A little audio plug for HIST 3CH3 (Catastrophic History), a new course on offer at McMaster University in January 2017. I’m excited about this new venture—and imagining new conduits for student discovery throughout the course. For McMaster students: there are still some spots available.
A dirty secret to start: course preparation is never as smooth as one would like. Behind in my work, I needed a big body of text to run through data visualization tools, so I turned to my dissertation, which I still had on my computer in .pdf. The work consisted of roughly 100,000 words—10,644 unique words. Modest for big data analysis like this, but sufficient for sharing with students in order to show them how digital tools can be used in historical analysis. Here’s a word cloud of the dissertation as a whole:
At a quick glance, this looks like a decent rendition of the work and its points of emphasis. But word clouds are simply snapshots in time and don’t provide any kind of chronological information. A good starting point, but limited. From here, I took the same text to voyant-tools.org to show my students how we could get under the hood a little more. The results surprised me a little. Not a lot, after I thought about it, but Voyant revealed some interesting evolutions within the text. Compare the relative and raw frequencies of my use of the words “science” and “environmental” throughout the dissertation in the images below.
About halfway through the dissertation, there seems to be a pretty clean transition from the history of science to environmental history. This is pretty consistent with the dissertation. The first two chapters engage Commoner’s participation in a number of scientific debates and his emergence as a scientist-activist. Heavy emphasis through these chapters considers scientists and their social responsibility, and investigates concerns over nuclear fallout (an issue that Commoner would later recall is what made him an environmentalist). The third chapter considers the Age of Ecology and scientists as public intellectuals in the developing environmental movement. This is the point where the blue line starts to climb and before the green line drops off. Eventually, I start to focus on the environmental movement as a whole and Commoner as an intellectual leader within that movement rather than as a scientist.
On a lazy morning—and buoyed by having played with some similar searches recently—I thought I could quickly pull Commoner references in The New York Times to see if I could draw any comparisons between my work and the primary source hits. Again: this is hardly a comprehensive or satisfactory methodology, but I think it provides sufficient material for working with undergraduate students as a means of showing them how historians might visualize and analyze bigger chunks of information.
“Barry Commoner” AND (science OR environment)
My search showed up in 252 articles. I elected to not use TV or radio guide references and a quick eye-test of article titles eliminated a number of non-relevant articles, so the total number of articles was reduced to 151. Too small to be a worthwhile dataset, but the articles totalled roughly 200,000 words, twice the number in my dissertation.
Here is the chronological distribution of the original search.
Not surprisingly, Commoner’s role as an environmental leader and outspoken activist reaches its apogee in the 1970s. His continuing work, his return to New York, and his presidential campaign likely contributed to his ongoing presence in the 1980s, even if he had technically “retired.”
Breaking up the newspaper findings into three sections—1950-1969, the 1970s, and the 1980s—the resulting clouds offer a story that is somewhat consistent with the Voyant trajectory shown above.
Commoner’s work in the 1950s and 1960s as a biologist, working on the Tobacco Mosaic Virus (for which he won the Newcomb Cleveland Award from the AAAS). This put Commoner within a ring of biologists informed about the developing events around heredity and the Watson-Crick discovery of DNA’s double helix. I should write about Commoner’s response to molecular biology at some point. But DNA, protein, and virus suggest this emphasis in the newspaper literature (life, too).
Another running theme in the newspaper articles and in the early stages of my dissertation is the treatment of social aspects of science. Too: Commoner’s outspoken opposition to funding for space travel, which he saw as a disconcerting expression of the military-industry complex and the Cold War arms race.
This first cloud also shows the beginning of environmental issues with “water” and some others. What else? This analysis is roughly consistent with the narrative I presented in the first three chapters of my dissertation/book (phew!).
Moving to the 1970s:
This second cloud shows a marked decline in “science,” “scientist,” and “university,” which suggests Commoner’s ascendance in environmental circles and his standing as a public intellectual.
In the third cloud, note the emphasis on “Carter” and “Reagan.” Perhaps the Reagan reference is not so surprising, but note that a goodly number of the Commoner references in the 1980s came from 1980 during Commoner’s presidential candidacy on the Citizens’ Party ticket (Harris refers to Commoner’s vice-presidential candidate, LaDonna Harris). The “Queens” reference is also indicative of Commoner’s retirement from Washington University in St. Louis and his move to CUNY Queens College (a return to his native New York City). Given my recent post, it’s also interesting to see “toxic” (in the bottom right corner) present in the 1980s.
One might also identify a change in environmental themes. “Atomic Energy Commission,” “atomic” and “radiation” in the 1950s and 1960s. “energy” in the 1970s; “recycling” and “waste” in the 1980s. “Environment”/”environmental” grow steadily in each word cloud. Clearly I prefaced this evolution in my dissertation and book—the benefit of looking backwards. And more. Again: limited as they are, I think clouds like these provide students with an interesting departure point for looking at big amounts of information, thinking about what might be present, and asking questions that will shape subsequent research. Play along: in the comments below, what evolving trends can we infer from the three newspaper clouds? What isn’t present, or surprisingly underrepresented?
This post draws on two lines of work. This fall, I have been introducing students to some (very) basic digital visualization techniques as a means of training them to ask historical questions. I have also been thinking further about the history of toxic fear—and whether a fear of toxic chemicals produced a distinct kind of fear during the Toxic Century. In A New Species of Trouble, Kai Erikson argues that the new, silent toxins of the post-World War II period “scare human beings in new and special ways, … [and] … elicit an uncanny fear in us” (144). I use Erikson as a departure point, and propose that it is time to examine toxic fear through an historical lens.
These two lines of work came together this week in my first year course on the Toxic Century (HIST 1EE3: The Historical Roots of Contemporary Issues). Working in groups of four or five, students have been tasked with identifying an appropriate keyword search, collecting ~500 newspaper articles in digital form, compiling them into a single, text-searchable file, and running them through some web-based reading and analysis tools. Groups were assigned a specific newspaper (for ease, we limited searches to 1950-1980 in The New York Times, The Washington Post, The Wall Street Journal, and The Globe and Mail, all readily available through McMaster University’s subscription to “Proquest Historical Newspapers”). ~500 articles constitutes a fairly small data set, but I am more interested in teaching the method and process than expecting very specific or accurate results.
Their assignment involves developing a series of word clouds in order to chart change and continuity in the Toxic Century’s vocabulary over time to see if their analysis can identify trends in that vocabulary. Each group would create a chronological suite of word clouds (1950s, 1960s, 1970s, for example) in order to “see” the articles they had collected. I recommended that students play with wordle for simple word cloud generation: I find it easy to use and it seems to generate some of the more aesthetically pleasing clusters. To better contextualize and quantify their results, I urged that they run the same material through Voyant-Tools, which offers some more sophisticated options. Building on this collaborative investigation and analysis, students will co-write a short paper on their findings. I should stress that these papers do not mean to offer anything but a bird’s-eye view of a singular primary source. The exercise is less about acquiring any conclusive historical understanding about a particular time or event. Instead, I introduce this process as a method of starting inquiry into a new topic (my third-year “Social History of Truth” class is doing something similar, but with scientific journals).
Which brings me back to toxic fear. To provide a mock example and case study for the class to take them through the assignment, I conducted a search for New York Times articles between 1950-1990 that adhered to the following criteria:
[toxic AND (fear OR anxiety) AND (chemical OR pollution)]
The search parameters were far from perfect, and I had to “weed” out some articles that debated marijuana use. But a cursory scan of article titles suggested there was not too much noise—non-relevant results that would interfere with the data visualization. I added the 1980s, since we had covered Bhopal and Chernobyl already in lecture, and I thought it would be interesting to see if we could “see” American coverage of international crises. But it’s probably just as well that I did. Of the 729 articles that came back, 504 (69%) were from the 1980s. Another 39 were from 1990. Remove “fear OR anxiety” from the search:
[toxic AND (chemical OR pollution)]
and The New York Times yields 5657 articles (of which a still surprisingly high 3535—62%—are from the 1980s. I haven’t done anything yet, but already I was surprised. While some literature engages the Reagan administration’s deregulation as a catalyst for swelling registration in environmental organizations in the 1980s, I had typically associated fear of toxic chemicals with the Age of Ecology writ large. Yes: Rachel Carson’s Silent Spring featured in the 1960s findings—and maybe my search parameters were skewed to leave out issues surrounding radioactive fallout. However, if The New York Times is at all representative of American print media, it would seem as though the 1980s was the decade of environmental fear (and toxic issues in general). Casting a wider net would be worthwhile. But even the more conservative Wall Street Journal, which returned only 168 hits for the first search including fear, had 122 of them (73%) come from the 1980s. Remove “fear OR anxiety” and you get 858 from 1240 articles (69%) from the 1980s.
Maybe this is simply media hype and marks a lexical transition in print journalism, but I’m not so sure. I have written about the rise and fall of the environmental jeremiad during the 1960s and 1970s, and argued that the effectiveness of alarmist rhetoric subsided during the 1970s. So it would seem out of place for media hyperbole on environmental fear to crescendo so dramatically in the 1980s. Something to investigate, though. On the one hand, perhaps this is just a sign of mainstream media catching up with a slow burning fire in American political thought. But it’s also possible that these results are not wholly surprising, even if the historical literature’s interest in the Age of Ecology tapers off somewhat after the energy crisis. We talk about the environment crisis as a post-World War II phenomenon, best articulated in Barry Commoner’s social activism, in Rachel Carson’s influence, and in the emergence of a number of public health concerns that emerged in the 1960s. And we typically associate the 1970s as a period of expansive environmental regulation in the United States—and, globally, as a key moment in the rise of contemporary global environmental governance. That’s the environmental crisis and its socio-political response. But we also know that the 1980s was punctuated by a series of intense environmental crises: Love Canal, Three Mile Island, Times Beach, Bhopal, Chernobyl. And perhaps these events prompted a more palpable recognition of interest and fear and anxiety surrounding toxins in the environment. Maybe I shouldn’t have been quite so surprised by the abundance of 1980s hits in my search.
Nevertheless, I spent yesterday afternoon focusing my efforts on the 1980s. This was quick and lazy work, and I only gave the files the most cursory of scrubs (and not satisfactorily: eliminating “New York Times” from the word clouds, for example, had the unhappy effect of problematizing: “Times Beach.” And I made the mistake of clearing “the” out of the text before I put it into Voyant. This produced “there” and “their,” which are prominent in some of the clouds (wordle automatically leaves out smaller words). As it happened, I had roughly 100 articles for every two years. I’ll spare you the detailed, more quantified analysis rendered in Voyant Tools. Here’s what each wordle-generated word cloud looked like.
It’s entirely likely certain that I’m working with too small a data set and too narrow a timeframe. But even here, I think there are opportunities for students to interpret and inquire. Dioxin features in 1982-1983 as a result of the Times Beach crisis; Bhopal and Union Carbide are (tragically) prominent in the 1984-1985 cloud. More useful for the undergraduate classroom is the opportunity to compare general topics, such as waste, water, air, etc. One can do a little of that with a preliminary eye- or smell-test with the clouds above. But this is where Voyant becomes a much more effective tool. It is possible to quantify and contextualize reference terms and compare their chronologies through the text. For instance, my New York Times articles for 1982-1983 contained almost 120,000 words (16,439 unique words). “Toxic” was present 270 times, “waste” 250 times, “health” 196 times, and “chemical” 180 times. All well and good.
But we can use Voyant to dig deeper and examine trends in the usage. For example, “dioxin” occurred 174 times. According to Google Books’ ngram generator, interest in dioxin increased through the 1980s and 1990s:
Back to Voyant, the chronology of dioxin references in my text from 1982-1983 looks like this:
The two spikes correlate with the discovery of dioxin and then the town’s evacuation. Which is to say that dioxin’s featuring in the 1982-1983 word cloud has a lot to do with Times Beach emerging as a national story. I’m learning with my students to become more proficient with Voyant, but it’s neat to play with. Voyant makes it possible to fiddle with the number of segments and analyze relative (rather than raw) frequencies. It is also possible to compare trends in terms:
That example is probably not instructive: since “chemical” was one of my search terms—and seems to experience mild spikes along with “dioxin”—I’m not sure what I’m learning here. And neither method shown here organizes the newspaper articles into an accurate chronology. The chronology is dictated by the raw number of articles and not divided into month-by-month sections, which might yield a different perspective. To wit:
Breaking the trend analysis into 25 segments (roughly one point for each month), it’s apparent that dioxin features too early (the story broke in December 1982). So the dumping large amounts of data into a reader does not necessarily return complete information for the historian. I could conduct a raw count of articles by month, of course, to determine the extent to which Times Beach dominated other issues during this two-year sample (it did). The wordle cloud also hints at some of those issues—Bhopal, above in 1984-1985, for example—but it does not indicate whether “dioxin” or “Bhopal” was used repeatedly within a small subset of articles or whether their prevalence is the result of a larger number of articles (or both).
But, still: too small and narrow a data set (though, arguably, this is a pragmatic start for in-class use at the undergraduate level). The work above could be bolstered with a range of newspapers that cover the United States. Having eliminated “New” and “York,” there are no references to city and state, though “Jersey” is present, and suggests regional coverage/emphasis of toxic issues. Perhaps midwestern newspapers such as The St. Louis Post-Dispatch or Chicago Tribune would return a greater number of relative hits (and emphasis) on Times Beach, Missouri, for example. And while adding to the raw data would be interesting, separating it geographically might also turn up some interesting variations in emphasis. Could we compare west coast reporting against east coast reporting, and what differences might be present? Of course, none of this precludes actually reading stuff! But it’s an interesting departure point that generates new and different questions. My less period-specific reading indicates that toxic fear exists and that it is galvanized by uncertainty and/or a lack of information. If that holds true under further and deeper scrutiny, what does that tell us about the 1980s if fear and anxiety increased? One knee-jerk reaction is to suggest that mass deregulation in the Reagan 1980s prompted less understanding and control over environmental problems. But Love Canal and Three Mile Island definitely fit into this story and they predate the Reagan administration. Perhaps this is a Superfund story—and the very idea of Superfund was enough to generate more toxic fear? Or, simply, the proliferation of crises prompted a distinct wave of environmental angst and fear.
Takeaway conclusions: we need to do more work that investigates environmental history in the 1980s. As I note evermore grey on my chin in the mornings, I’m reminded that the 1980s are receding in the rearview mirror, and it’s time we put that decade under the microscope. In American and global contexts, we know the basic story, but that narrative needs to be picked apart and complicated. Some good literature exists in environmental justice scholarship—and we should continue to expand on that—but we have little more to work with. The 1980s constitute a fascinating decade for environmental regulation agencies the world over. After the growth and (relative) successes of the 1970s, what happened in the 1980s? There’s also a distinct dearth of historical work on dioxin (Agent Orange and Vietnam notwithstanding).
I should emphasize that the above discussion of data visualization is (1) a teaching experiment, and (2) not a quantum shift in historical research. So far, I like the assignment and am drawn to the possibilities associated with coaxing first-year students into collaborative research and discovery (which can be tricky in a big survey course). But I don’t yet know what the results will be. Moreover, I do not mean to suggest that digital scholarship will transplant traditional archival research. But I do think visualization has helped me to shift my focus from a broader timeframe to a more concentrated examination of the 1980s—and to ask questions about how and why fear and anxiety proliferated during that decade.
Edit: On further analysis, I suspect the problem above is that “toxic” is the limiting term. A non-discriminatory search for “fear” in The New York Times finds only a modest increase in the word’s frequency:
Compare with “toxic”:
Could “toxic” be the problem? According to the ngram (which doesn’t relate to the NYT searches in any tangible way), “toxic” increased steadily through the 1970s:
Removing “toxic” from the search parameters raises some interesting perspectives, though. Searching for “pollution” AND “fear” changes the frequency of newspaper articles quite markedly.
But try again with “fear” AND “chemical,” and the trend indicates growth into the 1980s:
Does this make us less scared of pollution and more frightened by toxic chemicals? Or is this simply a shift in language? Or do our responses to environmental problems concentrate more specifically around toxic chemicals by the 1980s? And does this constitute some kind of evolution worth exploring in greater depth?
A word on teaching and ways to alter the classroom experience from my grant application.
I see a series of interwoven expected impacts on student learning:
1. A genuine investment in creativity & knowledge communication:
In general, the current approach to undergraduate assignments looks something like this. The instructor requires some form of written essay. The student works feverishly to meet the course expectations, mimicking (but not fully understanding) the complex and rigid rules of expository writing. The instructor grades the essay, providing comments on style and content. The student looks briefly at the instructor’s response before burying the paper in filing cabinet. The essay never sees the light of day again. This is unsatisfying.
Exploring data visualization and working with students to share their results more broadly encourages students to become more aware of potential audiences for their research (and not limiting their thought process to what they think the instructor wants to see). This invites students to take greater ownership over their work, and in my experience students have engaged much more willingly in more and better work habits as a result. I firmly believe that this approach treats students like emerging scholars and they are more likely to realize their potential because of that greater deal of respect.
2. A community of makers:
Building on that first point, I am intrinsically committed to the idea that the learning experience is enhanced when students become knowledge producers instead of just knowledge consumers. By turning students into makers of knowledge, it is possible to create the context in which active, self-directed inquiry and learning become the keystone of the educational experience. Through developing data sets and then critically analyzing them, students are creating the information they need. In producing visual representations of that information—through word clouds and flowcharts and infographics—they are also more involved in how their findings will be interpreted.
I see this as the fundamental characteristic of the Humanities in the 21st century: Whereas previously, research consisted of excavating—digging deeper and deeper into archives—today creating intelligent content is a constructive exercise. The data is available and constitutes a series of building blocks. The researcher and the collaborative teams of researchers get to build rather than burrow. The new, interactive classroom will encourage teamwork, experimentation, and inventive balancing acts to see what the data will and won’t yield.
3. A more holistic approach to problem solving:
I want to encourage Humanities students to learn at the bench, to use a concept taken from how the sciences are taught. In effect, the humanists’ digital lab is the new bench, a place where learning comes from doing, where students are encouraged to experiment and innovate. This environment invites students to get their hands dirty and to let the past (in the case of historical research and analysis) capture their imagination.
Thanks to Web 2.0, students have access to infinite amounts of information on their laptops and in their smartphones. The new intellectual challenge involves thinking critically about these new technological research tools and what the technology allows us to do. In many respects, our students are better prepared to ask and answer these questions than faculty. That constitutes an exciting teaching dynamic, where the instructor might adopt the business adage of being in command but out of control—allowing the students to “find” learning for themselves within the confines of a pre-arranged rubric. The danger endures, however, that these digital technologies threaten to make us the tools of our tools, to use Henry David Thoreau’s old phrase, but the central challenge to students is to break free from their tools—retain that capacity for traditional critical thought—and solve intellectual and technological problems in tandem. From the thought processes involved in coding and computational thinking, students will engage in more vigorous forms of problem solving, not just in their research and analysis, but also in the manner in which they communicate their findings.
I appreciate the irony in stressing the instruction of a number of quantitative research methods, but accepting that effectively evaluating the project’s results poses a bit of a qualitative quandary. In many respects, this project involves putting a teaching philosophy into practice. Similarly, gauging student success will need to be structured, on the one hand, quantitatively on their comprehension of the digital techniques, and qualitatively through the creative expression of their research communication and dissemination on the other. Whether or not this proves successful on a broader basis will be determined both by student enrolment and retention over a longer period of time and by evaluating the quality and quantity of the research data on the history of public health.
More from my Paul R. MacPherson Teaching Fellowship application:
“C’est la peur de la grande histoire qui a tué la grande histoire.”
Drosophila became the ubiquitous lab subject because of the confines of the academic semester. Its capacity to reproduce so prodigiously meant that Biology students could study multiple generations of their test subject over the course of a single, three-month term. Similarly, the digital humanities allow historians to capture greater data sets in shorter amounts of time. Whereas my own undergraduate research experiences were limited by the amount of microfiche I could stand to read within the time constraints of a semester’s term paper, data mining and mapping make it possible for today’s students to take on ever more ambitious projects if only we could bring the requisite technical skills to them. Moreover, it is now possible to shift the emphasis from data collection to data analysis—having them think about what their data is trying to tell them.
The vehicle for my project’s endeavour is an expansive history of public health, though the training guides for subsequent use may be applied more generally. My teaching and research interests live at the interstices of the histories of science and the environment, and themes in the history of public health are consistent with the curriculum I already have listed in the university’s Undergraduate Calendar. Writ large, questions of occupational health, hygiene, and environmental well-being offer an inexhaustible series of directions for student inquiry and on a scale previously unwieldy to scholars. As a topic, it lends itself to historical GIS mapping of various industrial diseases and cancer clusters, as well as textual analyses dating back to the 17th century. Students producing maps and timelines on the origins of specific environmental pollutants or the discoveries of health hazards stand to contribute not just to their education but to a scholarly reimagining of the field. Further, given McMaster University’s reputation for the health sciences, the history of public health points to History’s contemporary relevance, and might create opportunities for cross-campus collaboration.
During the tenure of the fellowship, I will identify discrete research projects on the history of public health, designed to introduce and develop digital humanities skills from Levels I to IV. The plan involves not just listing a series of disparate skills, but in establishing the most efficient build from one skill set to the next over a series of different courses. The instructional videos will be designed to aid students with little or no training in digital humanities to participate at each level so that they are not disadvantaged if they did not take the introductory course.
Yesterday I learned that I was named the Paul R. MacPherson Teaching Fellow for 2014-2015. This is nice news and very flattering; I’m honoured by the vote of confidence in my teaching, and especially pleased at the prospect of having time to devote to merging my teaching and research interests more fully. My application proposed integrating digital humanities techniques throughout my undergraduate curriculum (with a focus on the history of public health), while also preparing guides and directions for colleagues who might want to explore similar avenues.
Over the next few days, I will post bits and pieces from my application as a means of sharing my plans for the coming year. Digital Humanities (or DH) has become the buzzword du jour in scholarly circles, and it has become a funding priority, too. I remain a bit agnostic to much of the rhetoric surrounding its great promise, but I do see valuable applications in the classroom (as outlined below and in subsequent posts). I’ll return to this point, but I think much of the current literature and debate over DH—that it’s either the salvation of the struggling Humanities disciplines or the final nail in their coffin—is woefully misguided. I’m not sure DH needs to be quite so oppositional; rather, I see it as being complementary to traditional research inquiry rather than a singularly incompatible new direction.
But more on that in due course. In my proposal, I outlined a plan for DH development as well as exploring novel approaches to knowledge communication. I maintain a commitment to the traditional essay form and the importance of effective writing skills, but I think they can be supplemented by asking students to engage with design, aesthetics, and visual communication. I will expand on this in the blog over the course of the coming year.
But here’s the background and rationale from my proposal:
Big data is more than just an established trend in knowledge acquisition; it marks a seismic shift in the academy, in economics, and in culture. From social networks to demographic analysis to online media, complex methods of digital data collection dominate contemporary modes of knowledge production and consumption. No body of evidence is considered more compelling or persuasive than massive quantities of data. And more data: according to Wired magazine, we have entered the “petabyte age,” the consequences of which “force us to view data mathematically first and establish a context for it later.” This brave new world poses distinct challenges and opportunities for the future of Humanities teaching and learning.
The sheer weight of current data demands more than ever a humanist interpretation, but traditional academic disciplines have not adapted their methodologies rapidly in acknowledgment of these paradigm shifts. As a result, the Humanities appear out of touch with present methods of acquiring, analyzing, communicating, and disseminating information. This may be playing a role in a growing disenchantment among students about the value of a Humanities education. While I resist the notion that the foundational value of our disciplines has become less relevant, I appreciate the rationale behind the popular sentiment and recognize that we could be more proactive in blending the lifeblood of a Humanities education—critical thought, analysis, communication—with the technological possibilities inherent in the 21st-century knowledge economy.
Indeed, I read this tension as a golden opportunity to reinvestigate and reinvigorate our approaches to pedagogy and classroom instruction. It behooves us to think critically about how this new era of big data has transformed not just the world around us, but also how we study it. One option to deflect these criticisms of archaic programs is to develop a stronger profile in the digital humanities in our research and especially in our undergraduate teaching. The array of digital humanities practices can provide our students with new approaches to our traditional skill set and better prepare them for the emerging job market, which values independence, creativity, and intellectual versatility.
A rash of popular and scholarly literature highlights the digital revolution we are currently witnessing, and how it stands to transform education and the job market. While trends in this literature range from wildly enthusiastic to downright apocalyptic, the consensus would indicate that we have crossed the Rubicon. As the authors of Uncharted: Big Data as a Lens on Human Culture assert, “We have gotten used to a world in which we generate or obtain data and then analyze it however we want.” Similarly, books and articles on the digital humanities and its capacity to harness the new wave of infinite data is growing exponentially. In History circles, specifically, a renewed interest in “big” history—across time and space—is suggestive of the potential these methods offer.
My project involves re-visioning the manner in which knowledge acquisition and communication take place in the undergraduate History classroom. I propose integrating a suite of digital humanities practices across my undergraduate curriculum in order to provide a model for colleagues in my department and throughout the Humanities. Further, I mean to develop novel approaches to visualizing data in historical analysis—infographics, posters, and 3D media—working with students to articulate how design, aesthetics, and non-textual communication might open avenues to different forms of analysis and storytelling while reaching new audiences and fresh understandings. Whereas students are adept at consuming intelligent content through digital media, I propose to train them to create intelligent content in this new environment, drawing on the traditional research and analytical skills merged with newer computing techniques.
McMaster University is exceptionally well-positioned to become a leader in digital scholarship. The Lewis & Ruth Sherman Centre for Digital Scholarship constitutes an incredible resource for teaching and research using these new tools and for pushing the boundaries of how we might be communicate these findings. Similarly, MIIETL is at the forefront of these new approaches. While the resources exist, we could stand to see greater uptake within the more traditional Humanities disciplines. Through practicing digital humanities in the undergraduate classroom, I also propose to develop a series of tools and guides to support independent learning for both instructors and students.