Gender is being done – almost permanently. And it is the ‘almost’ we are interested in. Gender is culturally produced by using or misusing the male/female-distinction. It is so ubiquitous because it is much easier to use than more complex social categories. Taking the sex distinction one can ascribe differences to nature and that’s mainly it. To question the social position (age, education, class etc.) makes things very complicated. The gender difference would however not be so forceful, if we did not actively adapt our behaviour and our ‘will to knowledge’ to this category – referring to dress, haircut, attitude to technology etc. "Not only do we want to know the sex category of those around us (to see it at a glance, perhaps), but we presume that others are displaying it for us, in as decisive a fashion as they can." (West/Zimmerman 1987) And we also obey these expectations. The attribution of technical competencies to the different sexes is such a way of doing, performing, or conceiving gender. Because of its relation to other deep rooting differences like culture/nature, reason/emotion we can in a historical perspective even speak of a co-construction of gender and technology (Wajcman 2004). The coupling of the sexual difference with enthusiasm for or aversion against technology is however arbitrary. Though in some national cultures computers are or have been functioning as a water shed for gender. In Germany we even have or had ‘computer-angst’ as a mainly female phenomenon. However this anxiety is reduced by the usage of computers. The gender bias of IT is also much discussed in relation to e-learning: are there different usage patterns, does IT differentiate the access to education, is gender specific learning success mediated by the use of e-learning elements (Astleitner/Steinberg 2005)? We argue that it is also a question of how e-learning has to be used. As expression and social recognition of gender is not only a by-product but meaningful, to express a certain relation to IT can be a means to reach this goal. However if 'doing gender' has a benefit, it can also have costs. Further benefit-cost-structures are context dependent, i.e. there are contexts in which it is more or less arduous to communicate gender. Our hypothesis in regard to e-learning is thus: the more students are forced to use certain e-learning elements – both in regard to study administration and learning process – and the more standardized the possible usage of theses elements is, the lesser is the bias of gender and technology in this context. If an e-learning practice is just normal – and normality can be enforced by interface design and lack of offline alternatives – gender cannot be as easily done in this context. In the framework of a joint research project funded by the German Research Foundation (DFG) we are going to validate theses hypotheses by comparing four different academic e-learning scenarios. We are using guided interviews, group interviews (women, men, mixed) and log-file-analysis in order to reconstruct the (social) ‘doing gender’ in relation to the technological contexts und to compare it with actual usage patterns.

guided interviews, group interviews, log-file-analysis in four different e-learning contexts

From our research we expect a correlation between the measure of the 'need to use' a certain e-learning setting and the (inverse) measure of (technology biased) gender differentiation.