Remembering and forgetting

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Lots of people keep diaries. My wife’s grandmother kept a record of nearly every day of her life, preserved in perfect journals to which (I am told) she sometimes referred in order to refute something her husband said. I do not know if this is true, having seen no actual record of it, but I take it on good authority that this would sometimes happen.

Many people, myself included, are also keeping these web-journals or web-logs, both in an effort to communicate with others and to chronicle the present. They make for great records of what one was thinking at a given time. Smaller snippets of virtual remembering are also embedded in various social networks – what I thought about the latest cat meme, the sardonic comment that really didn’t come off about some piece of inane news, or the virtual argument I started with an acquaintance I haven’t seen since 1999.

My gmail account has so much storage that I no longer need to delete messages. Everything is archived and instantly searchable. With online note-taking tools, I can quickly unearth nearly anything I was thinking in the last several years. We appear to be rapidly approaching a time when life itself will be streamed live and recorded for posterity (see Google Glass). Anything that hits the web will likely be kept in perpetuity.

I recently finished a book about the aftermath of the American Civil War in which the author argued that specific kinds of forgetting and a creative remembering helped to bring the North and South back together, at least politically, after the war. “Both sides were valiant in battle, and both sides fought for that which they believed” – this was the constructed memory of the war. If they had YouTube back then, I doubt the fiery political speeches that each side made would have been forgotten.

We all tell stories about ourselves, and remembering itself is often an act of creativity. Our brains are wired to see patterns where they might not exist, to make our past more linear than it actually was, and to de-emphasize difficult or painful episodes. We tell stories, in the process re-encoding those memories and subtly changing them. We experience hindsight bias, the feeling that we knew exactly what was going to happen in a given situation, but only after the fact. We experience cognitive dissonance, or something akin to “making the best of it,” in which we tell ourselves that a decision that we made or a situation in which we find ourselves really is what we wanted all along. We rationalize our decisions to ourselves and others by remembering in creative ways – and by selectively forgetting or downplaying conflicting data.

All of which leads me to wonder if the mass “archivization” (to coin a neologism) or near-perfect, instantly-accessible, fully-searchable record of everything we have said and done is really as wonderful as we seem to think. Is there something to be said for uncertainty, especially the uncertainty of the past and the creative (and, perhaps, psychologically beneficial) ways in which we remember? Or is this simply the next way humanity will augment its intellect through computers?

Innovating within constraints

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I have been reading some pretty heady stuff recently, especially around creativity and innovation. I have been thoroughly convinced of the additive and connective nature of innovation – the idea that innovative thinkers are usually those who can combine existing elements in novel ways, thereby advancing the field in which they work (see Everything is a Remix for some great examples). I find this a compelling way to think about innovation. Rather than the isolated genius struck by a new thought as if by lightning, innovation by connection and addition allows us lesser mortals to practice the type of thinking that fosters innovation and actually improve at it. The fact that this idea is strange – the idea of “getting better” at creativity – is itself a sign of how deep the isolated genius idea permeates our perception of innovation.

But almost at the same time that I think this, I find another thought interrupting me: we all work within constraints. I want to be very clear here: I think some innovations do (and should) break open constraints and expand the boundaries of the possible. One look at the types of connected networks we’re building for ourselves should be enough to convince just about any one of this fact. But in other contexts we have defined constraints out of which we cannot innovate ourselves. Work constraints, budget constraints, time constraints (the list goes on and on) all help delineate the space in which we can innovate.

I find myself wondering if innovating within defined constraints can be understood as a subset of this idea of additive or connective creativity. I think that finding innovative ways to accomplish goals that seem out of reach certainly fits this paradigm. Likewise,  coming up with new ways to use existing tools certainly shows creativity. But what about things that we might call process improvements, like concocting new methods to improve the efficiency of a process or devising new methods for time management (things like GTD come to mind here)? Are these really innovations, or are they something else? Is “innovating within the realm of the possible” really innovation? Or does innovation contain within itself the idea of moving beyond the boundaries of what is understood to be possible?

In a certain respect I am beginning to think that constraints are a natural complement to innovative thinking. Physicists run up against lots of constraints in their work – the so-called “laws” of nature – and still manage to be innovative. I wonder if taking the attitude that constraints are drivers of innovation rather than its natural enemy would be a better way to foster the idea that one can get better at creativity by practicing. Or does this turn into a severely limiting frame of mind that detracts from one’s ability to “think big” and try to move beyond one’s constraints? Something tells me I might be thinking about this question for some time to come.

Intentional Connection-making

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I haven’t spent much time on Brainpickings because I was unsure about the “7 somethings to make you better at something else” type of posts that seem to characterize a lot of the content there. But after some good linking from Twitter, I took a look at a book review about the intentional practice of creativity, or what others have described as unusual connecting-making. I often feel like any writing that I do needs to be polished and professional, avoid strong opinions, and be generally palatable to whomever might read it. There are a few reasons I feel like this, not the least of which is the eighteen or so years I have spent in formal education of some kind. I do think it is important to communicate one’s ideas clearly, or at least make a good attempt at it, but I think that these three constraints have become excuses for me to hide behind in this format. How does discussion start if everyone agrees with what I say? Throttling my own opinions to make them more palatable also cuts into the authenticity of what I say – and what is this format supposed to promote but authenticity?

All that to say that I want to start practicing connection-making on a regular and intentional basis. Because writing is a great way to think through ideas, and writing with at least some audience in mind (hopefully) helps one to write clearly, I am going to ramp up my activity in this space.

On Data

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I have come across several articles recently that mention the rise of so-called “big data.” I have a certain hazy notion of what this means: the collection and collation of lots and lots of information about everything from shopping habits to traffic patterns to learning styles. For instance, if the data show that a lot of customers tend to buy Gatorade when they buy Clif bars, it might make sense for retailers to put these items next to each other on the shelves in order to increase the purchase of both items. If traffic at a particular intersection is calm between the hours of 10am and 3pm, but picks up during both rush hours, pothole repair could be scheduled for the calm part of the day. And so on.

Big data is making inroads into the educational context as well. Platforms like Coursera and edX are collecting an enormous amount of data about the students that take their courses, including information about when students tend to study, how they tend to interact in discussions, whether cross-cultural interactions spur increased reflection, how students collaborate, etc. These data will then help inform the design process for the next iteration of courses offered on the platform, and perhaps also inform traditional classroom settings as well.

I think the results of this research could be very beneficial to educators of all kinds, whether working in a traditional setting, a blended setting, or an all-online setting. The question I wonder about, however, is what kinds of data we should be collecting, not what kinds are now possible to collect. I’m not referring to privacy concerns, though that is an important discussion in its own right. I’m referring here to the development of metrics that will best allow educators and those who serve them to make informed decisions regarding pedagogy, especially technologically-enhanced pedagogy. What do educators need to know in order to improve education for their students? And how do we measure it? To say that this is a large question is like saying the Pacific Ocean is a big body of water. Nonetheless, I want to put down a few introductory thoughts about how we might try to approach the question, geared specifically to the higher education context.

First, I think that the answer to this question must reflect the goals of the discipline or course. These goals need to be stated explicitly and should probably be formulated as specific learning outcomes. In an American history course, for example, one goal might be civics-oriented: “Students will engage critically with the founding documents of the United States and be able to articulate the relevance of these documents at different stages of American history.” A goal like this may also belong to a larger category that stresses the development of critical thinking. The goal formulation process would then inform the course design process – once the goals are made clear, assignments directed toward meeting those goals would be easier to develop. Some disciplines may be focused primarily on process-centric learning, like engineering or computer science, while others may rely more heavily on memorization or concept-based thinking. This is why articulating the goals for each discipline or course is so important: it allows specific metrics to be designed and implemented. The use of the data collected through these customized metrics will then allow professors to gauge the effectiveness of new tools or pedagogical approaches by comparing data semester-over-semester or year-over-year. Rather than wondering whether a new technology is actually facilitating student formation, professors would be able to clearly see its impact in the data.

Though this sounds simplistic, I am relatively certain that only a handful of professors ever go through this entire process. Goals are certainly articulated on some syllabi, and some professors do spend significant time matching their assignments to these goals. But do they then collect data based on a well-designed series of metrics to measure the effectiveness of their approach? Do they formulate their assessments so that critical thinking skills or process-oriented skills are effectively measured? If not, why not?

While this might not be “big data,” it certainly is important data.

Exploring a “Personal Cyberinfrastructure”

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Servers

Creative Commons image “flight deck (2)” from Flickr by dѧvid

One of the most robust and interesting thinkers in educational technology today is Gardner Campbell at Virginia Tech. Through one of his recent blog posts I happened upon another article that he wrote for the Educause Review about developing a “personal cyberinfrastructure.” In short, Gardner argues that students should be introduced to “digital citizenship” through the personal management of their own web server. This would allow students to do traditional web things, like blogging and sharing other materials, but it would also allow students to explore the full potential of what Doug Englebart called “augmenting human intellect” through computers. I highly recommend the whole article (and the rest of Gardner’s writing as well), and I think this is a fantastic idea. But I was left with one small sticking point after reading the article: could I, as someone actually working in instructional technology, even set up such a server for myself? How might doing so change the way I thought about the web, especially about the possibilities of the web? The resulting project, described in some detail below, reflects my attempt to set up such a server and to wrestle with the central implications of Gardner’s thesis.

Before I get started, however, it is worth mentioning that while I do have some web development experience, it is limited to HTML and CSS (with a little Jquery just for fun). I am not really a coder, I do not know Javascript, and I have not previously attempted to set up a server by myself. That being said, I am something of a tech geek and I enjoy tackling new challenges, so I felt comfortable at least attempting this project.

Anyway, as this was going to be a test server rather than a production server (for now), I decided to use a product called Wamp to create a virtualized web server on my Windows 7 laptop. This handled the installation of Apache, PHP, and MySQL in a (relatively) straightforward manner. I did have to tweak a few PHP files, but the installs went smoothly otherwise. From there, rather than develop from scratch in HTML, I decided to install Drupal 7, which is a powerful web development framework. I did not have any trouble installing it on the Wamp-based server, and before I knew it I was up and running. I decided on Drupal for a number of reasons:

  1. It is open-source. This obviously means that the code is available for free, but it also means that the project embodies the collaborative and open ethos of the web.
  2. My department uses it fairly extensively, meaning that undertaking this project would also have professional development benefits.
  3. It has a very active developer community. The library of user-contributed modules is enormous (more on this in a moment), and the forums and help documentation probably contain every conceivable question and answer combination for new users.
  4. It is highly extensible and customizable. This was very important for the spirit of the project, as running a pre-packaged website without custom features is exactly the opposite of what I think Gardner was advocating in his article. Not only are there thousands of user-contributed modules that extend the core Drupal framework, but those with the requisite coding chops (or those looking to develop them) can interact directly with the code and contribute their own custom modules back to the user community.

At any rate, with Drupal up and running, I now had a somewhat daunting task ahead of me: actually using it! I had very little familiarity with the interface, so I spent a good deal of time reading the Understanding Drupal introduction. If you’re interested in the concepts underpinning Drupal, it is definitely worth a look. After playing around with it for far too many hours, going back to the documentation, trying out a host of new modules, and building a very basic but extremely functional site, I can now say that I am hooked. I am seriously considering moving my blog from this WordPress-based installation to my own custom Drupal site. The ability to do almost exactly what I want with the site is a feeling of freedom and creativity that really surprised me. It now seems that if I think it I can create it, even without writing a lot of code.

Even more to the point, I think this experience is generalizable beyond the Drupal environment. I didn’t use the words “playing around” lightly; I actually felt like I was playing, albeit with a grown-up set of toys. I tinkered, solved problems, tried new things, and almost completely lost track of time in the process. My experience is what I think Gardner is describing when he uses the word “iterative” with regard to learning: each new partial acquisition of understanding leads one to reassess, rebuild, research, and repeat. Once I understood how one piece worked I could incorporate that piece in a larger context that not only leveraged what I already understood but created something new. I didn’t expect to feel the sense of possibility, the sense of potentiality that I do now. In sum, I heartily agree with Gardner that we should be encouraging the type of learning and creativity that can only come from a process like this. It makes me wonder how this type of learning could be used in other contexts as well, though that discussion will have to wait for another post.

Looking forward by looking back?

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I like the way people prognosticate at the beginning of a year. It’s not that I think they are going to be terribly accurate or that the the insights contained within such ramblings will do me any particular benefit. I think it’s the tone of hope that strikes me. One of our favorite (and most resilient) phrases for the change of a calendar is “this year will be better than last year.” I appreciate this sense of optimism. And I think it has often been true in my life, with this year (hopefully) being no exception.

It’s getting to that time in my graduate school career, however, where I need to look backward in order to look forward. I recently spent some time perusing my personal bibliography, and I was slightly shocked to find names of books that I only half remember on the list. Forget articulating the author’s argument; if I’m lucky I remember the thesis of the book. I should probably be more upset by this, as this is the list that will inform my comprehensive examinations, but as of now I’m not terribly affected by this, nor am I surprised: forgetting is as much a part of life as remembering, I guess. I keep decent notes on each of the books that I read, so it shouldn’t be too difficult to reacquaint myself with the literature.

In a roundabout way, though, this lead me to a broader but related rumination: how much of looking forward is a sort of selective appropriation of the past? How much of finding a “new vision for the future” is an admittedly complex process of looking back over the things that worked and the things that didn’t, making inferences about the likelihood of the former continuing to work in the future, and perhaps making a few tweaks to each idea? This is related, in my mind, to the idea that radical innovations rarely just spring from the ether: they most often evolve through a series of small changes and adaptations that eventually add up to major changes. The process of change is often granular, incremental, and contextually-oriented.

To take one very small example, consider the innovations in classroom feedback technologies. Moving from decidedly analog hand raising to smartphone-enabled, real-time, peer-ranked question submission and polling data seems like a big change, and indeed it is. But looking at it as a series of changes – from hand raising to clicking a button on a dedicated device to adding smartphone support to adding full-text question ranking – allows one to get a sense of how things actually changed, and just how gradually they did. This isn’t a paean to the wonders of historical inquiry, necessarily, but it does change the way one thinks about the process of development and growth, both personally and in other realms.

Obviously this does not preclude game-changing innovations, nor imply that technologies (or people) are incapable of making significant progress in a short space of time. But I think it does mean that each innovation or series of innovations has a history that needs to be understood. Acquiring this understanding allows one to look hopefully toward the future by looking to the past.

Justifications

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A few weeks ago I was describing my work in academic technology to a good friend of mine. Our ensuing discussion was wide-ranging and enthusiastic, and we eventually made our way to the million-dollar question: how does educational technology improve student learning? This is a huge question, of course, and could not be fully answered in a long series of conversations or blog posts. We ended up discussing a smaller question: how could I justify working in educational technology in the university setting in light of how how expensive an undergraduate degree has become, especially at very good private institutions?

At first I was a little taken aback at the question. As a student loan-repaying person myself, I understand the enormous financial investment often required to obtain a degree. If I thought that my position was adding a superfluous expense to college education I would have to seriously reevaluate my chosen career field. Before I launch into the reasons that I think educational technology adds value to the university experience, let me first say that I am no expert on financial matters in higher education. I do not claim that educational technology merits preference over other university expenses, nor do I think that it is within the purview of this blog to comment on any of those other expenditures.

First, I think it is important to understand that the field called “educational technology” is about much more than just technology. As I have previously discussed here, I think conversations about pedagogy must take pride of place in any discussion about educational technology. Among my favorite parts of my position is getting to have these types of discussions with faculty members. I know from the experiences of others in my department and from faculty feedback that this time spent on pedagogy can be formative for instructors. By engaging faculty in this manner, educational technologists become something more like pedagogical consultants. These conversations may be happening in other settings, of course, but it stands to reason that faculty members who actively think about their teaching and work to improve it will deliver better instruction to students in their classes.

Second, and closely related, the technologies applied to enhance pedagogy themselves add value to undergraduate education. I won’t belabor this point, as it is one of the main themes of this blog, but suffice it to say that technologies like clickers that enhance the classroom experience and are now taken for granted by many students and faculty members were once technological innovations developed to meet specific pedagogical needs. This example, in fact, points to one way in which educational technology might lower costs for students: allowing a similar level of engagement in larger classes. If class sizes can be increased without compromising instruction quality, fewer sections of each class would be required, thus theoretically decreasing the number of faculty required to teach each course. This is a contested point, of course, and is open to counterarguments about the importance of faculty-student interaction for student formation. It seems clear, however, that educational technology improves the student experience, whether or not it actually reduces costs.

This leads one to wonder if applications of technology can substantially lower the cost of education for students. This has been the approach of many online-only universities and other blended learning contexts, though many of these schools seem to rely heavily on adjunct instructors to keep costs down. Whether blended learning approaches can be successfully adapted to residential institutions remains to be seen, but schools like Harvard and MIT seem to be at least exploring this possibility through the edX consortium. It is not totally clear whether the aims of these MOOCs include a long-term focus on reducing student costs, but it seems likely that the paradigm of open access to college-level content is here to stay (though the results of this access on course-credit mechanisms and the conferral of degrees is still up in the air).

What this last point in particular highlights for me is the way in which educational technologists continue to search for new ways to support and enhance pedagogy. While not all boundary-pushing ideas are necessarily beneficial for students, such ideas seem to have a mild interrogatory edge: are we teaching as effectively as we can? How might students benefit from increased faculty adoption of technologically-mediated pedagogical models? Can we do this better, and perhaps even at lower cost? Adding this to the other points addressed above makes me confident that educational technology truly adds value to the university experience for students and justifies positions like mine.