This presentation aims to describe the network governance (Jones et al., 1997; Provan and Kenis, 2008) produced in European education through the interactions ensured by the Expert Groups coordinated by the European Commission.

An ever-growing literature examined the contribution of interest groups to public education policy at the national (Viseu and Carvalho 2021) and international levels (Ball, 2012; Schuster, Jörgens and Kolleck 2021) and to European education policy (Olmedo, Bailey, and Ball, 2013). This literature also focused on the Commission’s Expert Groups (Milana, Klatt and Tronca, 2020; Milana, Tronca and Klatt, 2020).

Interest groups hold a favourable position in European governance, as they specialise in a narrow policy domain or issue around which they can network and gather information (Börzel, 2002; Costa & Muller, 2019). Given politics and policy fragmentations, there is a process of resource exchange between EU officials and interest groups (Rasmussen and Gross, 2015). EU officials often seek specialised information from interest groups, who in return seek access to EU officials as an opportunity to express their views and demands (Costa and Müller, 2019; Dür, 2008). 

Interest groups encompass several actors, including companies, trade and business associations, trade unions, private foundations, and non-governmental organisations (NGOs) that are neither governmental nor part of the market. Such interest groups are represented in the Commission’s Expert Groups, which assist policymakers in preparing working documents to support the European Commission’s directives and recommendations. Hence, we assume that participation in the Commission’s Expert Groups constitutes an opportunity for interaction between various types of interest groups and public institutions (at European and national levels), which produces a network capable of influencing the educational policies of the European Union. 

Against this backdrop, our study assumes a structural interactionist perspective (Degenne and Forsé, 2004, Tronca and Forsé, 2022) to examine the overall characteristics of the network produced by the Commission’s Expert Groups active in the field of education in terms of social cohesion and aggregation into subgroups and the structural positions of the single organisations and individual experts.

From this perspective, the structure of the network of relationships in which an actor operates determines the horizon of possibilities for its actions. Within the opportunities granted by the structure of relationships, actors choose freely which actions to take. It is, then, a ‘weak’ structural determinism. In short, the structure of the network of relationships, on the one hand, conditions the actions of each of the actors that constitute it and, on the other hand, is modified by the actions of the actors, who may or may not continue to maintain their ties or create new ones (Degenne and Forsé 2004).

In continuity with a similar investigation in terms of the object of study (Commission’s Expert Groups in education) and research method (Social Network Analysis) presented in Milana, Klatt and Tronca (2020) and Milana, Tronca and Klatt (2020), this study contributes further to the literature on European network governance in education.

Our data set consists of information extracted from the Commission's Register of Expert Groups and the European Union’s Transparency Register, which we analysed to reconstruct the collaboration network between all the actors involved, starting from their participation in the active expert groups. The data were collected in December 2024. The relational data thus obtained were examined using the tools of Social Network Analysis. From the Commission's Register of Expert Groups, we identified 13 Expert Groups active in the field of education, comprising 167 organisations and individual experts. We triangulated this information with that in the European Union’s Transparency Register for typify actors such as Member states, Candidate countries, Third countries, NGOs, Companies, Trade and Business associations, Trade Unions, Private foundations, Research institutes, EU agencies, EU networks or publish entities, International intergovernmental organisations, Academia, Individual experts. Once we had reconstructed an affiliation matrix in which we reported for each organisation and individual experts (rows) the possible membership of each Expert Group (columns), we reconstructed the network of collaborations between the organisations and individual experts guaranteed by their participation in the Expert Groups, which we transformed into a simple graph, within which the presence of a line between two nodes represents the existence of at least one Expert Group shared between them. We utilised the Ucinet 6 software (Borgatti, Everett and Freeman, 2002) to analyse the graph and the NetDraw software (Borgatti, 2002) to obtain its representation. As measures, we used density to determine the level of social cohesion, the two connectivity measures of ‘local centrality’ (i.e., degree and its normalised measure) and ‘global centrality’ (i.e., betweenness, and its normalised version, Freeman, 1979) with their relative levels of centralisation, and the cliques or indicators for highly cohesive subgroups (Wasserman and Faust, 1994).

While the study is under development, preliminary results point to a density level of 38.01% for the simple graph. This value is decidedly lower than the previous survey (Milana, Klatt and Tronca, 2020), which considered the Commission’s Expert Groups active in lifelong learning, with a density level of 63.20%. The significant growth of the brokerage phenomenon within the network under consideration in this study is accompanied by a decrease in density. Whereas in the previous survey, no organisation exceeded the nBetweenness level of 2%, now the actor most capable of acting as a broker even exceeds that of 25%, and other organisations show a relevant capacity to act as brokers within the network. Finally, unlike the previous survey, which identified a few organisations capable of reaching the highest level of local centrality (nDegree=1), no node has reached this level of centrality. The network governance between the institutions and NGOs participating in the Expert Groups thus is, to a very significant extent, characterised by the phenomenon of intermediation, in the sense that there are specific nodes that can affect decision-making processes by connecting unconnected nodes. The organisations that most significantly display this capacity are the Association for Teacher Education in Europe (ATEE), which reaches a level of nBetweenness of 25.772%, the European Trade Union Committee for Education, (ETUCE) 7.385%, UNESCO, 5.460%, OECD, 4.816%, ALL DIGITAL, 3.170%, European Schoolnet (EUN), 2.279%.

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