statistics of the scores obtained for each question and the level of significance (calculated using the Wilcoxon Signed-Rank test and Cohen’s d, which is a measure of the effect size) of the comparisons between the pre-test and post-test in the 2023–2024 and 2024–2025 cohorts.

2023–2024							2024–2025
	Pre-Test		Post-Test		p-Value	Effect Size (r)	Pre-Test		Post-Test		p-Value	Effect Size (r)
	M	SD	M	SD			M	SD	M	SD
Q1	1.14	0.69	2.62	1.04	p < 0.05	0.64	1.32	0.85	3.19	1.02	p < 0.05	0.71
Q1a	1.06	0.24	2.47	1.36	p < 0.05	0.58	1.84	1.21	3.43	0.96	p < 0.05	0.59
Q1b–c	1.06	0.24	2.24	1.19	p < 0.05	0.57	1.00	0.00	3.11	0.97	p < 0.05	0.84
Q1d	1.06	0.24	2.00	0.87	p < 0.05	0.59	1.03	0.16	3.43	0.90	p < 0.05	0.88
Q1e	1.38	0.60	1.76	0.69	p < 0.05	0.30	1.00	0.00	3.43	0.90	p < 0.05	0.89
Q2	1.21	0.47	2.03	0.92	p < 0.05	0.49	1.51	1.04	3.43	0.96	p < 0.05	0.69
Q3	2.59	1.44	1.91	1.07	p = 0.056	0.26	1.00	0.00	3.16	1.28	p < 0.05	0.77
Q4	1.12	0.20	2.47	0.75	p < 0.05	0.78	2.57	1.48	3.59	0.80	p < 0.05	0.43

, showing the mean and standard deviation of the scores obtained for each question. Some of the questions have been discussed in previous papers on student difficulties and improvements using a new engineering curriculum based on problem- and project-based learning (Gutiérrez-Berraondo et al., 2024). We summarize the relationship between the pre- and post-test questions in Table 6.

In all the questions and their learning objectives (LO1–LO7), the mean scores of the post-test are significantly higher than those of the pre-test, indicating progress in the understanding of the assessed concepts. The standard deviation (SD) in the pre-test is generally greater, suggesting a higher level of dispersion in the initial knowledge of the students. In the post-test, the SD is lower in most cases, reflecting greater homogeneity in learning after the intervention. The Wilcoxon Signed-Rank test p-values are below 0.05, confirming that the differences between the pre-test and post-test are significant and not due to chance. This indicates that the intervention has had a considerable impact on learning, with the most pronounced effects in the results of questions Q1b, Q1c, Q1d, Q3, Q1e, and Q2. This suggests that students showed a significant improvement after the intervention in calculating work from algebraic representations and force–position graphs (LO3, LO5, and LO7). The objective LO7 (question Q3) has improved notably, with the majority of students successfully identifying the variables that measure power (LO7). This suggests that the revised iSTEM 1.1 project was effective in developing students’ conceptual knowledge. However, the objective LO1 (use and conversion of units depending on the systems used), related to Q4, shows a smaller effect size difference compared to the other objectives. Attention must be given to this aspect in the teaching of the project.

When comparing the results of the two academic years, it can be observed that the trend between both iSTEM 1.1 cohorts shows greater improvement in the second intervention, with higher statistical significance and larger effects. This could indicate that the intervention is better understood by the faculty in terms of its implementation or that active teaching strategies are better mastered. Another factor that could influence this is that it is the third year of implementation within the new degree curriculum, and students have integrated the new way of working into their learning process. This last hypothesis is also supported by the results of the evaluation of the attitude towards learning, as shown in Section 5.4.

5.3. Results on Students’ Application of Engineering Skills in the Project

The results of the use of engineering skills are obtained using a rubric with a score ranging from 1 (no use) to 4 (satisfactory use), depending on the level of application of the skills (see

Table 7. Results of the analysis of the reports of the groups of students who carried out the project.

Scientific–Technical Skills	Number of Groups by Level of Achievement
	2023–2024 (9 Groups)				2024–2025 (7 Groups)
	Level				Level
	L4	L3	L2	L1	L4	L3	L2	L1
S1. Describes the project and explicitly indicates its characteristics	2	4	3	-	2	4	1	-
S2. Properly states the initial development of the project and describes the hypotheses	1	-	-	8			6	1
S3. Correctly identifies the variables and how to measure them	5	4	-	-	3	3	1	-
S4. Lists the steps to carry out the project and makes them adequately explicit	3	3	3	-	-	4	2	1
S5. Explains the results obtained in relation to the hypotheses and takes into account their specific conditions and limitations	-	-	9	-	-	4	2	1
S6. Adequately uses the mathematical and computational representations related to the project	3	4	2	-	4	2	1	-
S7. The solution to the project presents explanations based on evidence, technological feasibility, cost, safety, and compliance with legal requirements	1	1	6	1	3	3	-	1
S8. Adequately explains the positive and negative aspects of the project solution	.	1	2	6	-	6	1	-

). The rubric is applied in the analysis of the final project report (WS4), where the groups of students report, argue, and calculate the results related to the development of the project. The results are shown in Table 7 and Figure 4 and correspond to academic years 2023–2024 (nine groups of six students) and 2024–2025 (seven groups of six students).

In the reports, most of the groups use skills 1, 3, 4, and 6 with scores of 3 or more to explain how they construct the steps to reach a solution, argue based on evidence, and consequently construct explanations. At skill level 7, there is a significant increase in performance from the 2023–2024 to the 2024–2025 academic year. In 2024–2025, all groups except one (six out of seven) achieved scores in levels L3 and L4, whereas in 2023–2024, only two groups reached these levels. However, an exception is observed in the ability to adequately state and describe hypotheses, which presents a lower performance compared to the rest (skill 2). This result is in agreement with the lower use of the analysis of results in relation to the hypotheses issued (skill 5). This situation could be related to the lack of previous training in scientific methodology by the students, suggesting that they are unaware of the concept of hypotheses and, therefore, have not developed this skill adequately. It is worth noting the improvement from the 23–24 course to the 24–25 course in the explanations of the solution obtained and its positive and negative aspects (skill 8). In this aspect, the professors analyzed the results of the 23–24 course and focused their explanations of the results of the project on explaining the need for good communication on both the projects and results in engineering.

In general, Table 7 shows an improvement in the use of the skills assessed from one academic year to the next, with most of them reaching levels above L2. However, the data for skills 2 and 5 reflect low utilization of the skills related to hypothesizing and using them for verification. These results are in agreement with other studies on the use of hypotheses in problem-solving (Ferguson-Hessler & De Jong, 1990). The results of S2 and S5 show a persistent difficulty in the acquisition of these skills by students. It is important to further analyze the causes of these difficulties for the design of future materials.

5.4. Students’ Results Regarding Their Attitude Toward Project-Based Teaching

To evaluate the opinions and attitudes of the students about the contents worked on during the project, the way of working during the development of the project, and their satisfaction, a questionnaire was prepared with statements that are scored by the students between 0 and 10 according to their agreement (totally agree: 10 points) or disagreement (totally disagree: 0 points).

Table 8. Medians and standard deviations of students’ scores and their attitudes towards some of the statements from the protocol in the 2024–2024 and 2024–2025 courses.

	2023–2024 Year Median (Standard Deviation)	2024–2025 Year Median (Standard Deviation)
THE CONTENTS THAT HAVE BEEN WORKED ON
1. The amount of contents has been adequate.	7.0 (1.21)	7.3 (1.16)
2. The objectives pursued were clear (you knew what they were going to be used for).	7.0 (0.89)	6.4 (1.38)
3. When new concepts were introduced, they were related to the ones that had been introduced before.	7.0 (1.23)	7.0 (1.37)
THE WAY OF WORKING DURING THE PROJECT
4. The teaching method was adequate to the contents covered.	7.0 (1.08)	7.0 (1.12)
5. The activities proposed in class were adequate so that they could be solved by the students.	7.0 (1.32)	6.9 (1.51)
6. There were common discussions that helped to clarify the solutions to the activities.	7.0 (1.54)	6.5 (1.67)
THE SATISFACTION WITH WHICH THE PROJECT HAS BEEN WORKED ON
7. The classes of the project have managed to attract my attention.	6.0 (1.87)	6.6 (1.92)
8. There is support and willingness on the part of the teacher of the project and subject to help students overcome their difficulties.	7.0 (2.17)	7.5 (1.95)
9. In the class there has been a climate of cooperation among the students.	8.0 (3.26)	7.4 (3.17)

presents some results taking into account the median and standard deviation statistics that are appropriate for this type of analysis with a Likert scale (Cohen et al., 2007).

It was observed that the attitude of the students during the development of iSTEM 1.1 was positive, with scores between 6 and 8. The standard deviations in this context indicate a relatively low dispersion in comparison with the total range of the scale. The general trend from one academic year to the next has been to maintain these scores, except in items 2, 6, and 9, where a slight decrease was observed, but the dispersion above the median also increased as the standard deviation increased. In particular, item 2 reflects that the students’ perception of the understanding of the project objectives did not improve with respect to the previous year. Although the difference is not significant, for the next course, it will be important to consider this aspect when presenting the project to the students. In item 9 on the climate of cooperation among students, although the evaluation is very positive, there is a higher dispersion than in the other items. In the explanations given by the students regarding their evaluations, in this item, it is observed that a significant group of students think that they have worked more than their group mates and that others have taken advantage of their work. This feeling in some students is significant and should be introduced in subsequent courses, fostering group dynamics that allow equity and equality in the contribution to the work of each student in the group.

6. Conclusions

We have outlined the teaching approach of the Dual Engineering curriculum at IMH Campus, which is based on a problem- and project-based learning (P²BL) model that incorporates active learning strategies. The decision to structure the curriculum around problem- and project-based methodologies is supported by educational research, which demonstrates that both approaches complement each other in developing the competencies of future engineers. To illustrate this approach, we chose to describe one of the key teaching tools that bring it to life: long-term interdisciplinary STEM (iSTEM) projects. These projects offer several advantages, such as fostering a deeper and more comprehensive understanding of disciplinary knowledge, encouraging students to develop a more professional perspective on engineering, and helping them manage their time by focusing on a well-defined set of topics. Specifically, we detailed the design, implementation, and development of the iSTEM 1.1 project, which was undertaken by first-year students during their first semester.

The iSTEM project is designed to create teaching materials that establish strong connections between the project and the key concepts and challenges addressed in various disciplines throughout the semester. During its implementation, it became evident that engaging with the iSTEM project significantly benefited students, as reflected in their improved post-test scores. However, teachers also reported that some students faced difficulties in understanding and interpreting certain worksheet activities.

An important aspect of evaluating new approaches is the redesign of materials, which allows us to adjust the learning objectives we aim to teach. The analysis of the results from the first implementation of iSTEM led to a review that introduced substantial changes to the worksheets, both in terms of wording and teacher annotations related to their presentation to students. This resulted in the revised iSTEM project. Student achievement in conceptual understanding and the application of engineering procedures was higher with the revised project compared to its first-year implementation. Subsequently, the results with the revised iSTEM remained consistent in the second and third years of application.

An evaluation of the revised iSTEM project implementation revealed that most students successfully achieved the curriculum’s learning objectives, both in conceptual understanding and in the application of scientific skills. Furthermore, no negative effects were observed when comparing student learning outcomes to those of the previous lecture-based curriculum. Additionally, students’ attitudes toward the new iSTEM project methodology showed a marked improvement, with increased engagement and interest. This contrasts with the dissatisfaction expressed under the traditional curriculum, concerns that were a key factor in the shift toward the P²BL model.

It should be recalled that the implementation of the iSTEM project was carried out in small engineering groups (between 40 and 50 students) on a privately managed campus. We do not have data on how it would work in larger groups in other universities. However, based on our teaching experience, we believe that our design may be useful for those teachers who are trained in active teaching strategies such as problem-solving and projects. We believe that our materials will help these teachers implement the active teaching approach that they recognize as more effective than the traditional one. On the contrary, we believe that our iSTEM design will not work in teaching contexts where teachers are primarily limited to transmitting knowledge and conducting an evaluation at the end of the semester. We feel that these teachers are not accustomed to developing the class by offering students opportunities to learn the concepts and laws while practicing scientific skills, which is a requirement of the P²BL approach.

The value of these results is limited to one of the teaching materials that make up the new curriculum, the iSTEM projects. It does not tell us what the effect is of other changes in the curriculum, such as the introduction of active teaching techniques in the classes of each discipline. We have not shown whether these other changes, also with the P²BL approach, produce similar or better changes more effectively and with the optimization of research efforts. This will be the focus of our next studies.