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Research Article

The development of a Competence Framework for Environmental Education complying with the European Qualifications Framework and the European Green Deal

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Abstract

Following the severe impact of capitalist industrialization on the environment, the EU has funded several projects in the context of the European Green Deal to pursue climate neutrality by 2050. Some of these projects attempt to achieve zero emissions through political participation, while others by committing EU citizens to adopt sustainable habits in terms of both practical behavior and economic choices. The GreenSCENT project, funded by the European Union’s Horizon 2020 research and innovation programme, aims to develop a Competence Framework compliant with the European Qualifications Framework and the European Green Deal. The present article documents the process of developing such a Competence Framework. Eight distinct research teams independently conducted a similar thorough literature review over an assigned topic (Climate Change; Clean Energy; Circular Economy; Green Building; Smart Mobility; From Farm to Fork; Biodiversity; Zero Pollution). The resulting documental corpora have then elicited to build the competence matrices and the corresponding European Qualification Framework levels. Once the information has been reorganized as a knowledge graph, the researchers discovered a large amount of novel interdomain connections, providing a more engaging way of interacting with the Competence Framework, and potentially apt to avoiding information overload issues while preserving the complexity, in line with the simplexity paradigm. The environmental education tools produced by this research could be useful in mitigating the repercussions of Capitalocene on the environment toward the adoption of more sustainable behaviors.

Introduction: Reshaping climate policy through competences to tackle Capitalocene-induced climate change

The European Commission began adopting proposals to transform EU climate policies in 1996 with the Council Directive 96/61/CE of 24 September 1996 concerning integrated pollution prevention and control (EUR-Lex—31996L0061—EN, Citation1996). Subsequently, Directive 2003/87/CE of the European Parliament establishing a scheme for greenhouse gas emission allowance trading within the Community was adopted in 2003 (Directive 2003/87/EC of the European Parliament and of the Council of 13 October 2003 Establishing a Scheme for Greenhouse Gas Emission Allowance Trading within the Community and Amending Council Directive 96/61/EC, Text with EEA Relevance, Citation2003). In addition to these uniquely European directives, many EU states joined important international and intergovernmental climate pacts such as the Kyoto Protocol (Citation1997) or the Accord de Paris (Paris Agreement, Citation2015). In more recent times, the European Green Deal (GD) communication, has been published in December 2019 (Communication on The European Green Deal, Citation2019). Through the latter, the European Commission adopted proposals to transform EU policies regarding eight critical focus areas named: Increasing the EU’s Climate Ambition for 2030 and 2050; Supplying Clean, Affordable and Secure Energy; Mobilizing Industry for a Clean and Circular Economy; Building and Renovating in an Energy and Resource Efficient Way; Accelerating the Shift to Sustainable and Smart Mobility; From “Farm to Fork”: Designing a Fair, Healthy and Environmentally-Friendly Food System; Preserving and Restoring Ecosystems and Biodiversity; A Zero Pollution Ambition for a Toxic-Free Environment (Communication on The European Green Deal, Citation2019)—for the sake of simplicity, hereinafter we will use the corresponding following terms: Climate Change; Clean Energy; Circular Economy; Green Building; Smart Mobility; From Farm to Fork; Biodiversity; Zero Pollution.

The European Green Deal (GD) aims to achieve zero emissions by 2050, drastically reducing the environmental impact caused by the capitalist industrialization of the Anthropocene (Steffen et al., Citation2021; Steininger et al., Citation2022; Svenfelt et al., Citation2019).

Similarly to all other geological epochs, Anthropocene is marked by major global climatic events. In general, the global climatic events resulted in extinctions and subsequent appearance of new biota species, susceptible to natural selection and able to adapt more successfully to new environmental conditions (Beniston & Stephenson, Citation2004; Hoffmann & Sgrò, Citation2011). In the Anthropocene, for the first time in geologic history, the causes of climate change come from the biota with the best fitness relative to others on the planet: the Anthropos (i.e., humanity) (Moore, Citation2017, Citation2018).

In the context of the Anthropocene, the epoch in which human beings began to produce major effects on the planet, from the agricultural revolution to the present day, a stage can be defined. From the nineteenth century, the environmental changes accelerated dramatically due to capitalist economic power patterns that led to the extreme exploitation of resources without regard to ecological consequences (Moore, Citation2017). Because of these capitalist patterns, from the Anthropocene epoch, we are entering the stage of the Capitalocene—the time interval characterized by the accumulation of capital causing major implications, such as extensive changes in ecosystems (Moore, Citation2018, Citation2017). To reduce the ongoing impact of Capitalocene and tackle these upheavals, global policies are implementing several regulations and communication initiatives such as the European Green Deal (GD).

Reducing environmental impact would eventually result in increased well-being and improved health for citizens of the future generations, as well as an acceptable fitness on the planet also in economic terms (Bare, Citation2002; Remoundou & Koundouri, Citation2009). However, promoting GD requires political involvement, economic collaboration, and citizen engagement (Beauchampet & Walsh, Citation2021). The latter is crucial for the realization of such an ambitious project, but since the concept of environmental sustainability was introduced only a few decades ago, in this time of transition is mandatory to educate citizens about environment and sustainability themes (Caradonna, Citation2014; Foladori, Citation2005; Jickling & Wals, Citation2018; Robottom, Citation2005; Stevenson, Citation2007; Tilbury, Citation1995; Tranter & Malone, Citation2005; Van Rensburg, Citation1994). There is a strong tie between education and environmental attitudes, like the scholars have pointed out, especially in recent times (Pettus, Citation1976; Rickinson, Citation2001). Educated people are aware of these issues and tend to be more sensitive to the environmental consequences of their consumption behavior, as well as to be more prone to undertake environmentally conscious decisions (Onel & Mukherjee, Citation2015; Yue et al., Citation2020). Citizens aware of sustainability issues inevitably develop stronger environmental values and show greater support for environmental protection policies. Moreover, they are more likely to engage in activities that promote eco-friendly lifestyles, such as recycling and composting (Gilg et al., Citation2005; James, Citation2016; Yusliza et al., Citation2020). With these evidences in mind, European Union’s Horizon 2020 research and innovation programme funded several projects. Among them, the GreenSCENT – Smart Citizen Education for a greeN fuTure – (grant agreement No. 101036480) stands out (Garito et al., Citation2023). GreenSCENT aims to educate citizens through behavioral changes by developing a Competence Framework on sustainability (a.k.a “GreenSCENT Competence Framework”) leveraging experts’ input and suggestions, citizen participation, and students’ engagement.

A detailed Competence Framework on sustainability could help to bridge the knowledge gap by providing useful competences not yet sufficiently addressed to the community and enhancing the environmental education. Such a framework would provide a structure to help people to understand the concepts and challenges of sustainability and, especially, how these concepts can be applied in everyday life.

The Competence Framework is not only limited to help in bridging such knowledge gap, but it can also answer the question of the environmental education research by providing a platform for developing citizens’ competences.

The framework might be implemented in education systems, also outside European Union, allowing students to gain a strong environmental sensibilization that is currently lacking.

The GreenSCENT Competence Framework was developed for all eight GD areas (e.g., Climate Change; Clean Energy; etc.) addressed in the European communication. This paper only considers Clean Energy and Zero Pollution GD topics as a case study. The target of the Competence Framework built up in the GreenSCENT project is a broad spectrum of citizenship starting from teachers, and education designers to professional workers and students classified by educational rank with the European Qualification Framework levels (EQF) (The European Qualifications Framework (EQF) Europass). The aim is to provide a behavioral pattern through competences defined as a set of sustainable Knowledge, Skills, and Attitudes used in the construction of an explorable knowledge graph tool (De Nicola et al., Citation2022; Wang et al., Citation2017). This tool can be used by education designers to guide young people and beyond toward environmentally sensitive behaviors.

The remainder of the paper is organized as follows: Section “How Competence Frameworks are built: a comprehensive review of existing literature to identify competences” describes the literature review carried out to constate how much documentation was published on the topics covered in the GD communication targeting which educational levels. Highlighting gaps and areas that are lacking in publications is a further result that occurs during the process and which must be taken advantage of. To determine the number of published documents on each topic, it is necessary to populate the Competence Framework tool with data from research; Section “How Competence Frameworks are built: competence matrices and a knowledge graph creation for a sustainable future” describes the methodologies adopted in the construction of the Competence Framework and the related Knowledge Graph. These constitute the main objective of the work, i.e. the creation of a competence database; Section “Exploring the Competence Framework: matrices and a knowledge graph as complementary tools in addressing sustainable competences” describes the results of the research subsequently discussed in Section “Redesigning Competence Frameworks by combining competence matrices and knowledge graphs for sustainable education”; Section “Conclusions: enhancing environmental education exploiting Competence Framework matrices and knowledge graphs to tackle Capitalocene-induced climate change” deals with the conclusions of the research.

How Competence Frameworks are built: A comprehensive review of existing literature to identify competences

The research project begun with a literature review on sustainable education papers, in order to identify the competences at the basis of the Competence Framework developed. Starting initially by consulting all the relevant papers cited in already published Competence Frameworks such as GreenComp, DigComp, DigCompEdu, and EntreComp produced by the Joint Research Center (JRC) (Bacigalupo, Citation2022; Bacigalupo et al., Citation2016; Bianchi et al., Citation2022; Cabero-Almenara et al., Citation2021; Kluzer & Priego, Citation2018); then the involved researchers (13 people) queried Scopus and ERIC scientific databases to find more specific papers on a given GD area and a given EQF. Given the conspicuous volume of gathered documents, the research team developed a software-based framework of tools specific for its management. By exploiting some established natural language processing (NLP) algorithms (e.g., latent Dirichlet allocation, cosine similarity, Okapi BM25), this framework assesses the relevance of the papers (Blei et al., Citation2003; Robertson & Zaragoza, Citation2009; Singhal, Citation2001). More in detail, initially the documental corpus was converted from .pdf files into simple text format through the R package pdf-tools (Ooms, Citation2020). Then, the text files were parsed and analyzed in the Matlab environment where already built-in NLP functions were available. Finally, the cluster with the highest probability of having words referable to a GD area or an EQF was identified. After the previous stages, the screened documents were read by the research team and validated. Given the fragmentary nature of the data and the need to rationalize it, two literature matrices were built, one quantitative and one qualitative (Klopper et al., Citation2007). The quantitative literature matrix () is structured by cross-referencing the GD Focus Areas with the EQF levels.

Table 1. Quantitative literature matrix structured by cross-referencing the Green Deal Focus Areas (marked in the green row at the top) with the European Qualification Framework Levels (marked in blue on the leftmost column).

Each cell of the quantitative literature matrix shows the amount of documents present in terms of both GD Focus Area and Education Level. The row and column in red show the total number of articles found. From these results, it is possible to observe that some Focus Areas or some educational levels are more addressed in the literature than others. For example, the Climate Change topic has been more extensively addressed than the Green Building one. From the EQF standing point, there are fewer documents related to primary and secondary education than those addressed to professional workers and university students. Despite the overlapping of many documents in terms of Focus Areas and EQF, this quantitative analysis highlighted the need for a deepening of the knowledge, both by GD focus area and by EQF target, with the aim of data balancing in a homogeneous communication and information.

The qualitative literature matrix ( in the appendix) is structured similarly, but in this case each cell presents bibliographic sources. At this point, it is straightforward to recognize which documents are the most comprehensive in terms of GD areas and EQF occurrences. These documents turn out to be gray literature papers such as the UNESCO, OECD, and UNEP Reports (Sukhdev et al., Citation2010; OECD, Citation2011; Rieckmann, Citation2017; Leicht et al., Citation2018; Baker et al., Citation2019; Taguma & Barrera, Citation2019). The qualitative matrix also allows to understand how themes and targets vary over the years. Previously the documents dealt with sustainability in general, addressed primarily to the professionals. Only more recently has the Green Deal begun to be sectorized and affordable also for the K12 primary and secondary school students.

Interestingly, the literature review revealed an inhomogeneity in the amount of research or advancement of knowledge for some GD areas and some EQFs compared to others. The most strongly consolidated topics in the bibliography concern the Climate Change, Clean Energy, Circular Economy, Biodiversity, and Zero Pollution. There are knowledge gaps in the topics of Green Building, Smart Mobility, and From Farm to Fork. These latter topics were often treated within the topic “sustainability” in general and only in recent years begun to arouse interest with respect to the focus areas well-consolidated in the literature (i.e., Climate Change). Specifically, the topic of Climate Change appeared in the literature in the early 1900s (Lockyer, Citation1910; “Climate Changes in Western America,” 1926). In the 1960s and 1970s, articles dealing with the topics of Clean Energy, Biodiversity, and Zero Pollution began to be published (Bohnke, Citation1973; Crawford, Citation1969; Dale, Citation1970; Leakey, Citation1966; Stone & Johnson, Citation1972; Valentine, Citation1968). In the 1980s, Circular Economy began to be discussed (Brown, Citation1987; De Gregori, Citation1985). The areas of Green Buildings, From Farm to Fork and Smart Mobility are only addressed in literature from the 1990s and early 2000s (Coleman, Citation1995; Finch, Citation1992; Iwasa et al., Citation2006; MacNamara & Lacey, Citation2000; Oliver, Citation1990; Schothorst, Citation1997).

Concerning the EQF levels, as mentioned above, the publications to date are more aimed at professional workers (EQF3) and more advanced higher education (EQF6, EQF7, EQF8). The literature gap is consequently found to a greater extent for EQF1 and EQF2 levels followed by EQF4 and EQF5 levels. The inequality in the amount of research or advancement for some educational levels compared to others lies in the variation in the consideration of youth over time. Previously the major promoters of sustainability were professional workers and highly educated citizens, in recent decades the biggest supporters of these issues are the younger generations, who often have lower EQFs for age-related reasons (Belotti et al., Citation2022; Bergmann & Ossewaarde, Citation2020; Jung et al., Citation2020). As briefly mentioned, the main objective of the work is to create a database of competences and not to highlight gaps in the literature. Although this was not the main goal, it turns out to be a further important achievement in the research process that must be taken into account. Thus, despite this paper’s main research question is the development of useful resources for educational systems, it is important to note a lack of sufficient and unbalanced publications between the different GD topics. This is a different gap from the one being addressed in this paper but to build a database for educators is an issue that cannot be underestimated.

The literature review paragraph, describes the fundamental method of the Competence Framework building, namely the concept mining. Thanks to the literature review, it was possible to populate the Competence Framework with competences. The literature review paragraph was separated from the paragraph on methodologies for the following reason: in the Methods section are reported the more operational methodologies about the construction of the framework, such as the structure of the matrices (or tables) which constitute it, and on the building of the Knowledge Graph, which provides a parallel view of the matrices.

How Competence Frameworks are built: Competence matrices and a knowledge graph creation for a sustainable future

Building the foundation: Clean energy and zero pollution competences in the GreenSCENT Competence Framework matrices structure

The literature review provides the base to design the Competence Framework for all the GD focus areas and EQF. Clean Energy and Zero Pollution focus areas will be addressed in this paper. The Competence Framework for each GD topic is structured in a series of matrices as already published Competence Frameworks (Bacigalupo, Citation2022; Bacigalupo et al., Citation2016; Bianchi et al., Citation2022; Cabero-Almenara et al., Citation2021). Kluzer & Priego, Citation2018;

The GreenSCENT Competence Framework is much more detailed than the other existing Competence Frameworks already present in the literature: it consists of a higher-order matrix and several lower-order matrices addressing the competences for every single GD topic. In the first-order matrix, the specific GD topic, i.e., Clean Energy () or Zero Pollution (), is categorized into competence areas, which in turn cluster different competences in a specific column of the matrix (i.e., “Competence Areas”). To any of such competence is assigned a descriptor that broadly illustrates it. To each competence in the first-order matrixes match a second-order matrix illustrating the behaviors to be enacted on that specific competence (an example is reported in ).

Figure 1. The first-order GreenSCENT Competence Framework matrix concerning the Clean Energy GD focus area shows the competence areas column, the single competences column, and the column containing descriptors illustrating each competence.

Figure 1. The first-order GreenSCENT Competence Framework matrix concerning the Clean Energy GD focus area shows the competence areas column, the single competences column, and the column containing descriptors illustrating each competence.

Figure 2. The first-order GreenSCENT Competence Framework matrix concerning the Zero Pollution GD focus area shows the competence areas column, the single competences column, and the column containing descriptors illustrating each competence.

Figure 2. The first-order GreenSCENT Competence Framework matrix concerning the Zero Pollution GD focus area shows the competence areas column, the single competences column, and the column containing descriptors illustrating each competence.

Figure 3. Second-order GreenSCENT Competence Framework matrix. The example shows the “Organic Products” competence matrix belonging to the “Pragmatic Zero Pollution Competence Area.”

Figure 3. Second-order GreenSCENT Competence Framework matrix. The example shows the “Organic Products” competence matrix belonging to the “Pragmatic Zero Pollution Competence Area.”

In the second-order matrix, every single competence identified is categorized in the first column as a set of Knowledge, Skills, and Attitudes (KSA). Another column reports the EQF education levels of the whole educational spectrum from elementary school to post-docs via professional workers. Each KSA is explained in terms of knowledge, skill, or attitude to be obtained. The last three columns (i.e., keywords, hashtags, and notes) are conceived to ease the research process during the knowledge graph construction, and to provide the bibliographic references.

Visualizing the GreenSCENT Competence Framework: An innovative approach to build the Competence Framework

Humans have evolved relying most of their cognitive capacities upon image recognition (Rees, Citation2008; Yunes, Citation2005). Starting from this consideration, to give EU citizens a more affordable and visually appealing tool with respect to the matrices, the research group has converted the latter into an aggregated resulting knowledge graph. Such data representation allows for coping efficiently with a large amount of complex information (Patriarca et al., Citation2019). At the same time, this realization reduces the well-known problem of information silos (Min et al., Citation2022).

The Grounded Theory (Bryant, Citation2017; Charmaz, Citation2014; Glaser & Strauss, Citation2017; Strauss & Corbin, Citation1997; Tarozzi, Citation2008) has been used as a conceptual reference to build the knowledge graph linking the GD focus areas. This research approach provides a strategy for qualitative data collection, management, organization, and analysis (Allan, Citation2003). The data collected from the literature review were used in the analysis involving the following fundamental steps (Bernard et al., Citation2016; Bryant & Charmaz, Citation2007; Charmaz, Citation2014):

  • Text coding: useful concepts are identified marking key information with this step. Text coding includes the selective, the axial, and the open coding (these are explained more in detail further in the paper).

  • Memorizing: this involves a procedure in which the researcher documents transition notes for each identified concept.

  • Integration and refinement: once the coding concepts are recognized, they are linked together in a model built around a central issue that embodies the different identified enquiries. Obsidian software () (Obsidian, n.d.) was used to accomplish these steps, which already proved to be useful in similar research activities (Falegnami et al., Citation2021, Citation2022).

Figure 4. Knowledge graph showing links between Clean Energy and Zero Pollution GD focus areas. Clean Energy and Zero Pollution GD focus areas are reported as the two major blue circles. Competences are marked as gray circles. Hashtags are represented as beige-colored circles.

Figure 4. Knowledge graph showing links between Clean Energy and Zero Pollution GD focus areas. Clean Energy and Zero Pollution GD focus areas are reported as the two major blue circles. Competences are marked as gray circles. Hashtags are represented as beige-colored circles.

In the Grounded Theory the coding processes are (Strauss & Corbin, Citation1997):

  1. The selective coding which identifies the most generic and predominant categories of hierarchical order with higher level. As predominant concepts and higher-order categories, the eight focus areas found in the European GD communication were identified (Clean Energy and Zero Pollution in this paper) (blue circles in ).

  2. The axial coding, is a procedure involving data reorganization by making connections between categories, linking concepts that run together. Axial coding is performed in our work through the different competences identified (gray circles in ).

  3. Open coding is a process to design an open category system with maximum flexibility. The purpose is the data fragmentation to derive its properties by generating a taxonomy of concepts and categories. This step was set up by tagging (#) each knowledge, skill, and attitude in the second-order competence matrices with an appropriate sub-topic label (beige circles in ).

Memorizing lays the foundation for the coded theoretical relationships that emerge during coding, data collection, and analysis (Glaser, Citation1999). Memos are tools to refine and keep track of ideas that develop when researchers compare concepts and elaborate ideas to link concepts to each other. In this work, the purpose of relating concepts was to make the GreenSCENT Competence Framework as accessible as possible.

Pragmatically, Obsidian enables a rather complex text formatting that allows the hierarchical ordering of nodes and links between them. Markdown files were built directly in Obsidian and displayed subsequently in the graph (Falegnami et al., Citation2021). The knowledge graph was created to generate strong connections by inserting a text string inside a double pair of square brackets and weaker links using hashtags. The strong connections are imposed to be the links between the GD focus areas (blue circles in ) and the competences (gray circles in ). The weak links were obtained through the tagging process, and represent the latent connections between keywords, key concepts, EQFs labeled with hashtags to each KSA (beige circles in ) and competences (gray circles in ). As a result, a cognitive artifact (Kaastra, Citation2020) was obtained for the efficient delivery of GreenSCENT Competence Framework and the potential promotion of sustainable behaviors. Cognitive artifacts provide a shared assessment of the impact of research results and describe the need for changes in science involving social cognitive processes (Lomas, Citation2007). Cognitive artifacts (i.e., information displays) provide detail to thought processes and increase knowledge. They might play a key role in cognition driving the mental processes of data selection and evaluation, reasoning and decision-making. These cognitive processes have been deemed fundamental to promote sustainable behaviors (McLane et al., Citation2010; Patriarca et al., Citation2021; Walker & Avant, Citation2005).

Exploring the Competence Framework: Matrices and a knowledge graph as complementary tools in addressing sustainable competences

GreenSCENT Competence Framework matrices and the role of knowledge, skills, and attitudes to establish a competence

The framework matrices constitute the core tool of support to educators to address the purpose of environmental education. GreenSCENT Competence Framework’s first-order Clean Energy () and Zero Pollution () matrices both show a subdivision into three competence areas derived from the literature review. The first one, entitled “Transversal Competence Area,” encompasses concepts applicable to sustainable education and sustainability behaviors of all GD areas.

The second one, named “Pragmatic Competence Area” includes the tangible concepts related to the GD macro areas.

The third competence area detected for GreenComp’s first-order Clean Energy and Zero Pollution matrices is about competences with significant economic implications and application in industry, innovation, and employment opportunities. Thus, the latter was entitled “Implication and Application Competence Area.”

GreenComp’s second-order matrices (example reported in ) correspond to each of the identified competences previously mentioned in the first-order ones. Is given as an explanatory example “Organic Products” competence, belonging to the “Pragmatic Zero Pollution Competence Area.” As briefly mentioned in the methods chapter (see par.3.1), second-order competence matrices are characterized by a set of KSAs that define sustainable behaviors addressed in competences.

Knowledge is defined as the learning of concepts and the condition of being aware of something in the cognitive processing of information. In the reported example, for the primary school EQF level (EQF1), the knowledge “Awareness of the importance to separate collection of organic waste” was identified. For higher EQF levels (EQF2 to EQF8), the knowledge “Awareness of the long-term impact of non-biodegradable waste on the environment, on the ecosystem” and the knowledge “Awareness of the difference between biodegradable and non-biodegradable products and their different impact on the planet” were detected. Therefore, generally speaking, knowledge for this competence addresses the awareness of the impact of waste.

Skill is defined as the learning to do something and being able to perform an activity and then apply the knowledge gained. The skills identified in this competence are mostly related to the promotion of the avoidance or reuse of disposable materials whenever possible; other skills are related to supporting the use of biodegradable or natural items and reducing the purchase of products incorporating plastics. These skills are marked EQF3 to EQF8, as primary school students (EQF1 and EQF2) are unlikely to be able to make choices such as buying sustainable items.

Attitude is defined as the learning to form a new or different perspective belief, a way of thinking and feeling about someone or something. The attitudes identified in the competence “Organic Products,” for EQF1 focus on the assumption that an organic product derived from sustainable agriculture/cultivation is preferable to a product derived from intensive industrial processes. For EQF2, the attitude identified is about produce as less non-biodegradable waste as possible to improve environmental conditions. Attitudes for EQF3 to EQF8 are related to composting organic waste at home and adopting organic products without pesticides or chemicals.

The remaining columns of the second-order matrices are dedicated to the hashtags, keywords and literature notes. The first is required for the knowledge graph building.

Visualizing labeled competences and their interconnections in the GreenSCENT Competence Framework knowledge graph

The knowledge graph developed in Obsidian software () shows the connections between key concepts identified in the GreenSCENT Competence Framework’s matrices related to Clean Energy and Zero Pollution GD focus areas case study of this work.

The focus areas are represented in the graph as two blue circles. These are larger than the other circles because they are linked to all the connections of the graph. All the connections to the competences and consequently to the hashtags branch off from the focus areas. Competences developed in the GreenSCENT Competence Framework first-order matrices are represented as gray circles. Competences are the linking element from focus areas to hashtags allowing the connection between a very broad topic to sector-specific concepts ().

Figure 5. Detail of the knowledge graph showing the connection between the Zero Pollution focus area and its competences.

Figure 5. Detail of the knowledge graph showing the connection between the Zero Pollution focus area and its competences.

Hashtags assigned to the KSA items developed in the GreenSCENT Competence Framework second-order matrices are represented as beige-colored circles (). As mentioned, the connections to hashtags assigned to each KSA depart directly from the competences (gray circles in ). The largest hashtags’ beige circles are those with the greatest number of links to different competences. Thus, these turn out to be the hashtags related to the EQF education levels that were most labeled through the Competence Framework. The knowledge graph complemented by the framework matrices will allow an enhancement of the tool for environmental education that will be more accessible to the citizenry in general in addition to educators and educational designers.

Figure 6. Detail of the knowledge graph showing the connection between the Climate Action competence of the Zero Pollution focus area and the hashtags.

Figure 6. Detail of the knowledge graph showing the connection between the Climate Action competence of the Zero Pollution focus area and the hashtags.

Redesigning Competence Frameworks by combining competence matrices and knowledge graphs for sustainable education

Competences for a sustainable future countering the adverse effects of capitalism on well-being

The “Transversal Competence Area” included in the first-order matrices of Clean Energy () and Zero Pollution () GD focus areas, addresses several issues. These are useful in identifying, applying, and promoting the principles of sustainable development through one’s own values, perceptions, and actions by taking a position in the sustainability discussion (Holdsworth et al., Citation2008; Sterling & Thomas, Citation2006). This competence area also includes concepts about the global system complexity awareness, empathy, and respect for the environment (Wiek et al., Citation2011). Additionally, the notion of collaborative progress and inventive measures toward imagining a viable future are discussed (Evans, Citation2019; Lozano et al., Citation2019; Mets et al., Citation2021). Understanding the Earth system in an innovative, empathetic, and collective vision is the only way to achieve a sustainable future by replacing the capitalist interest foundation of the Capitalocene. The current era’s capitalist consumerism is fueling the factors behind the climate disturbance we’re facing, jeopardizing the well-being of communities (Clark & York, Citation2005; Lovins & Cohen, Citation2011).

The “Pragmatic Competence Area” covers more specific topics. In the Clean Energy focus area, competences have been identified concerning the promotion of the use of renewable energy. Adopting renewable energy sources would establish lasting and attainable models of consumption and production for all people, resulting in cities and human settlements that are equitable, secure and resilient (Constant et al., Citation2021; Kandpal & Broman, Citation2014; Rieckmann, Citation2017; Wynes & Nicholas, Citation2017). Regarding the Zero Pollution focus area in the “Pragmatic Competence Area,” concepts are elaborated regarding the need to preserve lands, the atmosphere, and the hydrosphere. By shielding these ecosystems from contaminants, we can ensure the preservation of biodiversity and promote sustainable communities via conscientious practices of production, consumption, and waste disposal (Rieckmann, Citation2017; Wynes & Nicholas, Citation2017; Leicht et al., Citation2018; Sandu et al., Citation2022;). The creation of a topic-specific competence area is fundamental to environmental sustainability education. With a solid knowledge base on specific topics, users of the Competence Framework will be better equipped to make decisions that will benefit the environment (Huang et al., Citation2020; Mphathiwa, Citation2015).

The “Implications and Applications Competence Area” addresses the Clean Energy and Zero Pollution topics from an economic and financial perspective. This competence area was developed to promote inclusive and sustainable industrialization to foster innovation and obtain expertise to contrast the current financial policy imposed by the Capitalocene (Moore, Citation2018, Citation2017). Furthermore, this area concerns the competences necessary to generate employment prospects associated with mitigating and controlling various types of pollution (Kandpal & Broman, Citation2014), as well as managing natural resources and promoting sustainable business development to encourage pollution prevention and the adoption of clean energy (Mets et al., Citation2021; Nowotny et al., Citation2018; Rieckmann, Citation2017).

The hundreds of KSAs identified are categories in which the learning lies. They are correlated to EQF levels based on the educational degree of the citizens whom these KSAs may be accessible. Knowledge is the cognitive ability useful for storing and processing information. Skills are physical abilities used to perform activities or tasks. Attitudes are feelings or emotions toward someone or something (Kelly, Citation2012; Salmani, Citation2021). KSAs are sequential to each other: knowledge assimilated and ingrained in behavior become skills, and with sustained practice, these skills shape one’s attitudes. Consequently, inevitably by stepping through KSAs, it is possible to achieve competences providing a behavioral pattern that can lead to counteract actions (Ferrari-Lagos et al., Citation2019) that encourage a capitalist model of society. The latter is rapidly increasing global warming causing climate change and the extinction of species that inhabit global ecosystems. The collective influence of these elements is bound to affect the well-being of humanity in the near term, and beyond (Lead, Citation2008; McMichael et al., Citation1996).

The Clean Energy and Zero Pollution issues highlighted in this paper necessitate policy-level interventions such as funding scientific research for forward modeling regarding the exploitation of alternative energy (i.e., wind, geothermal, or hydrogen) or the reduction of pollutants in soils and atmosphere (i.e., storing CO2 and radioactive waste in the subsurface) (Tomassi et al., Citation2022, Citation2023).

Encouraging sustainable education through knowledge graphs

The purpose of this tool is to offer an explorable database of competences. The user can explore the markdown text file or directly the corresponding knowledge graph (De Nicola et al., Citation2022; Falegnami et al., Citation2021).

In the knowledge graph, competences and labels (hashtags #) are collected, and dragging the mouse over a node displays the name and classification related. Similarly, dragging the mouse over a node of the GD focus area is it possible to see the name of the corresponding category and its connections (as shown in and in ). Clicking on the node displays the note corresponding to the selected competence or label ().

Figure 7. Screenshot showing the page of the note corresponding to the node of the graph that was hypothetically clicked with the mouse (in the example the 3.2 Employment opportunities area of the Zero Pollution topic).

Figure 7. Screenshot showing the page of the note corresponding to the node of the graph that was hypothetically clicked with the mouse (in the example the 3.2 Employment opportunities area of the Zero Pollution topic).

This database can be a valuable resource for anyone who wants to navigate the GreenSCENT Competence Framework through a graphic tool besides matrices. The use of a knowledge management tool has great potential for the usability of the concepts to be delivered with GreenSCENT Competence Framework, rendering it readily explorable and interactive for ease of access (De Nicola et al., Citation2022; Falegnami et al., Citation2021). As an example, a primary school teacher can exploit the knowledge graph by following the #EQF1 label bypassing concepts too complex for her or his students.

This knowledge transfer tool can strongly encourage the sharing of concepts (Falegnami et al., Citation2021) such as a sustainable and environmental culture by fostering an ecological behavioral pattern and bringing new aspects to be considered.

The competences related to Clean Energy and Zero Pollution in the interactive tool show the most connections among the transversal competences shared by most of the GD topics and EQF levels. Connections are also evident between the more specific concepts related to the topics of responsible consumption and production, sustainable communities, industry, and economy. Thus, the knowledge graph allows to find out links and connections between KSAs aiming to ease the accessibility of the Competence Framework. This tool could help in obtaining environmental competences. Attaining these competencies would enable individuals to regulate their consumption of food, energy, and other goods, leading to more sustainable practices. Moreover, it would facilitate comprehension of whether these items originate from environmentally conscious and sustainable production processes, having implications for the circular economy and eco-friendly industrialization. The dissemination of the Competence Framework with an innovative and easily explorable tool could be a turning point in the creation of environmentally sustainable and inclusive cities and communities as a driver of behaviorally, socially and economically sustainable growth. (Romanelli, Citation2022). Changing our behaviors could be the initial action to move as quickly as possible out of the Capitalocene that is compromising the durability of humankind’s (and other species’) permanence on earth. This behavioral change is the ambitious goal that GreenSCENT’s Competence Framework GreenComp aims even if there is still a long way to go.

Conclusions: Enhancing environmental education exploiting Competence Framework matrices and knowledge graphs to tackle Capitalocene-induced climate change

The interaction between the Capitalocene and climate change is a highly concerning issue that cannot be ignored. The Capitalocene refers to the current geological era, where the dominant mode of production is based on capital accumulation and the exploitation of natural resources for profit. Unfortunately, this system is also one of the main drivers of climate change, which is leading to disastrous consequences for the planet and all its inhabitants. The capitalist system that characterizes the Capitalocene is built on the principles of growth and expansion, which require the constant consumption of resources and energy. This has resulted in the production of huge amounts of greenhouse gases, such as carbon dioxide and methane, which are causing global temperatures to rise and the climate to become increasingly unstable. Furthermore, the impact of climate change is felt disproportionately by those who are already marginalized, including people living in poverty, Indigenous communities, and people in the Global South. These communities are often the most vulnerable to the impacts of climate change, such as drought, flooding, and food insecurity, but have the least resources to adapt to and mitigate these impacts. Despite the urgent need to address climate change, the Capitalocene system continues to prioritize profit over sustainability, and the interests of the wealthy and powerful over the needs of the planet and its inhabitants. The fossil fuel industry, for example, has been shown to actively lobby against climate action and perpetuate misinformation about the causes and consequences of climate change.

The aim of the GreenSCENT project is providing a Competence Framework to educate future citizen about green transition and foster sustainable behaviors. In this work, part of the Competence Framework developed within the context of the GreenSCENT project funded by the EU Horizon 2020 research and innovation program was exhibited. The aim of this paper is to build the framework, describing in details the process of building the framework included discussing competencies related to the Clean Energy and Zero Pollution GD focus areas taken as a case study and providing a tool for environmental education across EQF levels.

For both GD focus areas were identified tangible competence areas and inside each competence area, distinct competencies were described as a set of KSAs marked by EQF levels to provide a behavioral pattern.

Each item contained in the GreenSCENT Competence Framework was tagged obtaining a navigable knowledge graph which allows to find out links and connections between the two GD areas taken as a case study. Accordingly, the main conclusions are:

  • GreenSCENT Competence Framework provides a sustainable behavioral model addressed to all age groups and education levels of citizenship. The model shows how the competences related to the Clean Energy and Zero Pollution areas reveal a need to moderate consumption and ensure that consumer goods come from responsible and sustainable production.

  • The sustainable competences and KSAs identified in the GreenSCENT Competence Framework behavioral model describe actions that promote environmental awareness to be adopted to enhance sustainability.

  • A pro-environmental model focused on GD education might be the right way to encourage sustainability. Education on sustainable practices such as reducing energy consumption, recycling, and using renewable energy sources would motivate individuals to take action to reduce their environmental impact.

The limitations of the research presented may lie in the fact that the competences and KSAs identified in the framework may not produce the desired behavioral changes. Development and training of knowledge and mental faculties subject of education may be affected by social or intercultural issues or other characteristics that reflect the delicacy of the educational process. Additionally, the framework may not be able to capture the full range of competences and KSAs that are necessary for successful educational outcomes. Furthermore, the research may not be able to provide a comprehensive understanding of the impact of the framework on educational outcomes.

To minimize these limitations as much as possible, future research activities will involve running validation workshops to test the framework directly with the population that will benefit from it. Feedback will be gathered from these workshops to cross-reference a bottom-up research approach from the users with the top-down approach derived from the researchers’ analysis of the literature. Other future tasks within the project concern the application of the framework developed in pilot studies conducted on specific GD topics, involving school and university students and professionals in activities based on the Competence Framework. To see a comparison between the topics of the entire Competence Framework developed in all eight Focus Areas addressed in the European Green Deal Communication, one of the future research activities could be to publish the results in a monograph with all members of the research team.

In conclusion, the interaction between the Capitalocene and climate change is a complex and multifaceted issue that requires urgent attention and action. To address this problem, we must fundamentally rethink our economic system and prioritize sustainability, equity, and justice in all decision-making. It is crucial that we take immediate and meaningful action to reduce greenhouse gas emissions, protect vulnerable communities, and transition to a more sustainable and equitable future for all, and the proposed Competence Framework might represent a first important step for environmental education.

CRediT authorship contribution statement

Andrea Tomassi: Conceptualization, Methodology, Software, Data curation, Writing—original draft preparation, Results interpretation, Figures realization. Alessandro Caforio: Conceptualization, Methodology, Data curation, Results interpretation, Validation, Reviewing, and Editing. Elpidio Romano: Data curation, Validation, Reviewing, and Editing. Ernestina Lamponi: Conceptualization, Methodology, Software, Results interpretation, Validation, Reviewing, and Editing. Alessandro Pollini: Data curation, Validation, Reviewing, and Editing.

Acknowledgments

All partners of the GreenSCENT project are thanked for sharing their opinions about the Competence Framework. All the members working on Task 1.1 of the project are warmly thanked for sharing their ideas and experience with the research team. We are very grateful to the executive editor and the two anonymous reviewers for their constructive comments which greatly improved the work.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the GreenSCENT project within the European Union’s Horizon 2020 research and innovation programme under grant agreement [No. 101036480], funding which moreover permitted the paper to be published as open access.

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Appendix A

Table A1. Qualitative literature matrix structured by cross-referencing the Green Deal Focus Areas (marked in the green row at the top) with the European Qualification Framework Levels (marked in blue on the leftmost column).