Not Coding Alone: Teaching the Collaborative Habits of DH in a MOOC

IntroductionOnline courses present special challenges to the teaching of the digital humanities, particularly having to do with the collaborative nature of the discipline. In the last decade, as digital humanities pedagogy has emerged as a coherent and visible discipline in its own right (Hirsch 2012), the requirement that “students need to develop their collaborative and interdisciplinary skills” has arisen as a central concern (Mahony and Pierazzo, 215).This poster describes the collaborative and project-based approach of our course, Digital Humanities in Practice, a forthcoming HarvardX MOOC (June 2020). Our aim is to embody the pedagogic ethic of “seamfulness” advocated by Mauro et al. in a recent special issue of DHQ, productively exposing the messy process of development. We do so in a number of different ways: 1) the course is team-taught by a scholar, a technologist, and a librarian to demonstrate the affordances and difficulties that arise when the instructors’ different competencies are knit together; 2) we encourage our students to make mistakes and we model doing so ourselves, so they can see how the progress of a digital project often does not follow a straight line, and 3) while the arc of the course draws the complete narrative of a digital project -- from corpus acquisition to publication and project maintenance -- the pedagogical patterns of the course reinforce the iterative nature of digital work.Project BackgroundIn his own research on eighteenth-century intellectual history, Stephen Osadetz assembled a team of computer technologists and librarians that created Open Books (conceptsearch.fas.harvard.edu), a concept-search engine for Gale's Eighteenth Century Collections Online database. Based on the success of this project, Osadetz and his team were asked to develop a practical course focused on text mining that embodies the collaborative nature of their work.Our team held a number of focus groups with students who had enrolled in the original course, and Cole Crawford conducted a survey of over 100 DH graduate certificate and degree-granting programs. The results indicated a substantial growth in residential DH programs at all levels over the past five years, but an almost complete absence of online DH instruction.Pedagogical MethodThe course walks students through each part of a text analysis project, from acquiring data through presenting results. Units follow a set rhythm, which is meant to ease students into each new skill. After a brief assignment and video to frame what is to be taught, each unit breaks into two substantial parts: one guided, in which students follow along with an instructional video in whatever platform we are using (Jupyter Notebook, OpenRefine, Tableau, etc.); and the other self-guided, in which they practice and extend what they have learned, individually and with peers through a discussion board. These second, more exploratory assignments (on, for example, metadata enrichment with Wikidata, or author attribution, or LDA) will be peer-assessed. A preliminary study suggests that peer grading and professors’ grading is highly correlated (Kaplan et al., 2014).ConclusionWe have attempted to turn these difficulties of creating a comprehensive course on digital methods to our advantage by designing a MOOC that embraces the ethics of seamfulness and collaboration, addressing itself to different types of audiences: scholars embarking on digital research projects, but also technologists and librarians who increasingly facilitate this work. We believe this course may satisfy a crucial need that may be appreciated by many people interested in DH but intimidated by coding: a playful but intellectually challenging introduction to the field that tells students, above all, that you don’t have to do everything on your own.