|Institution(s)||Humboldt-Universität zu Berlin, Goethe-Universität Frankfurt|
|Maybe further partner(s)|
|Theoretical framework/approach||The data were categorized with reference to Pierre Bourdieu’s theory of capital to analyze and systematize the empirical results. It differentiates between three main forms of capital that define a person’s socio-economic status: economic capital, cultural capital, and social capital. Cultural capital is further divided into three dimensions that reciprocally influence one another: the objectified, the embodied and the institutionalized state.|
The study aims at answering the question of whether and how educational disadvantages in socially deprived settings are exacerbated through the pandemic and what counter measures can be taken.
|Themes / topics|
Educational inequality, COVID-19, distance learning, educational disparities, pandemic, Pierre Bourdieu, digital teaching and learning
|Main findings of study / highlights|
According to the teachers in socially deprived settings, their students lack resources in all three forms of Bourdieu’s capital. While these shortcomings are already problematic in regular times, they obstruct learning in times of distance teaching even more, worsening learning conditions and thereby adding to already existing disadvantages.
|Desig of data collection|
Carried out via video call, the interviews lasted 47 minutes. The data were transcribed following the guidelines by Dresing et al. (2015), aiming at literal yet legible transcripts. They were categorized through qualitative data analysis (Strauss, 1987) using the software MAXQDA (Kuckartz, 2018). After inductively encoding and identifying the significant similarities to and overlaps with the theoretical framework by Bourdieu, categories were formulated following Bourdieu’s theory of different forms of capitals. Coding was carried out at two different points in time (t1/t2) with eight weeks between the iterations. The comparison of the categories from four exemplary interviews resulted in an intracoder-consistency of 0.93 (k). The individual coding steps and the resulting categories were further validated through expert discussions with four colleagues who work in educational research. In addition, the categories were discussed with two teachers interviewed (T1 and T13).
|Time(s) of data collection||April 2020|
|Kind of sampling, kind and number of sample|
The sample was selected based on the neighbourhoods where the teachers work – 12 work in socially deprived settings, and 4 in privileged settings – and on their level of expertise. In contacting schools to compose the sample, extraordinary competencies in the field of teaching and learning were requested, for example, emphasized through special positions and tasks among the faculty.
Frohn, J. (2021). Troubled schools in troubled times: How COVID-19 affects educational inequalities and what measures can be taken. European Educational Research Journal.