Cross-national educational studies of student performance regularly show that socioeconomically disadvantaged students perform worse on average than their socioeconomically advantaged peers (OECD 2019; Stubbe et al. 2020). Bourdieu's theory of 'habitus' can be used as an approach to explain the reproduction of such social inequalities: while privileged groups of students inherit the cultural preconditions for successful adaptation to the educational system from their parents' homes, the familial habitus of non-privileged students may deviate from school values and requirements, so that it is often not performance but the "socially conditioned attitude" that is judged (Kramer, 2013). According to this, there is a lack of "habitus sensitivity" in everyday school life (Vester & Teiwes-Kügler, 2014), which is expressed in the fact that the lifeworlds of students and teachers are sometimes far apart, which can lead to conflicts and misunderstandings in class or when dealing with each other. In order to strengthen this "habitus sensitivity", it may be possible to provide teachers with appropriate knowledge about the social space of their students. As part of the Germany-wide educational project "SchuMas" (Schule macht stark), we developed an R-based tool that provides geo-referenced social space analyses based on small-scale social space data. Designed as a digital tool for social space exploration, the tool offers teachers the possibility to visualise different social indicators within the catchment area of schools on a city map. These indicators include, for example, the unemployment rate, the purchasing power or the educational level of the inhabitants. The representation at this area level makes it possible to get a differentiated picture of the social situation in the vicinity of the schools and thus to identify possible challenges and potentials within this social area on a quantitative basis. The distributions of the social indicators can be visualised on the basis of choropleth maps, for which various classification options are available (e.g. quantiles, "natural breaks"). Further possibilities for quantitative exploration of social space arise from the visual representation of the respective social indicators in the form of box plots, diagrams and in tabular form. In addition to a detailed description of the tool, our contribution will report on practical experiences of co-constructive collaboration with schools in challenging social spaces, where we have used our tool to offer teachers in the respective schools a workshop and an opportunity to reflect on the social space and the habitus of their students.

The geo-referenced social space maps generated with the R-based tool are based on data from the company microm and offer the possibility of combining data from small-scale neighbourhoods (approx. 500 households) to create a representative overall picture of the social space or school environment. The data was collected as part of the SchuMaS project for those schools with which intensive cooperation took place over a year in a so-called workshop phase in order to design a social space-oriented school and teaching development process. Based on the location of the school, the application allows to look at social space related indicators in a radius of 20 kilometres. In addition to descriptive analyses and visual representations of classified social space indicators, the application also offers the possibility of a multivariate analysis of the social situation in the school environment using a multiple deprivation index. This index is methodologically based on the British model of the Index of Multiple Deprivation (IMD) (DCLG 2019) and represents the extent to which small-scale neighbourhoods deviate from the citywide average. In addition to information on the usage of the R-based tool, the contribution also discusses how teachers can be made aware of the living conditions of their students using quantitative data. From a methodological point of view, we will discuss the workshop concept and experiences in the exchange with teachers and other pedagogical staff.

The presentation will give an insight into the possibilities of linking scientific work and everyday life in schools. On the one hand, it will show how social space data can be processed in a comprehensible and theory-based way for school administrators, teachers and other pedagogical staff, and how it can be related to everyday school practice. On the other hand, the approach chosen in the collaboration also emphasises the great relevance of a co-constructive exchange between science and practice, in which both parties meet at eye level. The experiences in the cooperation with the schools also show that although teachers have immanent knowledge about the social space and the social background of their students, discussions and reflections under guidance and with consideration of the actual social space data can help to improve habitus sensitivity and thus increase the probability of reducing misunderstandings and conflicts due to different life worlds.

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