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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.

Video games, like work, are basically a series of quests comprised of mundane and repetitive tasks: Receive an assignment, travel to a location, overcome some obstacles, perform some sort of search, pick up an item, and then deliver it in exchange for a reward—and, usually, another quest, which starts the cycle all over again. You are not playing the game so much as following its orders. The game is your boss; to succeed, you have to do what it says.

Instead of working, they are playing video games. About three quarters of the increase in leisure time among men since 2000 has gone to gaming. Total time spent on computers, including game consoles, has nearly doubled. You might think that this would be demoralizing. A life spent unemployed, living at home, without romantic prospects, playing digital time wasters does not sound particularly appealing on its face. Yet this group reports far higher levels of overall happiness than low-skilled young men from the turn of the 21st century. In contrast, self-reported happiness for older workers without college degrees fell during the same period. For low-skilled young women and men with college degrees, it stayed basically the same. A significant part of the difference comes down to what Hurst has called "innovations in leisure computer activities for young men." The problems come later. A young life spent playing video games can lead to a middle age without marketable skills or connections. "There is some evidence," Hurst pointed out, "that these young, lower-skilled men who are happy in their 20s become much less happy in their 30s or 40s." So are these guys just wasting their lives, frittering away their time on anti-social activities? Hurst describes his figures as "staggering" and "shocking"—a seismic shift in the relationship of young men to work. "Men in their 20s historically are a group with a strong attachment to the labor force," he writes. "The decline in employment rates for low-skilled men in their 20s was larger than it was for all other sex, age, and skill groups during this same time period." But there's another way to think about the change: as a shift in their relationship to unemployment. Research has consistently found that long-term unemployment is one of the most dispiriting things that can happen to a person. Happiness levels tank and never recover. One 2010 study by a group of German researchers suggests that it's worse, over time, for life satisfaction than even the death of a spouse. What video games appear to do is ease the psychic pain of joblessness—and to do it in a way that is, if not permanent, at least long-lasting. For low-skilled young men, what is the alternative to playing games? We might like to imagine that they would all become sociable and highly productive members of society, but that is not necessarily the case.

A military shooter might offer a simulation of being a crack special forces soldier. A racing game might simulate learning to handle a performance sports car. A sci-fi role-playing game might simulate becoming an effective leader of a massive space colonization effort. But what you're really doing is training yourself to effectively identify on-screen visual cues and twitch your thumb at the right moment. You're learning to handle a controller, not a gun or a race car. You're learning to manage a game's hidden stats system, not a space station. A game provides the sensation of mastery without the actual ability. "It's a simulation of being an expert," Wolpaw says. "It's a way to fulfill a fantasy." That fantasy, ultimately, is one of work, purpose, and social and professional success.

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.

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).

Our medical systems have terrible Internet security… MRI machines you can connect to with USB that still have “admin:password” to gain root access. That’s horrifying, sure, but that’s not an attack at scale. More frightening: we’re busily uploading all our medical records to the cloud. Take down that cloud, and no patients can be treated, because nobody will know what they have, what meds they are on. Software swallows your insulin pumps and your pacemakers. To kill people, all you need is to hack that database, or simply erase it or block access to it. After all, we don’t tend to realize that in an Internet of Things, humans are just Things too. As this software monster has encroached on stuff like election systems, the common reaction has been to go back to paper. So let’s consider a less obvious example. We should be going back to paper for our libraries too! We’ve outsourced so much of our knowledge to digital that the amount of knowledge available in analog has dropped notably. There are less librarians in the fewer libraries with smaller collections than there used to be. If the net goes down, how much reference material is simply not accessible that was thirty years ago? Google Search is “critical cultural infrastructure.” How much redundancy do we actually have? Could a disconnected town actually educate its children? How critical is Google as a whole? If Google went down for a month, I am pretty sure we would see worldwide economic collapse. How much of the world economy passes through Google hosting? How much of it is in GMail? How much is dependent on Google Search, Google Images, Google Docs? The answer is a LOT. And because financial systems are now also JIT, ten thousand corporate blips where real estate agencies and local car washes and a huge pile of software companies and a gaggle of universities and so on are suddenly 100% unable to function digitally (no payroll! no insurance verification!) would absolutely have ripple effects into their suppliers and their customers, and thence to the worldwide economic market. Because interconnection without redundancy increases odds of cascades.

But just as critically, governments and state actors seem to be the source of so many of the problems precisely because the Internet is now too many forms of critical infrastructure, and therefore too juicy a target. If software eats everything, then the ability to kill software is the ability to kill anything. Net connectivity becomes the single point of failure for every system connected to it. Even if the Net itself is designed to route around damage, that doesn’t help if it is the single vector of attack that can take down any given target. It’s too juicy a target for the military, too juicy a target for terror, too juicy a target for criminal ransom. The old adage goes “when they came for this, I said nothing. When they came for that…” — we all know it. Consider that the more we hand gleefully over to the cloud because we want convenience, big data, personalization, and on, we’re creating a single thing that can be taken from us in an instant. We’ve decided to subscribe to everything, instead of owning it. When they came for your MP3s, your DVDs, fine,. not “critical infrastructure.” When they came for your resumes, OK, getting closer.

As we rush towards putting more and more things “in the cloud,” as we rush towards an Internet of Things with no governance beyond profit motive and anarchy, what we’re effectively doing is creating a massive single point of failure for every system we put in it.

In my last year’s analysis of the MOOC space, I concluded that there’s been a decisive shift by MOOC providers to focus on “professional” learners who are taking these courses for career-related outcomes. At the recently concluded EMOOCs conference, the then CEO of Coursera, Rick Levin, shared his thoughts on this shift. He thinks that MOOCs may not have disrupted the education market, but they are disrupting the labor market. The real audience is not the traditional university student but what he calls the “lifelong career learner,” someone who might be well beyond their college years and takes these online courses with the goal of achieving professional and career growth.

One of the lessons I learned from running Class Central is that to make money, you need to make others money. By targeting professional learners, MOOC providers are trying to exactly do that. To better serve this audience, every MOOC provider has launched products that range from tens of dollars to tens of thousands of dollars. As a professional learner, I feel a certain amount of comfort knowing that high-quality educational material exists for skills that I would want to learn in the future. But if you are true lifelong learner—the ones that helped start all the hype in the first place—the MOOC experience has largely been reduced to basically a YouTube playlist with a cumbersome user interface. Unless, of course, you are willing to pay.

One problem is that participation is largely taken for granted and under theorized in many classrooms. The way we make use of a term like participation is in need of rescuing: moving away from a limited view of participation as it is often linked to motivation, engagement, or hand-raising and toward the view that participation as a concept is more generative when connected to the idea of membership in communities of practice (Wenger, 1998). Our limited view of participation is evident by simply turning to the language included in most syllabi: often, syllabi list “participation points” as part of the grade of the course. I find this to be an odd way to think about participation. What we often mean is that we will give students some points for “talking in class” and “raising their hands.” But demonstrating engagement by hand-raising and talk are fairly limited views of participation, and in fact, these ways of being are more connected to performance — acting like a student — than participation. We certainly want students to participate more than 10 percent, or even half, of the time. Are they participating when they are listening and pondering the ideas of their peers? Of course they are, but how do they demonstrate that? In thinking about course design, we should consider how students become members of our classroom community and our disciplines. Social media sites can open up other avenues for participation, and further, connect students to communities of practice outside our classrooms that they hope to enter.

Although sometimes confused with digital scholarship centers, digital humanities centers are often specialized research centers led by a group of faculty and serving only select disciplines rather than a broad campus community. Also, libraries often play only a peripheral role in digital humanities centers.1 In contrast, libraries or IT organizations have a key role in digital scholarship centers.

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.

Scholars with digital projects often need to explain both their work and to justify the field of the digital humanities itself.

In short: we are on the brink of a tipping point in history, where blogging is going to become the norm for the initial exchange of ideas.

Occasional training tool and/or the future of high end entertainment — just possibly. But, hey, no one likes to feel sick at the movies. Feeling like you want to barf is only a good use of your time and energy if you’ve eaten something that might otherwise kill you. The wider question in the gaming space, which excels at entertainment and escapism, remains how big VR might get when the hardware isn’t so pricey and clunky, and when investing time and energy in building compelling content can start to look like less of a sinkhole prospect for developers who can now be seen pulling their horns in. These same types of content makers may well be having their heads turned by the potential of AR gaming. Which can, as noted above, already point to the existence of essential content generating wild excitement among millions of consumers. Rather like the solar eclipse, AR has been shown turning masses of heads and even gathering huge crowds of like-minded folks together in public. For now there is simply no argument: AR > VR.

As TechCrunch’s Lucas Matney noted: “Over the past several months it’s become clear that the war is no longer HTC and Oculus trying to discover who is Betamax and who is VHS, now they’re just trying to ensure that high-end VR doesn’t turn out to be LaserDisc. Though few of the big players are keen to readily admit it, many investors and analysts have been less than thrilled with the pace of headset sales over the past year.” The bald fact that neither HTC nor Facebook/Oculus has released sales figures for their respective VR headsets speaks volumes. (Analyst estimates aren’t generous, suggesting <500k units apiece.) Sony did put out some sales figures for its Playstation VR headset in February which caused some initial excitement — with the company claiming 915,000 units sold since October 2016. But by June that figure had merely drifted past 1M.