Conference Agenda

The democratisation of education has triggered new educational issues related to the advocacy of a school promoting equal opportunities and social justice. The need for education systems to guarantee access and success for all students has put education at the centre of the political and economic space. Thus, there are several political texts that, in the last decades, produce meanings and guidelines for the design of more inclusive educational systems. This has contributed to inclusive education becoming a nominally accepted concept (Nilholm, 2006) and to its assertion as in a global political vision (Pijl, Meijer and Hegarthy, 1997). In Portugal, the Legal Framework for Inclusive Education (decree-law 54/2018, of 6 July) established for the first time in the same legal normative, measures to support learning and inclusion (MSAI) for all students and reinforced the participation of the educational community (teachers, students, guardians and external stakeholders from local communities) for its implementation. This Decree-Law established formal moments for such participation and provided guidelines to create conditions for schools to affirm themselves as more politically democratic contexts (Trindade & Cosme, 2010) in which inclusive education is seen as a purpose for the whole community. Despite the potential changes that this text seems to point towards a more inclusive education policy, we assume that the process of implementation of education policies departs from the social engineering model in which the policy text determines the practices and effects (Stoer and Magalhaes, 2005). In this way we are arguing that the implementation of an educational policy is a process of meaning construction (Spillane, 2004). Having this as a reference, we mobilised for the research the theoretical-methodological approach of the Policy Cycle of Stephen Ball (1994), which assumes the characterisation of the investigated policy with the discussion of historical, legislative, discursive and political-ideological aspects (Ball, Maguire and Braun, 2012) from five contexts: context of influence, context of text production, context of practice, context of effects, and the context of political strategy. This critical and post-structuralist approach refuses the idea that structure is what will define policy and the political process; on the contrary, it argues that policy emerges from the priorities of different interest groups and their network governance (Veiga, 2012) and that it develops with the participation and interaction of groups of people who construct and constitute reality. Thus, according to this approach, the origin of policies is not circumscribed to an isolated moment or to one of the contexts of the policy cycle. In this paper we propose to explore the contexts of influence and text production of the inclusive education policy embodied in decree-law 54/2018, identifying its conditions of production (Pêcheux, 1993), i.e., the influences that collaborated to its placement on the agenda. To access these contexts of the cycle of inclusive education policy we analysed international and national texts, such as declarations, conventions, studies, opinions, reports and legal texts. The research questions that guided this analysis and that we intend to answer in this proposal are: What are the organisations that guide inclusive education policies? What are the ideas that underpin inclusive education policies?

As outright discrimination has largely transformed into covert inequities, “discrimination [has] moved underground” (Massey, 2007). Institutions are increasingly interested in fostering diversity and inclusion [D&I] to counteract these inequities (Brimhall et al., 2017). Although frequently linked, diversity and inclusion are distinct (Mor Barak et al., 2015). Measuring the impact of D&I interventions on diversity involves monitoring workplace demographics. Measuring inclusion is less straightforward (Sherbin & Rashid, 2017). Researchers fail to agree on a single construct of inclusion and lack evidence to do so (Shore et al., 2011). Yet, defining and measuring inclusion is critical in the studying of how social stratification is localised in different contexts, such as in education.

Researchers usually define inclusion as perceptions of uniqueness and belongingness, or alternatively, as participation and contribution. Theories borrowed from social psychology explain how individuals will unconsciously sort themselves into groups based on commonalities, such as gender or race, while group membership influences how they perceive others (Tajfel & Turner, 1986). Individuals must feel a sense of belongingness in their groups, while also being sufficiently recognised for their unique characteristics (Shore et al., 2011). These social psychology theories could explain how individuals’ framing of themselves and others manifest into group dynamics. Therefore, social psychology could provide an explanation for patterns of student interaction within a given classroom.

Yet, a purely social psychological framework of inclusion overlooks how inclusion exists beyond individuals’ sentiments. Instead, Roberson (2006) defines inclusion as “the removal of obstacles to the full participation and contribution of [people] in organisations”. This version of inclusion highlights how in- and out-group dynamics dictate who is trusted, who is communicated with, and ultimately, who is embedded in social and collaboration networks (Ridgeway, 2011). Conventional inclusion surveys effectively measure inclusion as uniqueness and belongingness as Shore et al. (2011) defines it, but fail to appropriately measure inclusion in terms of participation and contribution.

To solve this methodological gap in the literature, this research borrows methodologies from the field of data science to revitalise inclusion research, using one university as a case study. The participating university was an elite public higher education institution. It prides itself on the usual interests of most historically white, high-ranking, and well-funded 21st century educational institutions: being research-driven, global, future-oriented, and a leader in higher education and learning. As such, in September 2022, one school at the institution implemented mandatory inclusion training for all tutors. The training had three main goals: to increase awareness and knowledge of what constitutes equality, diversity, and inclusion; to teach tutors tangible ways to alter behaviours to foster inclusion; and to provide a space for tutors to learn from each other to further develop inclusive teaching practices. The study and this resulting paper are a showcase of how one computational social science method, social network analysis, can help measure and analyse inclusion, as participation and contribution, in educational settings. Only a few studies to date have used social network analysis to research patterns of inclusion, such as Karimi & Matous (2018), Collins & Steffen-Fluhr (2019), and Hardcastle et al. (2019). None have employed mixed-methods of social network analysis, survey analysis, and demographic analysis. This innovative mixed-methods, but largely computational, approach is the focus of this paper as it allows educational researchers to monitor changes in students’ experiences of inclusion. A secondary benefit of this method is that it provides evidence, or lack thereof, for D&I interventions as they are implemented. Therefore, using social network analysis to measure inclusion helps ensure all students, regardless of identity, succeed in their education.