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At the Digital Pedagogy Lab Institutes where we’ve taught, there’s one exercise in particular we return to again and again. In our “crap detection” exercise (named for Rheingold’s use of the term), participants use a rubric to assess one of a number of digital tools. The tools are pitted, head to head, in a sort of edtech celebrity deathmatch. Participants compare Blackboard and Canvas, for instance, or WordPress and Medium, Twitter and Facebook, Genius and Hypothes.is. We start by seeing what the tools say they do and comparing that to what they actually do. But the work asks educators to do more than simply look at the platform’s own web site, which more often than not says only the very best things (and sometimes directly misleading things) about the company and its tool. We encourage participants to do research — to find forums, articles, and blog posts written about the platform, to read the tool’s terms of service, and even to tweet questions directly to the company’s CEO.

Here’s the rubric for the exercise: Who owns the tool? What is the name of the company, the CEO? What are their politics? What does the tool say it does? What does it actually do? What data are we required to provide in order to use the tool (login, e-mail, birthdate, etc.)? What flexibility do we have to be anonymous, or to protect our data? Where is data housed; who owns the data? What are the implications for in-class use? Will others be able to use/copy/own our work there? How does this tool act or not act as a mediator for our pedagogies? Does the tool attempt to dictate our pedagogies? How is its design pedagogical? Or exactly not pedagogical? Does the tool offer a way that “learning can most deeply and intimately begin”? Over time, the exercise has evolved as the educators we’ve worked with have developed further questions through their research. Accessibility, for example, has always been an implicit component of the activity, which we’ve now brought more distinctly to the fore, adding these questions: How accessible is the tool? For a blind student? For a hearing-impaired student? For a student with a learning disability? For introverts? For extroverts? Etc. What statements does the company make about accessibility? Ultimately, this is a critical thinking exercise aimed at asking critical questions, empowering critical relationships, encouraging new digital literacies.

Here are a few specific examples you can apply to your instructional design process to help learners with metacognition: Model the metacognitive process during instruction (or in one-on-one consultations) to ask and reflect on big picture questions such as: “What questions can you answer with this tool?” “What can you not do with this tool?” Keep in mind some answers may be simple (e.g., this tool can only work with data in this way, so it is excluded automatically). Also, “Did I get the results I expected? What could I have done differently?” Start with inquiry and build conversations based on the learner’s answers. “Is it the data that does not work? Or is the research question fundamentally wrong to begin with?” Collaborate with faculty to teach together, modelling your practices while demonstrating a specific tool. This could include thinking aloud as you make decisions so learners can self-correct assumptions. Also, be aware of your own expert bias so you can demonstrate how to clear obstacles. Ask learners to specifically define what is difficult for them during the process of instruction. Digital humanities tools are complex and are based on complex methodologies and research questions. By constructing opportunities for learners to self-question as they move from one task to another, they learn to self-assess their progress and adjust accordingly. There are several instructional design activities that promote metacognition: think-pair-share, one minute paper (“share a key concept learned” or “what comes next?”), and case studies.

There are specific strategies we can implement to help learners escape the recursive spiral of the liminal state they experience while managing complex digital projects: One of the most challenging aspects of teaching digital tools is forgetting what it is like to be a novice learner. Sometimes being a near-novice oneself helps you better prepare for the basic problems and frustrations learners are facing. But recognizing liminality is a reminder to you as a teacher that the learning process is not smooth, and it requires anticipating common difficulties and regularly checking in with learners to make sure you are not leaving them behind. When meeting with learners one-on-one, make sure to use your in-depth reference interview skills to engage in methods discussions. When a learner is in the liminal state, they are not always able to “see the forest for the trees.” Your directed questions will illuminate the problems they are having and the solutions they had not seen. Pay close attention to the digital humanities work and discussions happening on your own campus, as well as across the academic community. Working through the liminal space may require helping learners make connections to others facing similar problems. Also follow online discussions in order to point your learners to a wide variety of group learning opportunities, such as the active digital humanities community on Slack.9 When designing instructional opportunities, such as workshops and hackathons, pay particular attention to outreach strategies that may bring like-minded learners together, as well as diverse voices. For example, invite the scholar whose project was completed last year to add a more experienced voice to the conversation. By encouraging the formation of learning communities on your campus, you are creating safe spaces to help learners navigate the liminal state with others who may be on the other side of struggling with specific digital project issues. In designing instructional activities, guide learners through visualization exercises that help to identify “stuck” places. Making graphic representations of one’s thoughts (e.g., concept maps) can highlight areas that require clarification.

These studies demonstrate some evidence for the existence of disciplinary differences in technology adoption, which suggests that there is not a homogeneous form of “scholarship” within academia.

Pinker also refuses to engage seriously with the major philosophical critics of the Enlightenment such as Nietzsche, Heidegger, Adorno, and Foucault. He offers a ludicrous summary of their thought, claiming that they “are morose cultural pessimists who declare that modernity is odious, all statements are paradoxical, works of art are tools of oppression, liberal democracy is the same as fascism, and Western civilization is circling the drain.” The first and last statements are just crude ways of saying that they raise serious questions about the Enlightenment, which, given their influence over many years, should make them essential targets for Pinker. In fact, except for perhaps Heidegger, all of them are best seen as Enlightenment thinkers, extending its critical project to some of the Enlightenment’s own intellectual weaknesses. Moreover, none of them would assert that all statements are paradoxical or that works of art are tools of oppression; and only Heidegger might be inclined to equate fascism with liberal democracy. But even if these crude slogans were acceptable summaries of these thinkers’ conclusions, rejecting those conclusions would require careful consideration of their detailed analyses and arguments.

Although the phrase sometimes refers to issues surrounding copyright and open access and sometimes to scholarship analyzing the online world, digital scholarship—emanating, perhaps, from digital humanities—most frequently describes discipline-based scholarship produced with digital tools and presented in digital form.

Though the recent popularity of the phrase digital scholarship reflects impressive interdisciplinary ambition and coherence, two crucial elements remain in short supply in the emerging field. First, the number of scholars willing to commit themselves and their careers to digital scholarship has not kept pace with institutional opportunities. Second, today few scholars are trying, as they did earlier in the web's history, to reimagine the form as well as the substance of scholarship. In some ways, scholarly innovation has been domesticated, with the very ubiquity of the web bringing a lowered sense of excitement, possibility, and urgency. These two deficiencies form a reinforcing cycle: the diminished sense of possibility weakens the incentive for scholars to take risks, and the unwillingness to take risks limits the impact and excitement generated by boldly innovative projects.

When infrastructure is understood as an irrational social formation, emotional labor tends to compensate for a perceived lack of resources. Scholars who are used to the invisibility of traditional library services, for instance, find that digital projects expose hierarchies and bureaucracies that they don’t want to negotiate or even think about, and the DH librarian or one of her colleagues steps in to run interference. Why can’t the dean of libraries just tell that department to create the metadata for my project? After all, they already create metadata for the library’s systems. Why can’t web programming be a service you provide to me like interlibrary loan? I thought the library was here to support my scholarship. Why can’t you maintain my website after I retire–exactly the way it looks and feels today, plus update it as technology changes? In some conversations, these questions may be rhetorical; it may take emotional labor to answer them, but doing so exposes the workings of the library’s infrastructure–its social stack.

How does DH fit within this megastructure? According to some critics, DH is part of the problem of the neoliberal university because it privileges networked, collaborative scholarship over individual production. If creating a tool (hacking) or using computational methods has the same scholarly significance as writing a monograph, then individualized knowledge pursued for its own sake, the struggle at the heart of humanistic inquiry, is devalued. Yet writing a book always depended on invisible (gendered) labor in the academy. Word processing, library automation, and widespread digitization are just three examples of the support labor for traditional scholarly work that Bratton’s globalized technology Stack has absorbed. (And we know that the fruits of that labor are in no way distributed equitably.) What has changed in the neoliberal university is that the humanities scholar becomes one more node in a knowledge-producing system. Does it matter, then, whether DH work produces ideas or things, critics say, if all are absorbed into a totalizing system that elides the individual scholar’s privileged position? This is of course a vision of scholarship that is traditionally specific to the humanities; lab science and the performing arts, for example, have always been deeply collaborative (but with their own systems of privilege and credit).

There is a real lack of understanding, even among students and researchers, as to the extent to which their on-line activities are tracked. Libraries could do much more to educate the campus community as to the importance of ad-blockers, VPNs, and tools such as Tor and Tails.