Bringing the Digital into the Graduate Classroom

The impact of the digital on the humanities is often examined at the level of faculty engagement, scholarship, and ways of defining digital work in the twenty-first century. Meanwhile, the intersection between analog and digital heightens, deepens, and complicates what it means to participate in the academy. What happens when digital engagement becomes a core component of graduate-level pedagogy in the humanities? In this short chapter, I evaluate graduate offerings at the master’s level in the digital humanities (DH) at McGill University, reflecting upon our program and its connection to our department, with a particular focus on student projects, skill-building, and tools.1 Our emphasis on project-based learning provides students a way to strengthen their skillset in computational analysis of humanistic questions, which serves as an opportunity for sustained interaction with tools and skills—a helpful endeavor for those seeking work outside of the academy upon graduation.

The idea of a graduate degree in DH at McGill dates back to 2011 when the late Stéfan Sinclair was hired to spearhead new DH programs through coursework, events, interdepartmental collaboration, and other activities that fell under the broad rubric of digital humanities initiatives.2 Within the Faculty of Arts, the Department of Languages, Literatures, and Cultures (LLC) became the formal home of digital humanities, with DH faculty spread across departments.3 More widely, digital humanities initiatives included faculty members from music, religious studies, law, and the libraries. Currently, McGill houses an ad hoc master’s degree in digital humanities developed in collaboration between LLC professors—Sinclair, as well as Andrew Piper—and guided forward by Matthew Milner, then assistant director of the Centre for Digital Humanities.4 The program welcomed its first student in 2016 and has since built its cohorts from two to five on average as of 2022. In terms of positionality, I have been involved in DH programs at McGill since 2015 and served as the graduate program director from 2020 to 2022.

At the departmental level, DH courses are open to students from across the university, with a particularly high concentration from the Department of English.5 Ad hoc programs at McGill differ from standard graduate programs in that they typically draw from more than one discipline and thus require interdisciplinary committee approval on a candidate-by-candidate basis (remaining true to its Latin etymology “when necessary or as needed”). The program’s creation followed several years of discussion on what kind of graduate training and education would best meet an already diverse set of graduate options at McGill. Existing courses were canvassed for their suitability to form the basis of the program, and foundational and capstone courses were added. Digitally inflected graduate research cuts across the department, with students in Italian, Russian, Spanish, and German frequently choosing to pursue topics and methods that come from what would be considered the DH toolbox. One of the advantages of housing a DH program in a department that gathers students from many language homes and geographies is that multidisciplinary and intercultural research is part of its core mandate. Indeed, much of the work that our students and faculty undertake falls outside of the anglophone canon, with a particular attentiveness to decolonizing methods and projects.

In terms of structure, McGill’s ad hoc master’s in digital humanities is composed of one year of coursework and one year of thesis research. Students take an introductory course that is designed to familiarize them with some of the central practical and theoretical considerations of the field. They can then choose from an array of disciplines, ranging from computer science to anthropology. The courses are organized into five categories: cultural theories, data and text mining, quantitative and computational methods, spatial analysis, and sound and music.6 In the second year of the program, which is dedicated to thesis work, students collaborate with their advisors to build and pursue their research questions. In recent years, these projects have included using machine learning to examine a corpus of screenplays and test linguistic features and analyzing digitized migrant letters through computational text analysis with a particular attention to sentiment, topics, and social networks. We have benefited from the participation of several students from the Global South, including China and Nepal.

Examples of students’ project work show the variety of DH approaches that students can explore in their work. One of our students used Python to apply topic modeling and word embedding analysis (Word2Vec) in her exploration of cultural questions related to historical feminisms. She also carried out data mining and applied a decision-tree classification model to predict the adolescent fertility rate of several countries. This student carried out both projects during her first year of courses, a testament to the fact that project-based learning does not begin during the thesis year but is embedded in the toolkit students acquire in pursuing projects in their classes. In a student survey, this same student cited data mining and Python as essential to her work within data analytics, skills that she is confident will serve her in the private sector job she secured following graduation. Another student, who worked on the aforementioned migrant letter database, has considered pursuing work as a data analyst specializing in computational text analysis, which she envisions undertaking in the private or public sectors. But some DH students would like to stay in the academy; a third student expressed a desire to remain engaged in research upon graduation and investigate issues related to postcolonial DH, artificial intelligence, and tool sustainability.

Among the benefits that flow between both our ad hoc cohort and the humanities graduate community at large is the creation of a culture in which digital methods and research are welcome and increasingly the norm, evidenced by the fact that projects on text mining, web analytics, topic modeling, and metadata analysis are prominent throughout LLC. To cite a few examples, one PhD student in Hispanic studies engaged in digital research web analytics to examine how Latin American audiences and partners of the Biodiversity Heritage Library, an online archive of digitized global literature on biodiversity, engage with historical archives and create content.7 She mapped the selection and classification of texts using GIS and visualizations in Tableau, while performing topic modeling analyses (with MALLET) to interrogate how concepts of Latin America and biodiversity are constructed. Another PhD student in German studies worked with a dataset from the German National Library to apprehend why certain literary texts are translated over others and whether there might be stylistic or aesthetic consequences to wide-scale translation of German literature that could shape how fiction is written. This student utilized topic modeling and text mining methods including tagging, extraction, and matching to pursue her research questions. Meanwhile, a PhD student in Italian studies completed work on the Italian countercultural collective Wu Ming, including analysis of their online presence and their use of Twitter hashtags for political purposes. Another Hispanic studies student examined a corpus of Ibero-American short films using metadata modeling to better approach the commonalities and characteristics of this cultural database. She drew on text-based information such as tags, paratext, and keyword descriptors in databases and festival programs online to probe nationality, distribution, and impact. Many of these students were first introduced to theoretical frameworks and the application of computational methods to cultural questions in our introductory seminar, and their work speaks to the value of bringing computational mixed methods from the digital humanities to bear upon projects and disciplines across languages and fields of study.

Our experiences in running and establishing the master’s program speak directly to the view that engaging in sustained, multiyear digital research allows students to refine their computational skills and that said skills can be primarily acquired during their studies. In line with the scholarship, many students plan to pursue opportunities outside of the academy, in text analytics, archival work, and digital curation jobs in national and international libraries (Opel and Simeone, “The Invisible Work”). These experiences speak directly to some of the pushback experienced when presenting the idea of graduate programs in digital humanities—that is, that there is no clear benefit to longer-term engagement with digital methods and that the marketability of the degree is poor (McCarty, “PhD in Digital Humanities”). Given the shift toward data science, digital archival work, and text analysis in the private and public sectors, we hope to remain dynamic in how we meet students’ needs. With this in mind, we are actively creating a one-year master’s program that includes two semesters of DH labs and culminates in a summer capstone project. This twelve-month, nonthesis MA will be the center of a concentrated, project-based graduate program that will offer students with varying backgrounds an entry point into using digital tools and data analysis on humanistic research questions. Our nonthesis program will stress supervised, hands-on, collaborative training in a lab setting where students develop knowledge that is then applied to their capstone projects.

In concluding this brief chapter, I would like to return to some core questions and raise others. Many of the case studies I discuss above demonstrate engagement with digitally inflected projects across a semester, a yearlong thesis, or a multiyear dissertation. However, the length of study is but one factor worth examining when looking at DH graduate work. The creation of a shorter, project-based program that focuses on labs and a capstone is one of many modes of in-depth, intense training for students eager to engage with digital methods and critical data science. At the same time, there are challenges at the level of faculty skill building in digital humanities, given the need to supervise and train students around a diverse set of digital tools. Although summer training programs in digital methods including the Digital Humanities Summer Institute and the Digital Humanities Research Institute certainly offer options, it is inevitable that graduate programs in DH need to rely upon many disciplines and colleagues on a project-by-project basis. This is equally important in the area of assessment, as digital projects often require interdisciplinary collaboration to best evaluate their quality at varying intervals. In our engagement with our students and our vision for the future, project-based learning is at the heart of our pedagogy, whether it be in an individual course, a graduate thesis, DH labs, a dissertation, or potential capstone projects. In many ways, our students benefit from the multilingual, varied methodological landscape of our department in that collaboration is not a choice but an obligation of conducting research in an intercultural, multidisciplinary department.