1. Introduction
In Chile, technical–professional higher education is provided both at universities and at institutions exclusively dedicated to technical programmes, such as professional institutes and technical training centres. This type of education trains highly skilled professionals, whose contribution is vital for strengthening the productive sector and promoting the sustainable development of the country. As argued by Wheelahan and Moodie (2024), these institutions are fundamental for fostering collective capabilities and promoting inclusive development, becoming essential local actors for regional progress. From the perspective of institutional logics, these organisations face educational and productive challenges defined by three main orders: the state, the market, and the professions (Zoellner, 2024). In this context, the state ensures equitable access to education, the market demands competencies aligned with productive needs, and the professions require standards that ensure quality and legitimacy.
In terms of structure, although these programmes share a competency-based approach and an average duration of four to five semesters, they differ according to the type of institution that delivers them. Technical training centres and professional institutes are exclusively dedicated to technical–professional education, whereas universities combine this offering with undergraduate, postgraduate, and research programmes. From a social perspective, this educational modality plays a key role in ensuring access to higher education for students from socio-economically vulnerable backgrounds, due to its largely non-selective nature, which reinforces its function as an instrument of equity and social mobility (Esmar & Poo, 2022).
With a focus on short-cycle programmes oriented towards the productive sector, technical–professional higher education facilitates early entry into the labour market, particularly for students belonging to the lowest income quintiles. In fact, 71% of these students are the first in their families to access higher education, and 76% belong to the three lowest household income quintiles (Ministerio de Desarrollo Social y Familia, 2024).
Physics courses are typically offered in the early semesters of technical programmes, especially in disciplines such as mechanics, construction, design, and technology. Subjects like applied physics, mechanical physics, or principles of physics form the foundation for understanding and solving problems specific to these technical specialisations. However, Chilean secondary education student performance in science subjects has historically been low, as evidenced by national and international standardised tests. For example, the results of the 2018 PISA test showed that Chilean students scored below the OECD average in scientific competencies, with a significant proportion performing below Level 2, considered basic (Ministerio de Educación de Chile, 2019). These challenges are more pronounced among students from low- and middle-income socioeconomic backgrounds, with a steady decline in performance since 2012. Similarly, the results of the 2021 University Transition Test revealed significant disparities between students from public schools and those from private institutions, as well as between students from the humanities–scientific track and those from the technical–professional track (Subsecretaría de Educación Superior, 2021). These disparities pose significant challenges to the education system and directly impact higher education outcomes.
In addition to these issues, there is a need to foster active learning in technical training to develop essential skills such as critical thinking, problem-solving, planning, teamwork, and action (Subsecretaría de Educación Superior, 2023). Competence-based education prioritises developing skills like problem-solving, teamwork, and information management (Ministerio de Educación de Chile, 2017). However, these competencies, which are essential for technical professionals, are not always effectively developed through traditional methodologies, underscoring the importance of implementing active learning methodologies.
Active methodologies have gained prominence in higher education, as demonstrated by a Scopus database search, conducted by the authors, using the keywords ‘Active’, ‘Learning’, and ‘University’. This search, limited to open access articles, identified 297 articles published in 2024 that included these terms in their titles, abstracts, or keywords. Moreover, a growing trend in publications was observed from 2019 to 2023 for this search.
Problem-based learning is an active methodology proven effective in developing skills and attitudes (Gil-Galván et al., 2020). Studies have shown that students perceive problem-based learning as a motivating tool that facilitates the construction and integration of knowledge more effectively than traditional methodologies (Alreshidi & Lally, 2024; Delgado Trujillo & de Justo Moscardó, 2018; Gil-Galván et al., 2020). It has been associated with improved academic performance and higher student satisfaction rates (Rodríguez & Fernández-Batanero, 2017). Furthermore, problem-based learning promotes transversal competencies such as teamwork, critical thinking, and autonomous learning, which are crucial for future professional careers (Sepúlveda et al., 2021; Urrutia-Heinz et al., 2020).
Despite the growing interest in problem-based learning, its impact on physics teaching within technical–professional higher education remains under-researched. Most published studies have focused on other disciplines or educational levels, leaving a gap in understanding how this methodology can transform physics teaching in technical settings. A search in the Scopus database, using the keywords ‘active’, ‘learning’, ‘university’, and ‘physics’, identified 28 open access articles published between 2019 and 2024. Of these, 16 focused on university students, covering areas such as engineering education (three articles), basic sciences (two), introductory physics (six), and STEM degrees, health sciences, architecture, and technology (five). Additionally, four articles addressed secondary education research, and four studies analysed the preparation of future teachers and university lecturers. Some articles also explored mixed contexts, such as undergraduate physics students and secondary education (one) or university degrees in architecture and engineering (one). Finally, two studies focused on specific technical disciplines, such as chemistry and environmental physiology. These findings highlight the need to further explore the impact of problem-based learning on physics teaching in technical–professional education, thereby contributing to the development of knowledge in this specific area.
This study therefore seeks to contribute empirical evidence on the potential of problem-based learning to improve physics education in technical–professional contexts, and aims to address this gap by answering the following research questions: (1) How does the problem-based learning methodology impact students’ conceptual and propositional learning in physics teaching within technical–professional education in Chile? (2) In what ways does problem-based learning contribute to the development of transversal competencies, such as problem-solving, information management, and teamwork, among students in technical–professional programmes? (3) What is the level of student satisfaction with the problem-based learning methodology, and how do they perceive its impact on their motivation and academic engagement? (4) What evidence exists that problem-based learning can enhance meaningful learning in the technical–professional context by aligning academic content with practical applications?
These questions are grounded in a constructivist perspective of learning and seek to evaluate the pedagogical potential of problem-based learning within the framework of meaningful learning.
2. Theoretical Framework
Building on the issues raised in the introduction and aiming to address the research questions outlined, this theoretical framework presents the conceptual and empirical foundations underpinning the use of problem-based learning in the teaching of physics within technical–professional higher education. It draws upon theories of meaningful learning and constructivist pedagogy to justify the selected methodological approach.
2.1. Physics Education in Technical–Professional Higher Education Training and Meaningful Learning
In the context of technical university education, it is essential to move beyond traditional approaches that limit students to specific occupational roles. As Höhns (2022) points out, it is necessary to promote an education that connects academic content with practical applications, enabling students to develop broader and more relevant perspectives for their professional future. In this regard, preparing students with the competencies required to face the challenges of a constantly changing productive and technological environment, as well as the need for continuous learning, necessitates the promotion of meaningful learning. This type of learning, as described by Ausubel et al. (1983), is characterised by the integration of new knowledge into existing cognitive structures, facilitating students’ contextual application of what they have learned and enabling the resolution of discipline-specific problems. In technical–professional higher education training, the study of topics such as kinematics and dynamics is fundamental for fields like mechanics and construction. Physics courses in technical higher education typically address concepts like time, distance, measurements, vectors, velocity, motion, Newton’s laws, equilibrium, and energy. These contents are not only foundational for understanding classical physics principles but also have direct applications in technical specialties, such as metrology, thermal machinery operations, structural design, and the understanding of mechanical systems involving movement and forces in machinery and constructions, among others.
However, students often face difficulties in learning these topics due to preconceived misconceptions, such as the direct association between force and motion or the confusion between velocity and acceleration, as noted by Pozo and Gómez (1998). These preconceived notions, widely studied and common in everyday life, often misalign with scientific principles, creating significant barriers to understanding physics. According to Wandersee et al. (1994), as cited by Mufit et al. (2018), misconceptions occur across all areas of physics and at various educational levels. This is consistent with the findings of Guerra-Reyes et al. (2024), who highlight that these misconceptions hinder the development of critical thinking and logical–mathematical reasoning in disciplines such as physics, particularly in complex topics like kinematics, dynamics, and thermodynamics.
From Ausubel’s perspective, meaningful learning occurs when students connect new ideas with prior knowledge in a non-arbitrary and substantial way (Ausubel et al., 1983). To achieve this, educational materials must logically relate to the student’s cognitive structure, and pedagogical strategies should facilitate this connection. Prior organisers and carefully selected materials can promote long-term retention and facilitate the practical application of concepts in situations relevant to their technical specialties.
According to Ausubel, meaningful learning manifests in three forms: representational, conceptual, and propositional. Representational learning involves assigning meaning to symbols and basic concepts, serving as the foundation for more complex learning. Conceptual learning integrates new concepts with prior knowledge, enhancing understanding and application. Finally, propositional learning focuses on linking new propositions to existing cognitive structures, enabling problem-solving. When achieved through discovery, this type of learning allows students to generate meaningful propositions derived from posed problems, contributing not only to the understanding of concepts but also to transforming them into new propositions that are significant for problem-solving. In technical–professional training, this approach aids in developing key competencies, such as problem-solving and the contextualised application of knowledge, aligning with the objectives outlined in the Chilean Technical–Professional Qualification Framework, which emphasises preparing students to face labour market challenges (Ministerio de Educación de Chile, 2020).
2.2. Problem-Based Learning
Problem-based learning has proven to be an effective methodology for enhancing conceptual understanding of physics (Kanyesigye et al., 2022; Mrani et al., 2020; Sulaiman et al., 2024), as well as for developing essential skills such as critical thinking, communication, and teamwork (Hastuti et al., 2024; Kurniawan et al., 2024; Ndiung & Menggo, 2024; Suprapto et al., 2024). This active methodology focuses on students who are presented with problems that lack a single solution, encouraging them to solve these in groups under the guidance of a tutor acting as a facilitator rather than a primary knowledge transmitter (Morales Bueno & Landa Fitzgerald, 2004).
Problem-based learning originated in medical education during the 1960s but has evolved into a pedagogical approach with broader epistemological foundations. Savin-Baden and Major (2004) highlight that problem-based learning is not only a didactic methodology but also a situated practice grounded in constructivist and postmodern perspectives. This approach promotes the active construction of knowledge around authentic problems, with the student playing a central role as a reflective and autonomous subject. Furthermore, its expansion has coincided with a structural transformation in higher education, characterised by increased student diversity and a growing demand for flexible and contextualised approaches. In this context, problem-based learning represents not only a methodological innovation but also a response to new ways of conceptualising learning, teaching, and the relationships between university, society, and industry (Savin-Baden & Major, 2004).
Its benefits include increased motivation (Bruna et al., 2019), deeper learning, and improved attitudes towards studying (Alreshidi & Lally, 2024; Pu et al., 2019), as well as enhanced confidence, a sense of responsibility, and interpersonal skills (Ndiung & Menggo, 2024). By working on real-world problems, students experience learning that is more connected to professional reality, which increases their motivation by helping them understand the relevance of their future work (González Javier et al., 2009). Furthermore, problem-based learning fosters critical thinking through the continuous analysis of information (Suprapto et al., 2024), and develops essential skills for identifying and solving problems, providing significant opportunities for creativity (Escribano & Del Valle, 2008), active participation, and peer interaction (Kurniawan et al., 2024).
In addition to fostering the learning of disciplinary content, problem-based learning also promotes essential interpersonal skills, such as cooperation and effective communication. From a constructivist perspective, group work constitutes not only a means but also an object of learning. As Walsh (2005) argues, group development in problem-based learning progresses through various stages—formation, conflict, norming, and performing—which require reflective intervention by the tutor to facilitate cohesion, trust, and peer learning. This approach allows collaborative work to be understood not merely as an external condition, but as a critical pedagogical dimension that directly influences the quality of the learning constructed.
From a pedagogical standpoint, problem-based learning promotes the socially mediated construction of knowledge. Boud and Feletti (1997) emphasise that the principle of articulation implies that students must explain and share their learning with their peers, fostering collective understanding and strengthening cooperation. This interaction not only deepens learning but also facilitates the development of communication and collaborative skills, which are essential in technical and professional contexts.
Nguyen et al. (2024) highlight that the effective implementation of problem-based learning requires strategic curricular planning that considers both the design of authentic problems and the alignment of teaching materials and assessment. These aspects are fundamental to ensuring that this methodology has a significant impact on the development of key competencies in students.
In general, the problem-based learning workflow begins with recognising the topic, followed by problem formulation, supervision, monitoring, and presentation of results (Morales Bueno & Landa Fitzgerald, 2004; Varela-Guntiñas, 2016). In this context, the introduction of brief assessments before the reporting phase can be an effective strategy to improve academic performance, as it fosters self-directed learning and prepares students for more productive discussions (Bestetti et al., 2017). Assessment integrates both learning outcomes and the skills and attitudes acquired during the process, utilising various formats (Gutiérrez Ávila et al., 2012).
From a contemporary perspective, assessment in the context of problem-based learning should not focus solely on academic outcomes, but rather incorporate the analysis of processes, critical reflection, and active student participation. Moore and Poikela (2011) propose a typology comprising three fundamental purposes of assessment in problem-based learning: assessment for accountability (aimed at measuring outcomes and efficiency), assessment for development (focused on providing useful information to improve practice), and assessment for knowledge (intended to generate deep understanding of learning or change management). In particular, developmental assessment, which is formative in nature, seeks the continuous improvement in teaching and learning processes, emphasising the quality of the educational environment and the student experience. This perspective encourages the use of participatory strategies such as self-assessment and peer assessment, which strengthen the ownership of the learning process by those involved. In line with this approach, the present study incorporated specific rubrics to assess the process of problem-solving and collaborative work, enabling the analysis of dimensions such as problem understanding, information management, and group interaction.
Despite its benefits, the literature also points out certain challenges, such as unequal group work (Cujba & Pifarré, 2024), variations in how faculty perceive their role as facilitators—which can significantly differ between experienced and less-prepared teachers, affecting the effectiveness of the learning process (Sunarno et al., 2024)—and issues in peer evaluation and self-assessment, especially when students lack experience or an understanding of their importance. Additionally, there are persistent barriers such as rigid curricula and a culture more focused on content than methodologies, which can create resistance to change (Escribano & Del Valle, 2008). Moreover, its implementation may limit the amount of content covered, making it necessary to design problems that guide learning (Marcinauskas et al., 2024).
Despite the demonstrated benefits of problem-based learning, limited research has explored its integration into technical–professional physics education—particularly from the perspective of meaningful learning. This study therefore seeks to contribute to filling this gap by providing empirical evidence in this specific context.
Problem-based learning has a set of characteristics that promote meaningful learning, as it is based on constructivist philosophy. This methodology assumes that each student constructs their own knowledge by using relevant, carefully designed materials and drawing on prior experience to exchange initial ideas with peers or the teacher. A correspondence is presented in Table 1.
In summary, the theoretical foundations of this study lie in the constructivist paradigm and the principles of meaningful learning, with problem-based learning serving as a pedagogical strategy aligned with these principles. The coherence between the theoretical foundations and the research design supports a rigorous analysis of students’ conceptual and propositional understanding, transversal competency development, and satisfaction. These theoretical underpinnings directly inform the research questions posed and guide the selection of instruments and procedures, ensuring that the evaluation captures the multidimensional nature of learning in technical–professional physics education.
This theoretical grounding is further operationalised in the Methodological Section through the design of rubrics and data collection tools aligned with the dimensions of meaningful learning and collaborative problem-solving.
3. Materials and Methods
This section presents the methodology designed to address the four research questions related to the impact of problem-based learning on (1) conceptual and propositional learning, (2) the development of transversal competencies, (3) students’ satisfaction, and (4) the potential for meaningful learning through real-world problem integration.
3.1. Sample
This study targeted first-year students enrolled in the subject ‘Introduction to Physics’ at a technical–professional higher education institution in Chile during the 2022 academic year. The sample consisted of students from three sections of the course, selected from a total of seven sections offered by the university in technical programmes in the field of mechanics.
This subject is taught in the first semester of a total of four semesters that constitute the duration of the programmes and does not require prior coursework as a prerequisite. A total of 122 students participated, of whom 38 were enrolled in the University Technician in Industrial Mechanics programme and 84 in the University Technician in Mining and Metallurgy programme.
The participants were selected based on their direct admission from secondary education, without additional entrance examinations, ensuring a sample representative of the typical demographics of students in these programmes. The sample included 112 men and 10 women, aged between 18 and 29, reflecting the gender distribution commonly observed in technical–professional fields related to mechanics and mining in Chile.
3.2. Design
The activities associated with problem-based learning were carried out over five weeks, comprising two weekly in-person sessions of 3.5 h and one independent study session of 1.75 h outside the classroom.
The statements of Problems 1 and 2 included in this study are the same as those given to the students. They were originally written in Spanish and subsequently translated into English for the manuscript. During a previous round of review, based on comments from other reviewers, minor adjustments were made to the English version to enhance clarity, while preserving the original pedagogical content.
A limited but meaningful implementation of problem-based learning was conducted in order to allow for an in-depth observation of the effects of this methodology on conceptual learning, problem-solving, and collaborative work.
The problems used in the intervention were selected based on the contents of the course syllabus, with the aim of ensuring alignment with the intended learning objectives. They were validated through expert judgement, which assessed their relevance, clarity, and conceptual coherence.
The problems were presented to students within a structured learning sequence that included preparatory readings and guiding questions designed to activate prior knowledge and promote critical reflection. The use of a Formula 1 car in Problem 1 was intended to present a familiar and engaging scenario for the students, stimulating their motivation. The activity required students to select a real video, analyse the observed motion of the car, extract relevant data, construct tables and graphs, and finally interpret the results—thus promoting active, contextualised, and meaningful learning.
In Problem 2, students were invited to contrast Aristotle’s historical explanation of falling bodies with the current scientific view, in order to highlight the evolution of scientific knowledge and the importance of using measuring instruments, which are an essential component of technical practice. The aim of this problem was not to approach the phenomenon from Aristotle’s model, but to foster critical reflection on the evolution of scientific knowledge. The comparison between Aristotle’s explanation and the modern scientific view enabled students to distinguish intuitive or common-sense reasoning from reasoning based on empirical evidence and measurement tools, thereby strengthening their scientific reasoning.
Students’ teamwork was monitored by the lead researcher during the in-person sessions. Furthermore, the overall instructional plan included a weekly sequence outlining the tasks to be completed both inside and outside the classroom, along with specific guidance for independent study. The main form of feedback was provided during the process evaluations, through the use of predefined rubrics.
The main activities included the following: ▪. Initial Diagnosis: Application of a pretest to evaluate prior knowledge. ▪. Problem Development:
Problem 1: Construct graphs to describe the motion of a Formula 1 car over a time interval during which it undergoes uniformly accelerated rectilinear motion.
Problem 2: Aristotle once proposed an explanation for the falling of objects. What is the current scientific explanation? What information is available today that was not in Aristotle’s time?
▪. Final Evaluation: Application of a post-test and a student satisfaction survey.
The partial implementation of problem-based learning was chosen to ensure feasibility within the course’s institutional and curricular structure. This approach enabled a focused evaluation of its pedagogical effects while maintaining alignment with other course components, thereby facilitating comparison and integration within the broader instructional framework.
3.3. Procedure
At the beginning of the semester, students were informed that they would participate in a pedagogical intervention based on active methodologies, integrated into the regular development of the course. It was clarified that the results would be analysed anonymously, without any association with names or personal data. During an introductory session, the course syllabus was presented, including the general schedule, contents, assessment activities, and key dates. One session was specifically dedicated to introducing the problem-based learning methodology, its objectives, general structure, and expected forms of active participation. Brief examples of similar problems were provided, and the steps of the problem-solving process were explained.
The intervention was led by the first author, who assumed the role of learning facilitator: promoting collaborative work, posing open-ended questions, and offering formative feedback without giving direct answers. The same person was responsible for assessing the students using pre-defined rubrics. Throughout the intervention, the institutional Moodle platform served as the main support space. It hosted problem statements, rubrics, Supplementary Materials, and enabled submission of intermediate and final group work. No specialised digital tools for problem-solving in physics were used, as the focus was on conceptual argumentation and teamwork.
The results presented are derived from three parts, each with a different methodological focus: (1). Evaluation of Learning Achieved: To analyse the impact of the educational intervention, a pre-experimental design complemented by a descriptive analysis of the results was used. Changes in learning were measured by comparing the results obtained in a pretest and a post-test, applied before and after the intervention.
Analysis of the Development of Transversal Competencies: The development of competencies such as problem-solving, teamwork, and the use and identification of information was evaluated. This analysis was carried out through the application of specific rubrics designed to measure both the acquisition and application of these competencies within the context of problem-based learning.
Determination of Satisfaction Levels: To evaluate the level of student satisfaction with the Problem-Based Learning methodology, an exploratory descriptive study of a non-experimental quantitative type was implemented. This analysis was based on a survey that covered dimensions such as academic experience, proposed didactics, and teaching practice using an initial satisfaction questionnaire consisting of 23 questions.
Given the specific focus of this study, a subset of 14 questions considered most representative and relevant to the objectives was selected.
3.4. Evaluation Instruments
The evaluation events, the instruments used, the applied methodologies, and the expected outcomes are summarised in Table 2 below.
Each instrument was aligned with a specific research question: the pretest and post-test targeted conceptual and propositional learning (RQ1), the rubrics assessed transversal competencies such as problem-solving and teamwork (RQ2), and the student satisfaction survey explored perceptions of motivation and engagement (RQ3). Additionally, the integration of real-world problems sought to evaluate the potential for meaningful learning through practical application (RQ4).
3.5. Details of the Evaluation Instruments
(1). Pretest and Post-Test:
To evaluate the prior and final knowledge of students, a specific instrument was designed for this research. The pretest and post-test included 23 questions related to kinematics and dynamics content based on the Introduction to Physics course syllabus. These were divided into two main categories: (1) Conceptual learning: Understanding fundamental concepts such as measurement systems and equivalences, and (2) Propositional learning: Solving practical problems and analysing graphs. Although the pretest and post-test included multiple-choice and short-answer questions, commonly found in traditional assessments, the items were contextualised to reflect real-world applications and aligned with the conceptual areas addressed during the intervention. For example, students were asked to convert units using authentic examples (e.g., converting inches to metres), interpret physical graphs related to motion, apply vector addition, estimate measurement errors, and explain scientific principles such as gravitational acceleration or equilibrium using diagrams. This contextualisation was intended to foster transfer of learning and applied reasoning.
Sample questions included:
What measurement systems do you know for measuring length?
Consider the equivalence: 1 m = 39.37 inches. How many metres equal 520 inches?
In uniformly accelerated rectilinear motion, which of the following X(t) graphs best represents position as a function of time?
The instrument was validated through expert judgment, who assessed each item in terms of validity, clarity, and relevance, obtaining an average content validity coefficient of 0.91. Subsequently, Cronbach’s alpha coefficient was calculated, yielding values of 0.84 for the pretest and 0.91 for the post-test, confirming high internal consistency for both applications.
The pretest results informed the planning of activities. Specifically, prior organisers, such as text readings, video viewing, and group activities, were employed to reinforce initial concepts and guide students toward key topics.
Evaluation of Problem 1 and Problem 2 Processes:
A single process evaluation rubric was designed based on five key dimensions: (1) Understanding the problem/project, (2) Identification and selection of information and tools, (3) Recognition of methods or strategies, (4) Proposing relevant solutions, (5) Collaborative work. Each dimension included specific indicators describing performance across four levels, scored from 0 to 3 points, where 0 indicated insufficient performance and 3 indicated outstanding performance. For example, in ‘Understanding the problem/project’, the highest level (3 points) was achieved when the group fully understood and addressed the problem in its context, while the lowest level (0 points) indicated a lack of understanding or inappropriate addressing of the problem.
The rubric was validated by expert judgment for validity, clarity, relevance, and coverage, obtaining average scores of 4.33 or higher on a 5-point scale. Expert recommendations were incorporated into the final version of the rubric.
Final Evaluation of Problem 1:
A final rubric based on four key dimensions was designed: (1) Use of information, (2) Identification of motion variables, (3) Motion evaluation, (4) Collaborative work.
The rubric followed the same scoring criteria as the process rubric and was validated similarly.
Final Evaluation of Problem 2:
This rubric also included four dimensions: (1) Use of information, (2) Identification of differences in explanations, (3) Accurate evaluation of information, (4) Collaborative work.
Expert validation yielded high average scores, with recommendations incorporated into the final rubric.
Satisfaction Survey:
To analyse student satisfaction with the implemented methodology, a 5-point Likert-type questionnaire was used, with responses ranging from ‘strongly disagree’ (0 points) to ‘strongly agree’ (4 points). The questionnaire included 17 representative questions divided into three main areas: (1) Academic experience, (2) Proposed didactics, (3) Teaching practice.
Expert validation ensured the instrument’s validity, clarity, and relevance, with all criteria scoring an average of 4 or higher on a 5-point scale. The final questionnaire had a Cronbach’s alpha of 0.98, indicating high internal consistency.
For this article, 14 questions were selected based on their relevance and representativeness regarding the study’s objectives, ensuring comprehensive evaluation of the three main dimensions.
The design of the instruments was guided by the theoretical framework, particularly by the dimensions of meaningful learning (conceptual and propositional understanding) and collaborative problem-solving, thus ensuring conceptual alignment across all phases of the study—from data collection to interpretation.
4. Results
This section presents the findings of the study in relation to the four research questions. The results are organised into three subsections: the impact of the intervention on conceptual and propositional learning (RQ1 and RQ4), the development of transversal competencies and group performance during problem-solving (RQ2), and student satisfaction with the implemented methodology (RQ3).
4.1. Impact of Problem-Based Learning on Conceptual and Propositional Learning in Technical–Professional Contexts (RQ1 and RQ4)
This subsection addresses RQ1 and RQ4, which focus on the impact of problem-based learning on students’ conceptual and propositional learning in physics, as well as on evidence of meaningful learning through the articulation of academic content with practical applications in technical–professional contexts.
The effectiveness of the pedagogical intervention was evaluated through quantitative analysis, employing paired t-tests and Wilcoxon signed-rank tests. These statistical methods were chosen to assess changes in learning outcomes before and after the intervention, in line with the objective of quantifying the impact of problem-based learning on students’ application and understanding of physics concepts. The paired t-test was used to detect significant changes in mean scores, assuming a normal distribution, while the Wilcoxon test addressed any non-normal distribution, ensuring the robustness of the findings.
The results are detailed in Table 3 and Table 4. Table 3 presents the initial and final mean scores, along with standard deviations, for both conceptual and propositional learning. Conceptual learning scores increased from an initial mean of 63.88% to a final mean of 81.88%, with a notable reduction in the standard deviation from 23.39 to 10.67. The results for propositional learning showed an even more pronounced improvement, with mean scores rising from 14.93% to 68.53% and a reduction in the standard deviation from 9.65 to 8.74. These results are graphically represented in Figure 1 and Figure 2, illustrating the distribution of scores before and after the intervention.
Table 4 presents the results of the statistical tests, showing a t-value of −5.38 and a p-value of 0.001 for conceptual learning, and a t-value of −17.09 with a p-value of 0.00001 for propositional learning. The Wilcoxon test corroborated these findings, with p-values of 0.007 and 0.00001, respectively. These results indicate statistically significant improvements in both types of learning, suggesting that problem-based learning may be effective in strengthening the understanding and application of physics concepts.
These statistically significant improvements provide robust evidence that problem-based learning fosters meaningful learning, both conceptually and propositionally, by enabling students to understand and apply physics content in situations relevant to their technical–professional training.
4.2. Development of Transversal Competencies and Group Performance in Collaborative Problem-Solving (RQ2)
In response to Research Question 2 (RQ2), this section presents the analysis of the development of transversal competencies in the context of collaborative work during the resolution of contextualised physics problems.
Process evaluation of problem 1
Table 5 presents the calculated means for each dimension evaluated during the development of Problem 1.
Correlation analysis using Pearson’s correlation coefficient indicated a strong positive relationship between problem understanding and collaborative work (r = 0.78). This suggests that groups with better problem comprehension tended to work more effectively as a team. Similarly, information identification and selection showed a strong correlation with collaborative work (r = 0.70), reinforcing the idea that effective collaboration enhances the ability to select relevant information and apply appropriate strategies.
Final evaluation of problem 1
As in the process evaluation, Table 6 presents the results, showing the means for each evaluated dimension.
The findings were consistent with those from the process evaluation, with a strong interrelationship between information use and collaborative work (r = 0.76). These findings highlight the value of the methodology not only in terms of theoretical knowledge acquisition but also in the development of practical skills such as collaboration and problem-solving.
Process evaluation of problem 2
Table 7 shows the means obtained for the dimensions evaluated during the development of Problem 2.
The analysis of Problem 2 confirmed that better problem understanding is closely related to effective collaborative work (r = 0.74), reinforcing the positive impact of problem-based learning.
Final evaluation of problem 2
Table 8 presents the calculated means for each dimension in the final evaluation of Problem 2.
Correlation analysis for Problem 2 revealed a strong relationship between information use and collaborative work (r = 0.75), reinforcing the importance of teamwork for proper information evaluation and management. Similarly, the evaluation of information showed a strong correlation with collaborative work (r = 0.69), suggesting that students who work effectively in groups are better able to apply concepts and critically evaluate available information.
Taken together, the results suggest that collaborative problem-solving within the framework of problem-based learning fosters the development of transversal competencies such as teamwork, critical thinking, and information management. This provides empirical evidence of its relevance in technical–professional education, in line with the constructivist approach that underpins this methodology, whereby knowledge is socially constructed through peer interaction and the resolution of authentic problems (Boud & Feletti, 1997; Morales Bueno & Landa Fitzgerald, 2004).
4.3. Student Satisfaction with the Implemented Problem-Based Learning Methodology (RQ3)
Table 9 presents the average scores for each evaluated item, organised into three dimensions that reflect students’ perceptions and overall assessment of the implemented problem-based learning methodology.
In the Academic Experience dimension, students positively valued the methodology’s effectiveness in improving learning in physics, although they perceived less novelty in the problem-based approach. This dimension had an average score of 3.5. Regarding Proposed Didactics, students emphasised the clarity of objectives and strategies used, with an overall average of 3.7. Finally, in Teaching Practice, the professor’s guidance, ability to maintain group interest, and effective communication were highly rated, achieving an average score of 3.9.
A statistical analysis revealed a moderate to strong correlation between the evaluated dimensions, with a Pearson correlation coefficient of 0.61. This value suggests a moderate to strong relationship between the analysed variables, indicating significant associations among the questionnaire areas. These results support the validity and relevance of the instrument for measuring student satisfaction with the implemented methodology.
This finding suggests a consistent pattern in students’ responses across the dimensions, reinforcing the instrument’s internal coherence and its suitability for assessing satisfaction with the implemented approach.
These findings are consistent with learner-centred pedagogical principles, which emphasise students’ motivation, engagement, and autonomy as key components of meaningful learning (Pozo & Gómez, 1998; Ausubel et al., 1983).
5. Discussion and Conclusions
This study was conducted to evaluate the impact of problem-based learning on the teaching of physics in Chile’s technical–professional education, a domain that requires the cultivation of both technical and scientific skills. As evidenced in the literature review, this area remains underexplored in terms of pedagogical methodologies for teaching and learning.
Physics teaching is crucial in this type of education, especially in careers in the techno-scientific field that are constantly evolving, requiring learning approaches that equip students to address problems in a dynamic environment. Low academic performance in science, particularly in vulnerable socio-economic contexts, is a pressing issue. Results from standardised and large-scale tests reflect these learning gaps, emphasising the urgency of implementing more active and meaningful pedagogical strategies.
The main objective of this study was to evaluate whether problem-based learning could enhance conceptual and propositional learning and the development of transversal skills and student satisfaction. Through an evaluation designed using a mixed-methods approach that combined quantitative and qualitative methods, the results indicate significant improvements in these areas, along with a high valuation of the implemented methodology.
The results of this study confirm that problem-based learning is an effective methodology for promoting meaningful learning in the teaching of physics, as proposed by constructivist approaches to learning (Freeman et al., 2014; Hernández-Ramos et al., 2021). In terms of conceptual learning, Hernández-Ramos et al. (2021) highlight that PBL fosters conceptual understanding by connecting content to meaningful contexts. Similarly, Freeman et al. (2014) document that active methodologies significantly enhance academic performance, supporting the improvement observed between the pretest and post-test.
Regarding conceptual learning, an average increase of 18% was observed between the pretest and post-test results, representing a statistically significant improvement. This enhancement can be attributed to the constructivist nature of problem-based learning, which facilitates the understanding and application of concepts through active problem-solving.
The results for propositional learning were even more remarkable, with a 53.6% increase. This advance reinforces the idea that this methodology is particularly effective for fostering a deeper understanding of concepts that are often challenging for students. These findings align with previous studies that indicate problem-based learning is superior to traditional approaches in areas where students’ misconceptions conflict with correct scientific principles (Morales Bueno & Landa Fitzgerald, 2004; Rodríguez & Fernández-Batanero, 2017).
In terms of the development of transversal skills, such as problem-solving, teamwork, and information selection, significant improvements were also observed. Positive correlations between problem understanding and collaborative work (r = 0.78 in Problem 1 and r = 0.74 in Problem 2) suggest that deeper problem understanding promotes more effective collaboration. These results align with research demonstrating that this methodology fosters positive interdependence and creates a more dynamic and participatory learning environment (Nguyen et al., 2024). Nevertheless, it is worth stressing that some students were unfamiliar with or lacked prior experience in group work, which could also contribute to the results obtained in this aspect. From a teaching point of view, it is essential to recognise and allow adjustment periods to facilitate group dynamics.
Moreover, the integration of rubrics for process and collaborative work assessment was grounded in the need to promote formative practices consistent with the principles of problem-based learning. Within this pedagogical framework, self-assessment and peer assessment were used as educational strategies that, according to Walsh (2005), encourage students’ critical reflection on their own learning and that of their peers, thereby reinforcing both individual and collective responsibility in the learning process. These strategies also enable tutors to collect qualitative insights into group dynamics and to guide responsive interventions as needed.
These results align with the literature that highlights the importance of formative assessment in problem-based learning, particularly in supporting students’ metacognitive development and collaboration skills throughout the problem-solving process (Moore & Poikela, 2011; Gutiérrez Ávila et al., 2012).
Another important aspect is student satisfaction. This is a central topic in educational research, as it is closely linked to the quality of learning and academic success. The results of the Likert-scale questionnaire show that students positively valued the methodology, particularly in terms of academic experience and its contribution to improving their learning (mean = 3.9), understanding the proposed didactics, and the instructor’s practice. These findings support the idea that problem-based learning not only improves learning outcomes but also increases motivation and engagement among students (Ramos & Condotta, 2024), which is crucial in the technical–professional context, where students tend to be more oriented towards practical rather than theoretical aspects (Lárez Hernández & Jiménez, 2019).
This study seems to show that problem-based learning is an effective pedagogical tool for improving both meaningful learning and competency development in the teaching of physics within technical–professional higher education. The results support that it not only enhances conceptual and propositional learning, but also fosters essential transversal skills for the workplace, such as collaboration and problem-solving.
The implementation of problem-based learning provides an effective solution to the identified challenges by addressing learning gaps among technical–professional education students. Furthermore, high levels of student satisfaction indicate that problem-based learning not only has a positive impact on learning but also increases motivation and engagement as highlighted by Ramos and Condotta (2024), which are essential aspects for the long-term success of these students in a work context that demands practical and collaborative skills (Höhns, 2022).
From a broader perspective, the findings hold significant implications for the teaching of physics and other disciplines within technical and vocational education. Problem-based learning, by linking academic content with practical applications, provides a more relevant education aligned with the demands of the productive environment. These findings align with research that underscores the importance of equitable and authentic assessment practices in vocational education, where transparency and active student participation in the design and implementation of assessments play a central role (Sofía et al., 2022). This suggests that the methodology not only enhances learning outcomes but also better prepares students to face the challenges of the 21st century.
These results suggest that its implementation in technical–professional higher education programmes could be scalable at the national level, allowing for teaching more aligned with the needs of the productive sector. To maximise its impact, it would be advisable to integrate it into science curricula at the technical level, prioritising practical and collaborative training.
However, this study has some limitations that should be considered. The problems used in the intervention focused exclusively on the area of physics, which, although fundamental, limits the scope of the results. Future studies could explore a broader range of topics to evaluate how problem-based learning impacts other areas of learning. Additionally, the intervention period was relatively short, restricting the analysis of long-term effects on learning and competency development. A longer period would provide a more comprehensive perspective on the methodology’s impact.
Although the pre-test and post-test assessed learning across the entire course, the instruments were aligned with the core conceptual areas addressed in the problem-based learning activities, which extended over several weeks and constituted a substantial portion of the instructional time. Therefore, although it is not possible to attribute the observed improvements exclusively to problem-based learning, it is likely that this methodology played a significant role in these gains. Future research could deepen this analysis by employing quasi-experimental designs that allow for a more precise isolation of its specific effects. It would also be pertinent to explore the impact of problem-based learning on students’ employability and professional performance, providing further evidence of its relevance in technical and productive contexts.
In conclusion, this study provides a foundation for further exploration of active methodologies in technical training, contributing to better preparation, more tools, and a higher-quality, more relevant education for students.
Conceptualisation, G.M.A., I.M.G., and I.A.; methodology, G.M.A., I.M.G., and I.A.; software, G.M.A.; validation, G.M.A.; formal analysis, G.M.A., I.M.G., and I.A.; investigation, G.M.A., I.M.G., and I.A.; resources, G.M.A.; data curation, G.M.A.; writing—original draft preparation, G.M.A., I.M.G., and I.A.; writing—review and editing, I.M.G. and I.A.; visualisation, G.M.A.; supervision, I.M.G. and I.A.; project administration, G.M.A. All authors have read and agreed to the published version of the manuscript.
This research involved the implementation of an educational intervention in the classroom, with the collection of anonymised data (anonymous surveys, group reports, and academic grades). Since the study did not pose any risks to the participants nor involve the collection of identifiable information, ethical approval was not required according to the institution’s regulations in effect at that time.
Written informed consent was not obtained because all data were anonymised prior to analysis, and thus, the requirement for written consent was waived. However, verbal informed consent was obtained from all participating students before data collection, ensuring their voluntary participation and confidentiality. No identifiable personal data are included in this study; therefore, written informed consent for publication is not applicable.
The raw data supporting the conclusions of this article will be made available by the authors upon request.
The authors report there are no competing interests to declare.
Footnotes
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Figure 1 Comparison of pretest and post-test results for conceptual learning.
Figure 2 Comparison of pretest and post-test results for propositional learning.
Correspondence between meaningful learning and problem-based learning.
| Meaningful Learning (Ausubel’s Theory) | Problem-Based Learning | Description |
|---|---|---|
| Integration of prior knowledge | Activation of prior knowledge through the problem | The significant problem facilitates the connection with prior knowledge, allowing students to anchor new concepts into their cognitive structure. |
| Relevant material connected to prior experience | Real and contextualised problem | Contributes to the student’s education, not only in their area of specialisation but also in the development of skills relevant to the academic environment. |
| Structured and non-arbitrary learning | Structured development of investigation and solution of the problem | The process follows guided steps that help orient students and provide continuous feedback. |
| Long-term learning (retention and future application) | Synthesis and presentation of the final response | The final presentation serves as a synthesis of learning, facilitating retention and the application of knowledge in future contexts. |
Evaluation instruments and associated competencies.
| Information | Instrument | Method | Expected Outcome | Evaluated Competencies |
|---|---|---|---|---|
| Diagnosis (Pretest) | Questionnaire | Questionnaire | Determine students’ prior learning in terms of conceptual and propositional knowledge. | Scientific and mathematical reasoning and problem-solving |
| Problem Process (1 and 2) | Rubric | Group work | Evaluate and provide feedback on group processes during problem-solving. | Problem-solving, information management, teamwork |
| Problem 1 | Rubric | Group work | Evaluate learning achieved through problem-solving. | Problem-solving, information management, teamwork |
| Problem 2 | Rubric | Group work | Evaluate learning achieved through problem-solving. | Problem-solving, information management, teamwork |
| Post-test | Questionnaire | Questionnaire | Determine students’ learning outcomes in terms of conceptual and propositional knowledge. | Scientific and mathematical reasoning and problem-solving |
| Survey | Likert scale | Survey | Assess whether the methodology was well-received by students. | Collaborative work |
Changes in means and standard deviations of learning.
| Category | Initial Mean (%) | Final Mean (%) | Initial Standard Deviation | Final Standard Deviation |
|---|---|---|---|---|
| Conceptual Learning | 63.88 | 81.88 | 23.39 | 10.67 |
| Propositional Learning | 14.93 | 68.53 | 9.65 | 8.74 |
Statistical test results.
| Category | Statistical Test | t-Value | p-Value | Wilcoxon (p-Value) |
|---|---|---|---|---|
| Conceptual Learning | Paired t-test | −5.38 | 0.001 | 0.007 |
| Propositional Learning | Paired t-test | −17.97 | 0.00001 | 0.00001 |
Means by dimension for process evaluation (Problem 1).
| Dimension | Problem Understanding | Information Identification and Selection | Method Recognition | Proposing Relevant Solutions | Collaborative Work |
|---|---|---|---|---|---|
| Mean | 2.45 | 2.23 | 2.32 | 2.23 | 2.45 |
Means by dimension for final evaluation (Problem 1).
| Dimension | Information Use | Motion Variables Identification | Motion Evaluation | Collaborative Work |
|---|---|---|---|---|
| Mean | 2.19 | 2.26 | 2.23 | 2.37 |
Means by dimension for process evaluation (Problem 2).
| Dimension | Problem Understanding | Information Identification and Selection | Method Recognition | Proposing Relevant Solutions | Collaborative Work |
|---|---|---|---|---|---|
| Mean | 2.26 | 2.03 | 2.19 | 2.06 | 2.29 |
Means by dimension for final evaluation (Problem 2).
| Dimension | Information Use | Identifying Differences | Accurate Information Evaluation | Collaborative Work |
|---|---|---|---|---|
| Mean | 2.16 | 2.13 | 2.16 | 2.32 |
Results of the student satisfaction survey on problem-based learning.
| Question | Mean |
|---|---|
| Academic Experience | |
| 1. I find the problem-based approach innovative. | 3.1 |
| 2. Working with problems/projects contributes to meeting the objectives of the physics course. | 3.1 |
| 3. Projects improve learning in physics. | 3.9 |
| 4. Problems contribute to collaborative work. | 3.6 |
| 5. Problems support future professional development. | 3.8 |
| Proposed Didactics | |
| 6. Knowing the objectives before starting the problems was important. | 3.9 |
| 7. Knowing the work format and times beforehand was important. | 3.8 |
| 8. Communication among peers was easy. | 3.5 |
| 9. The material and bibliography available in the virtual classroom helped guide the problem-solving process. | 3.8 |
| 10. The evaluation method allows understanding the levels of achievement reached by the group. | 3.7 |
| Teaching Practice | |
| 11. Formative assessment was constructive and timely for developing the final problem. | 3.8 |
| 12. The professor’s guidance was appropriate for the activity. | 3.9 |
| 13. The professor maintained our interest throughout the problems. | 3.8 |
| 14. The professor maintained good communication with students in and out of class. | 3.9 |
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Details
; Greca, Ileana M 2
; Arriassecq Irene 3
1 Departamento de Ciencias, Universidad Técnica Federico Santa María, Viña del Mar 2340000, Chile, Doctorado en Didácticas Específicas, Universidad de Burgos, 09001 Burgos, Spain
2 Faculty of Education, Universidad de Burgos, 09001 Burgos, Spain; [email protected]
3 ECienTec, Facultad de Ciencias Exactas, Universidad Nacional del Centro de la Provincia de Buenos Aires, Tandil 7000, Provincia de Buenos Aires, Argentina; [email protected], CONICET, Ciudad Autónoma de Buenos Aires 1425, Argentina