During graduate school, I participated in an experimental seminar, “Literature+: Cross-Disciplinary Models of Literary Interpretation,” taught by Alan Liu. He asked students to form groups around topics of their choosing and perform analyses using digital tools on their materials. Most students shared similar research interests and organized their projects around a content-based theme. Our group represented four different disciplines and formed around our interest in digital tools, rather than content. Professor Liu created a toybox of links to various textual analysis tools that generated visualizations, translations, data about word counts, etc. Each of us took a tool in which we were to become “expert,” and applied that tool to data we had collected for our research.
In our recently published book chapter, “Interdisciplinary Knowledge Work: Digital Textual Analysis Tools and Their Collaboration Affordances” our motley team discusses how we applied these digital tools to our research goals and collaborative work. The most important lesson our collaborative experience taught us is that working together both pushed us and liberated us to experiment with our data and methods. In fact, much like our visualizations provide a big picture view of the texts we study, the multidisciplinary nature of our process forced us to step back and view our research at a macro-level. Although our collaboration began as a class project, playing together with technologies led each of us to new and significant understandings of our texts.