Learned gender

Social attributions have an enormous influence on the self-image of female and male actors in digitization. In the learning context, external and self-assessments in dealing with technology use and technical-rational understanding are established, which help to determine women's and men's actions and decisions. The meaning of “gender” in the context of learning and technology has been the topic of many social science, pedagogical and psychological research projects since the 1960s (among other things due to the advent of computers), usually initiated by politics or business. The project aims to examine these studies in terms of a secondary analysis of their empirical data collection in order to reflect on the quantifications and attributions of gender-specific experiences of technology. Through various forms of quantification, learning subjects could be increasingly fundamentally measured, viewed as a sum of learning characteristics, and thus classified as parts of a group (male/female). This project will examine how empirical research quantified and (re)produced gendered presuppositions (biases) through format, categorizations, classifications, and content. By analyzing questions that sometimes change and sometimes remain continuous, the project aims to demonstrate the persistent impact of bias that pre-structured respective answers through the formal and semantic logics of the questions. The project aims to investigate how statistical surveys, in interaction with presuppositions about “technology” and “gender,” contributed to the consolidation of gendered subjects of learning and thus provided supposedly objective facts for social and political decision-making processes.