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Article

Sustainability Education in Geomatics Students: Nature of STEM Through Meteorology and Ecology of Fire

by
Víctor Martínez-Martínez
1,*,
Jairo Ortiz-Revilla
1,
Almendra Brasca Merlin
2,
Mariela Sammaritano
2,
Rodrigo Molina
2,
Matías López
2 and
Ileana María Greca
1
1
Faculty of Education, University of Burgos, 09001 Burgos, Spain
2
Mario Gulich Institute, University of Córodoba, Falda del Cañete 400000, Argentina
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(24), 11208; https://doi.org/10.3390/su162411208
Submission received: 12 November 2024 / Revised: 16 December 2024 / Accepted: 17 December 2024 / Published: 20 December 2024
(This article belongs to the Section Sustainable Education and Approaches)
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Abstract

:
To address the urgent challenges of sustainability in our changing world, STEM education must evolve to integrate a stronger focus on socioenvironmental dimensions. This study examines how students in geomatics courses understand the nature of STEM (NoSTEM) in the context of meteorology and fire ecology—fields closely tied to sustainability. Using two validated mixed-method instruments comprising closed- and open-ended items, we assessed students’ comprehension across cognitive–epistemic and socio-institutional dimensions, framed within the family resemblance approach (FRA). Data collected from 44 students in meteorology and 57 in fire ecology were analyzed using descriptive statistics and phenomenographic methods. Our findings indicate that, while students demonstrate a stronger grasp of technical concepts, their understanding of socio-institutional implications is comparatively limited. These results highlight the need to align STEM education with sustainability education, emphasizing real-world applications and the integration of socio-institutional elements into the curriculum. Addressing these gaps is essential for preparing students to engage with complex sustainability challenges, such as those posed by climate change, resource management, and disaster mitigation. Future research should investigate long-term interdisciplinary educational strategies to foster a holistic understanding of NoSTEM and its role in promoting sustainable development.

1. Introduction

In today’s interconnected world, humanity is confronted with a web of challenges that defy disciplinary boundaries. From the escalating climate crisis, which risks causing irreversible damage to the planet’s ecosystems, to enduring social inequalities, these problems are both intricate and pressing [1]. Addressing their interdependence necessitates an integrated and systemic approach that moves beyond fragmented and isolated solutions, which often fail to grasp the complexity of their ramifications. The United Nations’ sustainable development goals (SDGs), adopted in 2015, exemplify an effort to craft holistic strategies for tackling global challenges [2]. These goals, encompassing objectives like eradicating poverty and combating climate change, emphasize the interconnectedness of human and environmental dimensions, recognizing the necessity of addressing problems collectively [3]. The successful realization of the SDGs hinges not only on sound global policies but also on robust educational approaches that empower future generations to comprehend these complexities and devise sustainable solutions [4].
In the context of Latin America, educational disparities and systemic inequities hinder the development of the competencies necessary to address sustainability challenges effectively [5]. These inequalities manifest in the varied educational pathways of students, particularly in STEM fields (science, technology, engineering, and mathematics). Providing adequate STEM education is crucial to equipping students with the skills required to confront contemporary challenges, as it nurtures their capacity to engage with problems in a more integrated and multidimensional manner [6]. By emphasizing science, technology, engineering, and mathematics, STEM education lays the groundwork for devising technical solutions to complex issues, ultimately driving economic, social, and technological progress across the region [7,8].
In this context, geomatics emerges as a key discipline, especially relevant to the SDGs. Geomatics combines remote sensing, photogrammetry, geographic information systems (GISs), geodesy, and related sciences to capture, store, analyze, and disseminate georeferenced data. These tools allow for a deeper understanding of the complex problems facing our world, from natural resource management to the monitoring of disasters [9]. The use of geospatial technologies, such as GISs, satellite remote sensing, and global positioning, facilitates the geolocation and measurement of fire hotspots, damage assessment, and the planning of ecosystem restoration, among others [10,11]. By providing a multiscale view, geomatics facilitates the sustainable management of natural resources and aligns directly with the SDGs, as it enables the evaluation and response to challenges such as climate change and environmental degradation [12,13].
In this sense, the nature of STEM (NoSTEM) emphasizes, as a theoretical framework, the need to transcend traditional disciplinary boundaries by integrating scientific and technical knowledge with insights from the humanities. We believe this approach is particularly useful in the context of sustainability education, where addressing complex global challenges requires a comprehensive understanding of both the natural world and the societal structures that shape it [14]. Aligning scientific and social disciplines with humanistic perspectives fosters critical thinking and ethical reasoning, equipping students with the ability to evaluate the broader implications of their actions. For instance, understanding the historical evolution of environmental policies or the philosophical foundation of sustainability enables students to make informed decisions that consider technical feasibility, social justice, cultural values, and ethical responsibility [15,16]. By bridging these domains, NoSTEM provides a holistic framework that prepares learners to engage with the interconnected realities of the 21st century, empowering them to develop innovative, sustainable solutions grounded in an interdisciplinary perspective.
In addition to its technical aspects, geomatics demands a profound understanding of NoSTEM, which extends beyond technical expertise to encompass the ethical and social implications of technology use and the interconnectedness of various disciplines [17]. This comprehensive understanding is crucial for geomatics students, as it empowers them to apply their knowledge effectively in areas such as disaster management, territorial planning, and environmental monitoring. NoSTEM underscores the importance of situating science within its broader social and ethical context, which is essential for devising sustainable solutions that are responsive to the specific needs of communities. [18,19,20]. To effectively measure NoSTEM, the family resemblance approach (FRA) has been employed to create and validate instruments capable of assessing students’ understanding of STEM concepts in a comprehensive and multidimensional way. The FRA provides a structured framework for evaluating both cognitive–epistemic and socio-institutional dimensions, ensuring that assessments reflect the complexity of NoSTEM within real-world contexts [21,22]. Through the FRA, researchers can gain deeper insights into how students connect scientific knowledge to societal challenges, an understanding that is critical for designing educational interventions aimed at fostering holistic STEM literacy.
Addressing contemporary challenges requires geomatics students and professionals to cultivate critical thinking, problem-solving, and collaboration skills—core components of the NoSTEM approach [14]. These skills not only enable the effective use of advanced technological tools but also encourage a broader understanding of the societal and environmental impacts of their decisions. Consequently, STEM education must extend beyond technical proficiency to incorporate an understanding of the social, economic, and environmental dimensions of geospatial technologies [23]. This holistic preparation is indispensable for developing robust decision-making skills, which are crucial for geomatics students as they navigate the interconnected challenges of sustainability.
Integrating sustainability as a central objective within STEM education necessitates a paradigm shift from purely technical training to a more holistic approach that encompasses cognitive–epistemic and socio-institutional dimensions as FRA assets. This alignment with the SDGs—particularly SDG 4 (quality education) and SDG 13 (climate action)—underscores the importance of fostering interdisciplinary competencies that enable students to engage with complex, interdependent global challenges. By examining the intersections between geomatics, meteorology, and fire ecology, this research illustrates how an understanding of NoSTEM fosters the development of the critical skills necessary for addressing sustainability challenges. For example, interpreting uncertainty in meteorological forecasts or understanding the socioenvironmental consequences of forest fires requires technical expertise and the ability to apply knowledge within complex societal contexts. Integrating NoSTEM into sustainability-focused curricula prepares students to tackle multifaceted problems and empowers them to act as agents of change in professional and societal roles. In professional practice, geomatics practitioners are often tasked with making informed, responsible decisions that affect human and environmental systems [24]. These decisions demand technical precision and an awareness of their broader societal impacts and ethical considerations. This is particularly significant in contexts where resource management, urban planning, and disaster prevention intersect with public interests and ecological sustainability [25,26]. Such an integrated approach ensures that geomatics professionals are well equipped to contribute meaningfully to sustainable development and address pressing global challenges.
In Latin America, this multidimensional approach holds relevance due to persistent limitations in access to and quality of geomatics education. These constraints risk undermining students’ preparation to address sustainability challenges comprehensively. Without adequate training that integrates both cognitive–epistemic and socio-institutional competencies, future professionals may lack the critical skills needed to evaluate diverse perspectives, consider the long-term impacts of their decisions, and collaborate effectively with stakeholders across sectors. Consequently, including social, economic, and environmental considerations within geomatics curricula is beneficial and essential for cultivating reflective decision makers capable of contributing meaningfully to sustainable development in the region. A robust understanding of the NoSTEM equips students with the technical proficiency and contextualized, holistic perspective necessary to navigate the complex challenges of the 21st century. This integrated STEM vision empowers future professionals to tackle field-specific problems while significantly contributing to the SDGs and fostering global impact. By aligning geomatics education with the principles of sustainability and the SDGs, students gain knowledge that is both interdisciplinary and action-oriented, enabling them to create meaningful change within their communities and beyond [27,28].
This study explores how geomatics students comprehend NoSTEM concepts within the specific contexts of meteorology and fire ecology—two critical domains that intersect environmental phenomena and socioenvironmental decision making. Understanding these areas is vital for future professionals tasked with addressing such challenges as climate change, natural resource management, and disaster prevention. The study also examines differences in students’ levels of understanding across cognitive–epistemic and socio-institutional dimensions. Insights from this research will inform the design of future educational interventions in NoSTEM, fostering a more comprehensive, sustainability-focused, and decision-oriented STEM education framework.
This study tries to contribute to a better understanding of sustainability education within STEM fields by focusing on the specific context of geomatics. By exploring students’ comprehension of the NoSTEM concepts in meteorology and fire ecology—two areas directly linked to socioenvironmental challenges—this research sheds light on potential gaps in their knowledge. The analysis of cognitive–epistemic and socio-institutional dimensions suggests the importance of integrating these aspects more deeply into STEM curricula. Furthermore, the findings aim to inform the design of interdisciplinary and context-based educational strategies aligned with sustainability principles and the SDGs. These insights could support efforts to foster critical thinking, ethical decision making, and more comprehensive problem-solving skills among future geomatics professionals.

2. Materials and Methods

2.1. Method

Both types of items were analyzed according to their nature. The closed items were examined using the IBM statistical software SPSS 29.2, which facilitated the calculation of descriptive statistics. Additionally, an inferential analysis was conducted to explore potential relationships and differences between groups, providing a deeper understanding of the data. This quantitative analysis offered a structured overview of the participants’ performance in the closed-ended items, enabling the identification of general trends and significant patterns in their understanding of NoSTEM concepts. Within the closed items, participants could choose from multiple options, each of which was assigned a specific score: 2 points for fully correct responses, 1 point for partially correct responses (where applicable), and 0 points for incorrect answers or “I don’t know” responses. This scoring system provided a nuanced assessment of the participants’ understanding, allowing for the identification of varying levels of knowledge and partial comprehension within the closed-ended items.
For the open-ended items, a qualitative analysis was conducted using phenomenographic principles to identify varying levels of student understanding. The open-ended responses were categorized and interpreted through an independent process carried out by two of the authors. This analysis focused on understanding student conceptions in the areas of meteorology (MO1 and MO2) and fire ecology (FO1 and FO2). Specifically, FO1 was designed to assess the role of statistics in understanding and predicting fire behavior, while FO2 examined the importance of communication and public awareness in fire prevention. In meteorology, MO1 explored the use of models in studying meteorological phenomena, and MO2 investigated the application of scientific data in political decision-making processes. Following the independent categorization, a discussion was conducted to reach a consensus on the final set of categories. This step was essential for ensuring the reliability and consistency of the qualitative analysis, as it resolved discrepancies and confirmed the coherence of the findings. The consensus-building process applied rigorous criteria to maintain clarity and uniformity in defining the levels of understanding, thereby strengthening the robustness of the analysis.
The phenomenographic analysis included comprehension levels ranging from 0 to 3, assigned based on the depth and accuracy of the responses provided. For instance, in the meteorology section, MO1, which explored the use of models in studying meteorological phenomena, could elicit responses at different levels. A response at Level 0 might simply state that models are used to predict the weather without further elaboration. A Level 1 response could recognize that models use past and current data but lack an understanding of the complexities involved. A Level 2 response might describe how models incorporate various data points, such as temperature and pressure, to make predictions, showing a more developed understanding. Finally, a Level 3 response would detail how meteorological models are not only data-driven but also subject to limitations and uncertainties, demonstrating a comprehensive grasp of their use and challenges.
In the fire ecology section, FO1, which assessed the role of statistics in understanding and predicting fire behavior, responses were similarly categorized. A Level 0 response might not mention the use of statistics at all, indicating no understanding. A Level 1 response could note that statistical data are sometimes used in fire prevention but without explaining their significance. A Level 2 response might highlight that statistical analyses help predict fire risk based on variables such as humidity and wind speed. A Level 3 response would demonstrate an in-depth understanding by explaining how complex statistical models integrate multiple environmental factors and historical fire data to accurately predict and manage fire behavior. This categorization approach ensured that the levels of understanding captured varied degrees of knowledge and insight, allowing for a detailed analysis of the students’ conceptual grasp of NoSTEM topics in both meteorology and fire ecology.
This methodological approach allowed for a comprehensive examination of students’ conceptions, capturing the variability in their responses and providing valuable insights into their understanding of NoSTEM concepts within the contexts of meteorology and fire ecology. The detailed analysis not only identified distinct levels of comprehension but also highlighted potential areas for improving educational strategies to foster more effective learning.

2.2. Population

Data collection was conducted virtually through Google Forms, facilitating remote participation and ensuring broader student access. The study lasted two months, from 12 October to 10 December 2022.
The instruments were administered only once, prior to the start of the different courses in which the participants were enrolled, with the aim of assessing their prior conceptions of NoSTEM. From the different courses, two comparable groups were formed. A total of 44 (23 men, 19 women, and a nonbinary person) students participated in the meteorology assessment, while 57 (27 men, 29 women, and a nonbinary person) students took part in the fire ecology assessment. Participants were drawn from students enrolled in various geomatics courses at an Argentine higher education institution, such as “Geostationary satellites and their application to hydrometeorology”, “Geomatics tools applied to territorial planning”, “Spatial ecology”, and “Geomatics tools applied to agricultural production” among others, representing diverse educational backgrounds.
The meteorology study’s population sample included 44 participants, divided based on their academic background and field of study. When categorized by field of study, 26 participants came from Natural and Exact Sciences, 9 from Engineering and Architecture, 7 from Social Sciences and Law, and 2 from Arts and Humanities. In terms of academic background, 27 participants were either pursuing or had completed an undergraduate degree, 10 were engaged in a master’s or postgraduate program, and 7 had reached or completed the doctoral level. The population sample for the fire ecology study consisted of 57 participants, categorized by their fields of study and academic backgrounds. By field of study, the distribution was as follows: 10 participants from Social Sciences and Law, 28 from Natural and Exact Sciences, 15 from Engineering and Architecture, and 6 from Arts and Humanities. Regarding academic background, 16 participants were enrolled in or had completed a master’s or postgraduate program, 34 had an undergraduate degree, 10 were pursuing or had completed a doctorate, and there was one participant with a vocational training level. A population scheme can be consulted in Figure 1. Ethical approval for the study was obtained from the Ethics Committee of the University of Burgos, authorizing all research activities associated with the project. Informed consent was obtained from all participants prior to their involvement.

3. Results

The results are presented based on the analysis of closed- and open-ended items, evaluating students’ understanding in the domains of meteorology and fire ecology. Descriptive statistics and a phenomenographic analysis were employed to identify comprehension levels and significant differences in knowledge regarding the NoSTEM.

3.1. Closed-Ended Item Analysis

This section presents the findings of the study corresponding to the domains of meteorology and fire ecology (Table 1). Descriptive statistics for these dimensions are provided, as well as comparisons by gender, educational level, and field of study.
The results in the meteorology domain indicate a general understanding of NoSTEM, with a mean score of 1.68 (SD = 0.26). The cognitive–epistemic dimension shows a higher mean (M = 1.79, SD = 0.29) than that of the socio-institutional dimension (M = 1.57, SD = 0.36). Among the closed items, the highest scores were observed in item MC2 (M = 1.93, SD = 0.33), which focuses on the importance of past meteorological data for accurate forecasting and understanding of climate patterns, followed by item MC5, which evaluates the participants’ knowledge of the instruments and technologies used in meteorology, and item MC6, which addresses the understanding and perception of the role of weather forecasts in society. The lowest scores were found in item MC1, which deals with the processes and scientific practices involved in the preparation of meteorological forecasts, followed by item MC4, which assesses the participants’ understanding of research conducted in meteorology, item MC3, which explores the value and reliability of information provided by meteorological services, and item MC7, which investigates the role and capabilities of advanced computational technology in meteorological modeling and prediction. When comparing results by gender, male participants scored slightly higher than female participants in both dimensions. Specifically, males achieved a mean of 1.85 (SD = 0.25) in the cognitive–epistemic dimension and 1.66 (SD = 0.33) in the socio-institutional dimension, while females scored 1.75 (SD = 0.33) and 1.51 (SD = 0.39), respectively. The results also revealed differences based on the participants’ educational levels. Students with university degrees or postgraduate education scored higher in both dimensions than those with vocational training. For example, master’s students had a mean of 1.92 (SD = 0.17) in the cognitive–epistemic dimension, while vocational training students scored 0.86.
In the fire ecology domain, the overall mean score was 1.45 (SD = 0.28). As in meteorology, the cognitive–epistemic dimension had a higher mean (M = 1.51, SD = 0.27) than the socio-institutional dimension (M = 1.35, SD = 0.49). The highest scores were achieved in item FC7, which focuses on the application of scientific practices, and item FC2, which explores the aims and values guiding fire studies, specifically the perspective from which forest fires are analyzed. The lowest scores were found in item FC4, which relates to the scientific ethos and examines the ethical implications of maintaining secrecy around research findings due to competition among scientific groups, and item FC5, which assesses the applicability of scientific knowledge by questioning whether fire data from one climatic zone can be effectively applied to different zones.
Gender-based comparisons revealed that male participants again scored higher in both dimensions: 1.60 (SD = 0.23) in the cognitive–epistemic dimension and 1.54 (SD = 0.44) in the socio-institutional dimension. In contrast, female participants scored 1.43 (SD = 0.28) and 1.18 (SD = 0.48), respectively. The results by educational level show that higher levels of education correspond to better performance. Doctoral students scored the highest, with a mean of 1.66 (SD = 0.26) in the cognitive–epistemic dimension, while vocational training students scored 1.43 (SD = 0.40).
An additional inferential analysis was conducted to further explore group differences and the overall understanding of NoSTEM concepts. The Kolmogorov–Smirnov test was used to assess the normality of the data distribution, and in all cases, the results indicated a violation of the normality assumption (p-value < 0.05). Consequently, nonparametric tests were applied: the Mann–Whitney U test was used to compare gender differences (Table 2), and the Kruskal–Wallis H test was employed to evaluate differences by educational level and field of study (Table 3).
In the fire ecology domain, the Mann–Whitney U test revealed significant gender differences in the cognitive–epistemic dimension (U = 258.500, p = 0.017), the sociopolitical dimension (U = 235.500, p = 0.005), and overall understanding (U = 197.500, p < 0.001). However, the Kruskal–Wallis H test did not show significant differences in any of the dimensions when considering educational level or field of study (p > 0.05).
In the meteorology domain, the Mann–Whitney U test did not reveal significant gender differences in any of the evaluated dimensions (p > 0.05). Similarly, the Kruskal–Wallis H test indicated no significant differences across all dimensions when comparing by educational level or field of study (p > 0.05).

3.2. Open-Ended Item Analysis

The phenomenographic analysis of the open-ended items was conducted with the aim of identifying the different levels of student understanding in the areas of meteorology (MO1 and MO2) and fire ecology (FO1 and FO2). We present the categorization of students’ responses based on four levels of understanding (Table 4), ranging from basic recognition of key concepts (Level 0) to a comprehensive and nuanced understanding of the complexities involved (Level 3).
Figure 2 shows graphically the distribution of responses across these levels, highlighting the variability in students’ comprehension within both disciplines. The following analysis will interpret these results, offering insights into the areas where students exhibited strong understanding and where further educational focus is needed.
In the field of meteorology, significant variations were found in the understanding of key concepts, such as the function and limitations of models, the inherent uncertainty in predictions, and the use of historical data in modeling. Most students exhibited an intermediate level of understanding. Regarding the function and limitations of models, a considerable number of students with lower educational backgrounds (e.g., those in vocational training or undergraduate programs) fell into the lower levels (Levels 0 and 1), offering superficial descriptions of the purpose of meteorological models or failing to adequately recognize inherent limitations. This trend aligns with the quantitative data, which showed that students at higher educational levels tended to perform better in NoSTEM assessments. Only a minority reached Level 3, demonstrating a detailed understanding of how models operate based on data and patterns, including the complexity and limitations of input data uncertainty. These students were predominantly from postgraduate programs, consistent with the higher mean scores observed in the cognitive–epistemic dimension of the quantitative analysis. Regarding understanding uncertainty in meteorological models, a progression was observed across different educational levels. At Level 0, students, mainly those at lower academic stages, did not recognize uncertainty as a relevant factor. In contrast, those who reached higher levels (Levels 2 and 3) included students from advanced educational backgrounds who understood the probabilistic nature of predictions and explained how uncertainty is managed to generate scenarios that inform decision making. This pattern is aligned with the statistical analysis. Using data for modeling also revealed disparities in responses linked to educational background. At lower levels, students often did not mention or superficially understood the importance of historical data. However, those who reached Levels 2 and 3, primarily from higher academic tiers, provided detailed explanations of how historical data are essential for refining and improving predictions, underscoring their relevance in calibrating models for more accurate results. This qualitative observation supports the results obtained with the quantitative part of the test, showing that students with more advanced educational experiences demonstrated a more sophisticated understanding of the NoSTEM framework in meteorology.
In fire ecology, concepts related to uncertainty in fire prediction, decision making based on probabilistic models, and the influence of environmental variables, such as humidity and wind, were analyzed. A considerable proportion of responses fell into Level 0, with students, particularly those from lower educational levels (e.g., vocational training or early undergraduate programs), either failing to mention uncertainty or perceiving it as a mere error in models. This pattern is consistent with the quantitative findings, which showed that students with lower academic backgrounds tended to score lower in the cognitive–epistemic and socio-institutional dimensions. A greater number of students demonstrated an intermediate understanding (Levels 1 and 2), acknowledging uncertainty as an inherent part of predictions and describing basic strategies for managing it to mitigate risks. These responses often came from students with more advanced undergraduate or initial postgraduate training, aligning with the quantitative data that indicated better comprehension among students at higher academic levels. Only a small group reached Level 3, providing detailed explanations on managing uncertainty using mathematical models. These students were predominantly those with postgraduate education, reflecting the trend observed in the quantitative analysis, where students with higher educational levels presented greater proficiency in NoSTEM understanding. Decision making based on probabilistic models also exhibited a range of comprehension levels that were tied to the students’ academic backgrounds. Responses at Level 0, which lacked consideration of model-based decisions, were more frequent among students in vocational training or at the beginning of their undergraduate studies. In contrast, students at higher educational levels discussed the application of probabilistic models for preventive strategies and provided detailed examples, such as evacuation planning, thus demonstrating a comprehensive approach at Level 3. Responses related to the influence of environmental variables on fire prediction also varied according to educational background. Students at lower levels often showed complete unawareness of how variables such as humidity and temperature affect fire predictions. In comparison, those at Levels 2 and 3, who were generally at more advanced stages of their education, explained how these variables must be continuously monitored to improve prevention strategies.
This finding is supported by the quantitative analysis, which showed that students with higher academic qualifications performed better at understanding complex NoSTEM concepts. The analysis of responses regarding the importance of communication and proposed preventive actions revealed similar trends. Many students made only vague references to the role of communication, with more detailed and practical examples provided by those at higher academic levels, aligning with the quantitative data showing higher comprehension scores among this group. Additionally, the connection between technology and public awareness was clearly articulated by only a small fraction of students, primarily those with more advanced educational experiences.

4. Discussion

The findings of this study provide a nuanced understanding of how students perceive the NoSTEM within the fields of meteorology and fire ecology. Consistent with prior research [29,30], our results indicate stronger performance in the cognitive–epistemic dimension than in the sociopolitical dimension, suggesting the need for STEM education to emphasize social and institutional contexts. This disparity underscores the importance of balancing technical competencies with social awareness in science education, particularly as these are increasingly recognized as critical for sustainability-focused decision making [31,32].
Inferential analysis revealed significant gender differences in the fire ecology section, where male students outperformed their female counterparts. However, no significant gender differences were observed in the meteorology section. These findings highlight the need to explore the underlying factors contributing to gender disparities and underscore the importance of promoting equitable participation [33,34], in line with SDG 5, which calls for gender equity and inclusivity in education. Encouraging diverse representation and participation in STEM is crucial, as gender-equitable learning environments have been shown to enhance overall academic performance and engagement [35]. Additionally, students with higher academic exposure demonstrated slightly improved comprehension, but the minimal differences between undergraduate and postgraduate levels suggest that curriculum quality and pedagogical approaches play a more critical role than educational level alone. This observation corroborates findings emphasizing the need for curricular approaches that integrate cognitive and epistemic practices into STEM education [36]. Notably, the absence of significant differences between educational levels in socio-institutional dimensions highlights a pervasive gap in current STEM curricula, particularly in addressing the broader social implications of scientific practices [37]. Performance variations by academic background revealed that engineering and natural sciences students outperformed their peers from other fields. Such findings underscore the need to design curricula that effectively bridge disciplinary divides and provide a socio-institutional context for students from nontechnical backgrounds. Integrating sustainability-focused frameworks, such as the GreenComp model [38], into STEM education can help to create a more inclusive and comprehensive learning environment, aligning with the objectives of SDG 4.
In addition to gender and academic background, this study identified varied levels of understanding among students in key areas, such as model-based reasoning, uncertainty management, and data utilization in meteorology and fire ecology. The challenges associated with teaching abstract scientific concepts remain evident. However, some authors have suggested that real-world scenarios, such as climate-related disasters or ecological crises, can significantly enhance students’ comprehension of these complex concepts [39,40]. Our findings support this view, as students showed better understanding when tasked with contextualized problem-solving exercises.
The inferential analysis reinforced these observations, revealing no significant differences based on field of study or educational level. This finding highlights the universal need to strengthen NoSTEM education across all dimensions, regardless of prior academic exposure. Integrating socio-institutional elements into STEM education is essential not only for fostering technical expertise, but also for preparing students to address the interdependent challenges of sustainability [41,42]. Embedding sustainability-related competencies into STEM curricula can empower students to become informed decision makers who contribute meaningfully to global efforts in sustainability and resilience.

5. Conclusions

This study underscores the critical need for a more integrated approach in STEM education, one that balances cognitive–epistemic and socio-institutional dimensions [6,17]. While students generally demonstrated a better grasp of technical concepts, their limited understanding of socio-institutional implications highlights an area for significant improvement. Addressing this gap is essential, particularly in fields like geomatics, where socioenvironmental considerations are vital for sustainable decision making. The findings also emphasize the importance of refining educational strategies. Implementing long-term, context-based learning interventions that use real-world scenarios can make abstract concepts more tangible and relevant. The analysis revealed no significant differences based on educational level or field of study, underscoring the necessity of strengthening NoSTEM education across all dimensions, irrespective of students’ academic backgrounds. This finding aligns with the existing literature on STEM education and emphasizes the importance of promoting gender equity to address observed disparities. Additionally, it highlights that factors beyond academic attainment, such as the quality of the curriculum and pedagogical strategies, play a critical role in shaping students’ understanding [43,44]. The absence of significant differences between educational levels and fields of study underscores the need for instructional strategies that bridge diverse academic experiences and foster a comprehensive understanding of NoSTEM concepts. Such an approach ensures that students, regardless of prior training, are equipped with the cognitive–epistemic and socio-institutional competencies needed to address complex sustainability challenges effectively. This integration can help future geomatics professionals develop not only technical skills but also an acute awareness of the broader social and environmental implications of their work [45,46].
The participants in this study represent a group with a strong interest in geomatics, having voluntarily chosen this field of study. Despite their advanced educational backgrounds, the research identified a low level of understanding of core NoSTEM ideas in fire ecology and meteorology, which underscores the urgency of addressing these issues at earlier mandatory educational levels. This is vital for developing responsible citizens who can make informed decisions in the face of increasingly complex challenges. Climate-related events, such as the recent cut-off low disaster in Valencia (Spain), further highlight the importance of fostering strong decision-making skills in STEM fields. While early meteorological warnings were issued, the resulting human and material losses underscore the multidimensional nature of decision making in such scenarios, involving political responses, societal preparedness, and awareness. This example reflects the need for education systems that equip citizens, policymakers, and professionals with technical expertise and a comprehensive understanding of the socioenvironmental impacts of their decisions. In this context, the principles outlined in the Sendai framework for disaster risk reduction are particularly relevant as they emphasize understanding risk, fostering resilience, and making informed, proactive decisions to minimize disaster impacts [47,48]. Additionally, frameworks like GreenComp, which emphasize sustainability-related competencies, offer valuable guidance for embedding sustainability education within STEM curricula [49]. Evaluating students’ abilities to think critically, understand complex systems, and act ethically and sustainably at all educational levels could drive meaningful improvements in NoSTEM education. Such a focus goes beyond the foundational goals of civic education to prepare individuals who will generate reports and make decisions with far-reaching socioenvironmental implications. In scenarios like the disaster in Valencia, where timely and informed decisions could have mitigated severe losses, the necessity of comprehensive STEM education becomes particularly evident [50].
Future research should prioritize educational interventions that incorporate interactive and technology-enhanced tools, interdisciplinary collaboration, and experiential learning methods to enrich student understanding. Additionally, exploring the integration of sustainability competencies into STEM curricula could enhance students’ readiness to address real-world environmental challenges. However, it is important to note that this study’s findings are rooted in a specific geographic region and focus on a particular academic field, which may limit their generalizability to broader contexts. Future research should consider extending these approaches to diverse educational settings and disciplines to examine how the integration of NoSTEM concepts can be adapted and applied in varied socioenvironmental and cultural contexts. By embedding sustainability-focused frameworks into STEM education, we can better prepare professionals to contribute meaningfully to sustainable development and to address the global challenges outlined in the SDGs.

Author Contributions

Conceptualization, I.M.G.; methodology, V.M.-M.; software, V.M.-M., J.O.-R.; validation, V.M.-M. and J.O.-R.; formal analysis, V.M.-M. and J.O.-R.; investigation, V.M.-M. and J.O.-R.; resources, A.B.M. and I.M.G.; data curation, A.B.M., M.S., R.M. and M.L.; writing—original draft preparation, A.B.M., M.S., R.M. and M.L.; writing—review and editing, I.M.G.; visualization, V.M.-M.; supervision, I.M.G.; project administration, I.M.G.; funding acquisition, I.M.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Research Agency under the Ministry of Science and Innovation of the Government of Spain through the project “The Nature of i-STEM (NoSTEM) for citizen education”. PID2020-118010RB-I00.

Institutional Review Board Statement

Ethical approval for the study was obtained from the Ethics Committee of the University of Burgos, authorizing all research activities associated with the project. Informed consent was obtained from all participants prior to their involvement.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author(s).

Acknowledgments

Our hearts remain with the victims of the recent DANA disaster in Valencia. We extend our deepest sympathies to those affected and to the families who have experienced loss and hardship. This study is dedicated to emphasizing the importance of education and informed decision making in preventing and mitigating the impacts of such devastating events.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Table A1. This table shows the relationship between the closed items. Each one appears with its statement; note that some are formulated as questions and others as phrases to be completed, both using the available options in the item.
Table A1. This table shows the relationship between the closed items. Each one appears with its statement; note that some are formulated as questions and others as phrases to be completed, both using the available options in the item.
ThemeClose-Ended ItemsFRA DimensionStatement
MeteorologyMC1Scientific practicesAbout the preparation of forecasts…
MC2Scientific practicesAbout the importance of past meteorological data…
MC3Aims and valuesThe information provided by meteorological services…
MC4Aims and valuesAbout research in meteorology…
MC5Scientific knowledgeAbout the instruments used in meteorology…
MC6Scientific practicesThe weather forecasts…
MC7Scientific practicesImagine the best computer in history…
MC8Financial systemsInvestments in meteorological forecasting…
MC9Professional activitiesScientists who research and carry out their professional activities in meteorology…
MC10Social values of scienceWhat happens with the predictions of when extreme meteorological phenomena will occur?
MC11Social disseminationPublications in specialized journals by scientists researching meteorology…
MC12Social values of scienceMeteorological studies…
MC13Scientific ethosScientists who study meteorological phenomena…
Fire ecologyFC1Scientific practicesCan predictions about fires be made by studying the conditions of fire?
FC2Aims and valuesFrom what perspective are forest fires studied?
FC3MethodologyCan a fire be studied while it is occurring? Or, due to its danger, must one wait until it is extinguished?
FC4Scientific ethosSometimes the scientific findings of a research group are kept secret until their publication because of competition between scientific groups; what is your opinion on this?
FC5Scientific knowledgeCan fire data from one climatic zone be applied to a different zone?
FC6MethodologyDo you think computer simulations play an important role in fire research?
FC7Scientific practicesIn terms of fires, can decisions be made based on scientific criteria, even if we don’t have 100% certainty?
FC8Social institutionsWhat is the collaborative relationship between companies, universities, and institutions regarding fires?
FC9Social values of scienceWhen finding solutions to fires, should the environment be protected at all costs without being influenced by social or economic factors?
FC10Political structuresA significant portion of the land that burns is privately owned; what should the Government do about it?
FC11Social values of scienceHow does the abandonment of rural populations affect forest fires?

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Sustainability 16 11208 g001
Figure 1. Population distribution scheme for this study. The population assessed with the meteorology instrument is represented in shades of blue, while the fire ecology population is depicted in shades of red. The diagram progresses from inner to outer circles: total population, gender distribution, academic level, and field of study. Created by the author V.M.M.
Figure 1. Population distribution scheme for this study. The population assessed with the meteorology instrument is represented in shades of blue, while the fire ecology population is depicted in shades of red. The diagram progresses from inner to outer circles: total population, gender distribution, academic level, and field of study. Created by the author V.M.M.
Sustainability 16 11208 g001
Sustainability 16 11208 g002
Figure 2. Bar chart representation of the information included in Table 4.
Figure 2. Bar chart representation of the information included in Table 4.
Sustainability 16 11208 g002
Table 1. Relation between closed-ended items and FRA dimensions. For a better understanding of these items, Appendix A can be consulted.
Table 1. Relation between closed-ended items and FRA dimensions. For a better understanding of these items, Appendix A can be consulted.
Test StatisticsMeteorologyFire Ecology
CEDSPDNoSTEMCEDSPDNoSTEM
Mean score1.791.571.681.511.351.45
SD0.290.360.260.270.490.28
Table 2. Statistical results of the Mann–Whitney U test in the gender comparison for the cognitive–epistemic dimension (CED), the sociopolitical dimension (SPD), and overall NoSTEM.
Table 2. Statistical results of the Mann–Whitney U test in the gender comparison for the cognitive–epistemic dimension (CED), the sociopolitical dimension (SPD), and overall NoSTEM.
Test Statistics
Gender		MeteorologyFire Ecology
CEDSPDNoSTEMCEDSPDNoSTEM
Mann–Whitney U201.000186.000173.000258.500235.500197.500
Wilcoxon W501.000486.000473.000723.500700.500662.500
Z−1.008−1.329−1.600−2.381−2.824−3.343
Asin. Sig (b)0.3130.1840.1100.0170.005<0.001
Table 3. Statistical results of the Kruskal–Wallis H test in the field study and educational level comparison for the cognitive–epistemic dimension (CED), the sociopolitical dimension (SPD), and overall NoSTEM.
Table 3. Statistical results of the Kruskal–Wallis H test in the field study and educational level comparison for the cognitive–epistemic dimension (CED), the sociopolitical dimension (SPD), and overall NoSTEM.
Grouping VariableTest StatisticsMeteorologyFire Ecology
CEDSPDNoSTEMCEDSPDNoSTEM
Study fieldKruskal–Wallis H5.7673.6123.5382.9503.4002.973
FD333333
Asin. sig0.1240.3070.3160.3990.3340.396
Education levelKruskal–Wallis H2.5921.0962.4373.8200.3151.457
FD333333
Asin. sig0.4590.7780.4870.2820.9570.692
Table 4. Results of the phenomenographic analysis. The number of individuals who responded with the indicated level of understanding is represented.
Table 4. Results of the phenomenographic analysis. The number of individuals who responded with the indicated level of understanding is represented.
ItemCategoryLevel 0Level 1Level 2Level 3
MO1
a.
Function and limitations of models
181084
b.
Model uncertainty
21975
c.
Use of data in modeling
191163
MO2
a.
Uncertainty in meteorology
1512161
b.
Forecast-based decision
146204
c.
Value of meteorological forecast
191492
FO1
a.
Uncertainty in fire prediction
1610108
b.
Decision-making based on statistics
1914126
c.
Influence of variables
1012126
FO2
a.
Importance of communication
2710911
b.
Specific preventive actions
285915
c.
Relationship between technology and awareness
37983
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Martínez-Martínez, V.; Ortiz-Revilla, J.; Brasca Merlin, A.; Sammaritano, M.; Molina, R.; López, M.; Greca, I.M. Sustainability Education in Geomatics Students: Nature of STEM Through Meteorology and Ecology of Fire. Sustainability 2024, 16, 11208. https://doi.org/10.3390/su162411208

AMA Style

Martínez-Martínez V, Ortiz-Revilla J, Brasca Merlin A, Sammaritano M, Molina R, López M, Greca IM. Sustainability Education in Geomatics Students: Nature of STEM Through Meteorology and Ecology of Fire. Sustainability. 2024; 16(24):11208. https://doi.org/10.3390/su162411208

Chicago/Turabian Style

Martínez-Martínez, Víctor, Jairo Ortiz-Revilla, Almendra Brasca Merlin, Mariela Sammaritano, Rodrigo Molina, Matías López, and Ileana María Greca. 2024. "Sustainability Education in Geomatics Students: Nature of STEM Through Meteorology and Ecology of Fire" Sustainability 16, no. 24: 11208. https://doi.org/10.3390/su162411208

APA Style

Martínez-Martínez, V., Ortiz-Revilla, J., Brasca Merlin, A., Sammaritano, M., Molina, R., López, M., & Greca, I. M. (2024). Sustainability Education in Geomatics Students: Nature of STEM Through Meteorology and Ecology of Fire. Sustainability, 16(24), 11208. https://doi.org/10.3390/su162411208

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