Beyond fostering teamwork and critical thinking, engineering education must also address contemporary global challenges. Among these, sustainability constitutes one of the most pressing issues in problem-solving [3]. In this context, the engineering profession plays a core role in responding to these emerging demands by drawing on knowledge and competencies from multiple disciplines and advancing innovative areas such as resource productivity, energy efficiency, integrated systems design, and biomimicry, that is, nature-inspired design [4]. The intricate, interdependent nature of sustainability challenges requires a multidisciplinary, collaborative approach to develop effective, long-lasting solutions. Recognising this need, the United Nations General Assembly adopted the Sustainable Development Goals (SDGs) in 2015, establishing “a shared blueprint for peace and prosperity for people and the planet, now and into the future” [5].

The increasing complexity of urban environmental challenges has driven the adoption of Green Infrastructure (GI) as an integrated solution to enhance city resilience and sustainability. These infrastructures combine natural and engineered elements to provide multiple benefits, including stormwater management, improved air quality, and urban heat mitigation [6]. Additionally, they play a crucial role in biodiversity conservation and restoring natural cycles in urban areas, transforming impervious spaces into ecologically functional environments. In engineering, implementing these solutions requires an interdisciplinary approach that integrates technical and ecological knowledge to optimise performance and reduce maintenance costs [7]. Thus, GI addresses contemporary environmental challenges and creates opportunities for better integration between the built environment and natural systems, fostering more sustainable and resilient cities. Several developed and developing countries are already using this approach to obtain economic, sociocultural, and environmental advantages [8].

GI encompasses a broad range of nature-based and hybrid solutions implemented in urban environments, including vegetated roofs and façades, rain gardens, bioretention systems, infiltration swales, detention basins, permeable pavements, and green streets, designed to enhance environmental performance and urban resilience. In recent years, the intensification of climate change impacts has led cities worldwide to seek adaptive strategies to mitigate environmental risks while strengthening socioecological resilience. In this context, GI has emerged as a multifunctional approach that integrates ecological processes into urban planning, offering benefits beyond climate adaptation, including improvements in environmental quality and human well-being [9].

By incorporating natural elements into the built environment, GI plays a key role in providing ecosystem services, understood as the ecological functions and processes that directly or indirectly support human life and societal development. These services include, among others, regulating hydrological cycles, moderating climate, enhancing urban biodiversity, and improving air and water quality – all of which are fundamental to sustainable urban systems [10].

Moreover, GI implementation is closely aligned with achieving several SDGs. Its multifunctional character contributes not only to goals directly associated with urban sustainability and climate action, such as Sustainable Cities and Communities (SDG 11) and Climate Action (SDG 13), but also to broader objectives related to infrastructure development, ecosystem conservation, public health, social equity, and water security. As such, GI represents a strategic pathway for promoting integrated, resilient, and sustainable urban development across both developed and developing regions [11].

Given the complexity and interdisciplinary nature of GI, engineering education must equip students to analyse, discuss, and develop solutions collaboratively. In this regard, Team-Based Learning (TBL) emerges as an effective pedagogical strategy, particularly in graduate-level engineering courses. Active learning methodologies significantly enhance content comprehension, with TBL featuring among the most widely accepted by students [12].

Recent studies show that competitive and collaborative team-based learning approaches significantly improve students’ engagement, motivation, and retention of core engineering concepts [13]. This methodology also strengthens essential professional skills, particularly teamwork and communication, and has been widely accepted by students as an effective active learning strategy in engineering education [14]. Higher test scores and a consistent reduction in failure rates were observed in mechanics of materials courses when TBL was integrated, compared with traditional lecture-based instruction [15].

Team-based approaches foster a more dynamic and accessible learning experience than individual study, as reflected in student performance assessments. Moreover, the instructor’s role is crucial in facilitating discussions, providing feedback on group work, clarifying doubts, and synthesising key concepts. Each educator is responsible for engaging students to help them develop their full potential and meaningfully contribute to sustainable development. By integrating TBL into GI teaching, students engage in collaborative problem-solving, reinforcing their ability to address real-world engineering challenges while developing essential teamwork and critical thinking skills [16].

Hence, this study reports on the application of TBL as an assessment method in a graduate-level environmental course and evaluates its effectiveness in enhancing student engagement, interdisciplinary collaboration, and understanding of GI concepts. We analyse the impact of TBL on student performance, teamwork dynamics, and the ability to apply theoretical knowledge to practical engineering challenges, contributing to research on active learning methodologies in sustainable engineering education.

Although previous studies have investigated TBL in engineering education, most focus on general learning outcomes or single-course applications, without explicitly linking collaborative learning to complex, interdisciplinary topics like GI. In contrast, the present study advances the literature by applying TBL to the teaching of GI concepts, explicitly addressing their interdisciplinary nature and real-world engineering challenges. Additionally, this work provides empirical evidence from a graduate-level engineering context, thereby extending existing research that has primarily focused on undergraduate or non-environmental engineering courses. Thus, this study not only applies TBL to a sustainability-oriented engineering context but also provides empirical evidence that collaborative assessment enhances understanding of complex environmental systems, reinforcing its relevance to sustainability-focused engineering education.

The article “Green Infrastructure: A Systemic Approach of Urban-Rural Integration” [21] was selected to identify general guidelines for implementing urban GI to maximise its social and environmental benefits. Based on a literature review of the relevant concepts, the study examines the plan developed for Barcelona, which is considered an exemplary case of this emerging paradigm [21]. The material was selected for its comprehensive coverage of fundamental concepts related to the topic and for its application of a case study that can be replicated across different contexts.

The class consisted of ten students with diverse academic backgrounds, including architecture, environmental engineering, civil engineering, and law. To implement TBL, students were randomly divided into two groups of five members each. One week before the activity, they were informed that an active learning methodology would be used, but no specific details about its operation were provided. During this time, they were instructed to read the selected article in preparation for the activity.

At the beginning of the class, the PhD student responsible for the activity introduced himself to the group and explained the first stage of the process. Students had 45 minutes to complete a 10-question multiple-choice questionnaire individually, with each question containing four answer choices, each assigned a weight of 0–4, according to the method’s principles.

Next, teams were randomly formed using the official class attendance list, with students divided into even- and odd-numbered groups. For another 45 minutes, the groups discussed their answers and collaborated to determine the correct alternatives. Finally, an additional 20-minute period was allocated for appeals, allowing teams to challenge and respond to key responses when disagreements arose.

The final implementation stage involved providing students with access to a “Class Evaluation Form (CEF)” via QR Code. This instrument was initially developed by [22] and later adapted by [23], as shown in Table 1.

Students’ answers to the CEF in each pedagogical intervention enable a comparative analysis of different lessons within the same course and an evaluation of student perceptions across various engineering disciplines and fields. This process helps identify strengths and challenges in implementing active learning methodologies, contributing to the continuous improvement of educational practices.

Learning outcomes were operationalised through a structured two-phase assessment using the same evaluative instrument, namely a 10-question multiple-choice questionnaire based on the text “Green Infrastructure: A Systemic Approach of Urban-Rural Integration” [21]. Each question presented four alternative answers, with only one correct option.

In Phase 1 (individual assessment), students completed the questionnaire independently, without discussion, serving as a baseline measure of individual comprehension. In Phase 2 (team-based assessment), students revisited the same questionnaire in structured teams, engaging in discussion and collective decision-making before submitting a unified group response. Each correct answer was worth 4 points, with 10 being the maximum. Scores were converted into percentages to allow comparison between individual and team performance.

To evaluate whether collaborative discussion significantly improved learning outcomes, a two-tailed paired t-test was used at α = 0.05 to compare individual and team scores within the same cohort. In addition to quantitative performance measures, qualitative data were collected using the Class Evaluation Form (CEF), which employed a 10-point Likert-type scale to assess students’ perceptions of engagement, understanding of Green Infrastructure concepts, and collaborative dynamics. Descriptive statistics (mean value and standard deviation) were calculated for each item.

Quantitative and qualitative indicators were analysed independently without weighting, as they were designed to capture complementary dimensions of learning performance (objective achievement) and learning perception (subjective experience). Explicit descriptions of the evaluation instrument, scoring procedure, and statistical analysis enhance methodological transparency and enable replication in similar graduate-level sustainability-oriented engineering contexts.

Table 2 presents the mean scores for the two phases of the TBL process, indicating that the average student scores were significantly higher in the group evaluation than in the individual assessment.

Additionally, variability analysis shows that the standard deviation of individual scores (4.93) is higher than that of team scores (4.13), suggesting a more homogeneous distribution of learning among participants.

In total, ten students completed both assessment phases. The mean individual score was 20.0 ± 4.93, corresponding to 50% of the maximum possible score (40 points). After a structured team discussion, the mean team score increased to 32.5 ± 4.13, corresponding to 65% of the maximum score. According to the two-tailed paired t-test, the difference between individual and team performance was statistically significant (t = –5.4211, p = 0.0004, α = 0.05), indicating that collaborative discussion contributed to measurable improvement in learning outcomes.

The fact that TBL assessment emphasises team-based learning and fosters student discussion is a key factor in meaningful learning, as evinced by the significantly lower number of correct answers in the questionnaire when completed individually compared to when completed in teams. Moreover, results showed that the highest individual performance (27.0) was exceeded by both teams’ performances (29.0 and 36.0). These findings highlight the importance of peer learning, as the TBL methodology aligns with the ‘peer-to-peer’ teaching approach, which, according to [24], promotes the development of communication and interpersonal skills, responsibility, self-confidence, and student collaboration.

On average, students improved their scores by 12.5 points after team discussion, representing a relative increase of 62.5%. This gain suggests that peer interaction and collective reasoning contributed to deeper conceptual understanding of GI topics.

Out-of-class preparation and student engagement in constructing knowledge through the TBL methodology highlight learners’ active role in their learning process. According to [25], student protagonism extends beyond classroom participation, playing a key role in knowledge formation and consolidation. By fostering this autonomy, TBL contributes to a comprehensive education, enabling students to develop intellectual independence and reinterpret theoretical content meaningfully.

As an active learning methodology, TBL promotes meaningful learning in which students play a central role in the educational process. For this approach to be practical, individual preparation is essential, including the assigned reading and prior research, which are key steps for the strategy’s success [26].

CEF application provided valuable insights into students’ perceptions of their learning experience, engagement, and the overall TBL effectiveness. The results, summarised in Table 3, indicate a positive evaluation of the TBL approach, with high average scores across all questions and relatively low variability in most responses.

Upon arriving in class (Q1: 7.0 ± 3.1), the student’s state of mind showed the highest variability, suggesting that initial expectations and mood differed significantly among participants. This result may indicate that some students arrive motivated and prepared, while others may have felt uncertain about the methodology or the topic. However, after participating in the session, their self-reported experience during class (Q2: 8.9 ± 2.6) showed a considerable increase with reduced variability, indicating that the session positively influenced students’ engagement and comfort in the learning environment.

The topic’s perceived relevance (Q3: 9.4 ± 0.8) received one of the highest ratings, with a low standard deviation, indicating strong consensus among students on the importance of GI as an educational subject. Similarly, the effort students perceived in their participation (Q4: 8.6 ± 1.3) was also high, reflecting active engagement in the methodology. The slightly higher variability in this response suggests that while most students felt actively involved, some may have encountered challenges in fully participating.

The learning outcome assessment (Q5: 8.2 ± 1.5) indicates that students generally felt they had learned effectively, though there was some individual variation that could be attributed to differences in prior knowledge, engagement levels, or learning preferences. The relatively low standard deviation of this response indicates that the TBL session consistently contributed to student learning.

The instructor’s role (Q6: 9.6 ± 0.8) was highly rated, reflecting strong facilitation, clear instruction, and practical guidance throughout the session. This result aligns with the existing literature, which emphasises instructor engagement in active learning methodologies. Additionally, the class’s contribution to personal and professional development (Q7: 9.8 ± 0.6) received the highest rating with the lowest variability, reinforcing that the team-based nature of the activity fostered collaboration, knowledge exchange, and an enriched learning environment.

These findings indicate that the TBL methodology was highly effective in engaging students, reinforcing key concepts, and creating an interactive learning environment. The relatively low standard deviations in most responses suggest a consistent learning experience among participants. Increased engagement and perceived learning outcomes further highlight the effectiveness of active learning methodologies in engineering education, mainly when applied to interdisciplinary topics such as GI.

The results also emphasise the instructor’s key role in facilitating learning and guiding discussions, as well as the importance of peer interaction in enhancing students’ understanding. Future implementations of TBL in similar contexts could further explore additional preparatory strategies to minimise variability in initial engagement levels (Q1) and ensure even more consistent learning experiences across participants.

Qualitative feedback collected through the CEF also indicated an evolution in students’ perceptions of collaborative learning. Several students reported that while individual work initially felt more comfortable, team discussions helped them reconsider assumptions, clarify misunderstandings, and build confidence in applying GI concepts. This transition from individual reasoning to collective problem-solving was frequently highlighted as a key learning experience.

Despite the overall positive outcomes of the TBL activity, students also faced challenges common to collaborative learning environments. Some participants reported initial difficulties with task delegation and balancing individual contributions within teams. Differences in academic background and prior familiarity with GI concepts occasionally led to uneven participation during early discussions. However, as the activity progressed, the instructor’s guided facilitation and structured discussion phases helped mitigate these challenges, fostering more equitable engagement and shared responsibility among team members.