CLS INFRA: The New Wave: Charting Skills Gap in Training for Computational Literary Studies

We have explored gaps in teaching of research skills for computational literary studies to inform the CLS INFRA project’s own approach to training schools and chart the territory to gain broader insight into current CLS teaching practices. To understand supply we have manually annotated a sample of European university courses in Digital Humanities and summer school workshops. To index demand we set up an online survey to ask the community to evaluate a set of predetermined ‘skills’ based on its perceived future prospects in the field and teaching (1-5 scale response, 118 participants). The survey also offered a chance to observe the demographic structure of the CLS community. The prevalence of early career respondents indicates a new generational wave within computational literary studies. Participant gender was balanced, although introduction of variables such as career stage, self-reported proficiency, and discipline demonstrated skewness. Researchers who work in the field of CLS also report more experience in computational methods, which suggests that these go hand in hand in current practice. Despite the gap in skills education being more general in nature, we identified areas of heightened interest. These are the skills that make up the backbone of computational research: from designing the study to text collection, to multivariate analysis and statistical modeling. Survey responses reiterated that the current gap in schooling is qualitative rather than quantitative. Moreover, there was a consensus among participants that the institutionalized training of a new generation of researchers is instrumental to disciplinary advancement of CLS.