sleeping alone and starting out early

an occasional blog on culture, education, new media, and the social revolution. soon to be moved from http://jennamcwilliams.blogspot.com.

Archive for the ‘graduate school’ Category

entering graduate school, quitting utopia

Posted by Jenna McWilliams on June 30, 2010

I just spent several hours revising my curriculum vitae, which I can’t imagine is very interesting to you. I do want to share with you my revised research statement. When I looked at the statement I wrote about 10 months ago, I found it embarrassingly utopian and a little bit silly. Also, it didn’t really say anything.

Here’s that version of my research statement:

My interests lie at the intersection of media studies and education. I’m fascinated by the promises inherent in the emergence of new valued participatory practices and cultures, and specifically on the potential of these to transform how we think about and approach teaching and learning. I’m also deeply obsessed with the Free/Open Source Software Movement, the movement toward open education, and what I’ve started to refer to as the social revolution: A deep, cultural shift in values and practices that enables us to rethink issues of social justice and the ethics of participation.

Ridiculous, right?

Here’s the new version:

Research as activism: All educational research is social activism, and all educational researchers are social activists. There is no such thing as politically neutral educational research. All statements of research findings are statements of a belief system about the role of education, and all researchers must therefore conduct research that both aligns with and serves to articulate that belief system. Further, all researchers must make their belief system clear, to themselves, to the communities they work for, and to policymakers who make decisions about those communities. They must always ensure that their belief system aligns with the needs and interests of the communities they work for, and if there is a conflict then the community’s interests always trump the belief system of its researchers. If the ethical conflict is irreconcilable, then the researcher must find another community to serve.

The community I serve: I work in the service of working class learners, on whose backs our education system has been built. While ongoing efforts toward “educational equity” sprung from honest and honorable impulses, the dominant conversation about equity promotes ideals that too often fail to serve the needs of working class kids. It’s also premised on a lie: That anyone who works hard enough can escape even the most desperate of economic conditions. We might call this the “bootstrapping myth.” If it really was true that anyone who works hard enough (i.e., anyone who pulls herself up by her own bootstraps) can achieve academic and therefore economic success, then it would also be true that everyone could, in theory, achieve academic and economic success. But if this were true, we would no longer have a working class, would no longer have people to work in the service industry or take jobs in manual labor. Our economy cannot operate without a working class; if working class kids started matching the grades and test scores of the middle and upper class kids, we’d simply adjust accordingly.

I accept but do not embrace this reality, and I therefore want to work in the service of learning communities for whom mainstream markers of academic success are either unrealistic or inapplicable. I wonder: How can we make a college education a possibility for every student while also preparing every student for trajectories that may not include a college degree? How can we empower working class learners to confront the Great Lie of the bootstrapping myth, and how can we help them to make informed, meaningful, and satisfying decisions about their educations, their careers, and their lives? How can we educate working class kids in their own best interests?


My research focus: I agree wholeheartedly with the assertion by Schwartz & Arena (2009) that assessment is a normative endeavor. What we decide to assess, and the strategies we employ in order to assess it, become our belief systems about the nature of learning and about what is worth teaching. I’m interested in developing alternative assessment systems and frameworks that can make explicit an educational approach that empowers, values, and supports working class kids. Currently, my focus is on developing assessments that support learning gains on traditional educational benchmarks while also making it possible to make claims about students’ preparation for future learning contexts and about their proficiencies in areas not measured by traditional assessments.

Now we’re cooking with gas!

I guess now that I’ve revised my research statement,  all I need to do is wait for a Reputable Research Institution to call me for advice and pay me for my thoughts. I’ll just be over here waiting for my phone to ring.

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Posted in education, graduate school, politics, poverty | 3 Comments »

how I kicked the email monkey off my back

Posted by Jenna McWilliams on June 16, 2010

I receive about 100 emails a day, which from what I can tell is typical for youngish, tech-based professionals like me. Also typical is my struggle to manage my email inbox. Like a lot of people, I spent more time wringing my hands over how full my inbox was or studiously avoiding dealing with my email or doing email-filter acrobatics than I did actually responding to email.

No longer, I tell you! My PLN has come through for me once again!

After a long weekend away from my email, my higher-than-average email stress levels led me to call out in anguish for help:

I got lots of helpful advice, but the most helpful of all came from my Twitter pal Matt Thomas, who directed me to Gina Trapani’s solution: Control your email inbox with three folders.

I spent a few hours yesterday implementing this solution, with one important result: I got my inbox down to zero for the first time in literally years. As anyone in similar straits can imagine, the sight of an empty inbox left me feeling gloriously unburdened and a little giddy.

Who knows if it’ll last? But just in case it does–and just in case Trapani’s strategy can help someone else deal with inbox overload–I’m passing the news along.

Posted in academia, awesome, graduate school, productivity | Leave a Comment »

notes on being the chainsaw you wish to see in the world: Closing remarks for the AERA 2010 annual meeting

Posted by Jenna McWilliams on May 6, 2010

I just got back from my first trip to the annual meeting of AERA, the American Educational Research Association. AERA is apparently the biggest educational research conference in America. I had a fantastic time (highlight: I got to have dinner with Jim Gee!) and my presentation went well (highlight: I argued with the panel’s discussant over why thinking about gender inequity isn’t enough if you’re not also thinking about class inequity!), and I don’t think I made too much of a fool out of myself.

I really enjoyed my first trip to this conference, though when I got home I learned from others that there are significant challenges to be made about the structure, format, and ethos of AERA. I am coming around to that way of thinking and will post my thoughts on this soon.
For now, though, I want to share with you the paper I had to writereallyfast when I got back from the conference. It’s a final paper for a course on computational technologies, and because I was thinking about AERA, social justice, and why the conference’s biggest events mostly featured staid, mainstream thinkers, I decided to write the paper as closing remarks for the conference. I am sure that once the AERA organizers read my closing remarks, they will invite me to deliver next year’s closing remarks in person. I am also available to deliver opening remarks and keynote addresses.

Notes on being the chainsaw you wish to see in the world: On a critical computational literacy agenda for a time of great urgency
Closing Remarks for the AERA Annual Meeting
Jenna McWilliams, Indiana University
May 4, 2010

I want to thank you for giving me the opportunity to speak this evening, at the close of this year’s annual meeting of the American Educational Research Association.

I want to talk to you tonight about the nature of urgency.

Because urgency characterizes the work we do, doesn’t it? The education of our children—our efforts to prepare them to join in on this beautiful and necessary project of naming and claiming the world—it is certainly a matter of the deepest urgency. Even more so because of the war being waged over the bodies and minds of our children.

It’s a war whose contours are deeply familiar to many of us—more so the longer we have been a part of this struggle over education. Certainly the issues we’re fighting over have limned the edges of our educational imagination for generations: How do we know what kids know? How can we prepare them for success in their academic, vocational, and life pursuits? What should schools look like, and how can we fill our schools up with qualified teachers who can do their jobs well? No matter what else, then, at least we’re continuing to ask at least some of the right questions.

Yet a deeper than normal sense of urgency has characterized this year’s annual meeting. It was a “hark ye yet again” sort of urgency: We stood, once again, on a knife’s edge, waiting for word of legislative decisions to be passed down from the policymakers—among whom there are very few educational researchers—to the researchers—among whom there are very few policymakers.

And what sorts of decisions were we waiting to hear on? The same sorts we’ve been wringing our hands over for a decade or more: Decisions over the standardization of education. Development of a proposed set of Common Core Standards whose content seemed painfully anemic to many of us. We’re waiting to learn whether teacher pay will be linked to student performance on standardized tests. Massive budget cuts leading to termination of teachers and programs—these certainly feel familiar to us, though the scope of these cuts and the potential consequences of these decisions seem to loom larger than ever before. The decision by the Texas Department of Education to pervert and politicize its K-12 curriculum by removing references to historical events and even terminology that might offend members of the political Right-—the specifics are new, but the story feels familiar.

A call to action was paired with the clanging of the alarm bells. Ernest Morrell told us that he had counseled his kids to prepare presentations that not only described their work and achievements but that also included a call to action. “I told them, ’Don’t let them leave this room without marching orders’,” he said. “We need to do better. AERA needs to do better.”

He’s right, of course. And I plan to heed Ernest’s advice and not let you leave this room without your marching orders. But first I want to explore the edges of this new urgency, explain why critical computational literacy is part and parcel of the urgency of this moment, and explain exactly what I mean by the term.

There are at least two reasons for the acuteness of the urgency that has characterized this year’s AERA conference. The first is that many of us had hoped for something more, something better, something more honorable from the Obama administration. After eight years living in a political wasteland, many of us felt a glee all out of proportion with reality upon hearing Barack Obama’s position on educational issues. We felt hope. Even a warm half cup of water can feel like a long, tall drink when you’ve just walked out of a desert.

It’s a long revolution, you know. And if Obama authorizes something that looks very much like No Child Left Behind, and if he mandates merit pay based on student performance on standardized tests, and if the recent changes made by the religious right to the Texas state history curriculum stand, and if school board nationwide continue to make terrible, terrible decisions about how to cut costs, and if we see the largest teacher layoff in our history and class sizes creep up to 40 students per room and if computers get taken over by test prep programs and remedial tutoring systems, well, we’ll do our best to live to fight another day. The other day, I listened to Jim Gee talking about his deep anger at the people who run our education system. But he also said something we should all take to heart: “I’ll fight them until I’m dead,” he said. Let’s embrace this position. If they want to claim the hearts and minds of our children, let’s make it so they do it over our cold, dead bodies.

Let’s not let ourselves begin to believe that the stakes are any lower than they actually are. This is the second reason for the urgency this year: There is the very real prospect that the decisions we make within our educational system will get taken up by education departments across the globe. Around 30 of us attended an early-morning session called “Perspectives From the Margins: Globalization, Decolonization, and Liberation.” The discussants, Michael Apple and Dave Stovall, spoke with great eloquence about the nature of this urgency. You’ll forgive me for secretly recording and then transcribing a piece of each of their talks here.

Michael Apple, responding to a powerful presentation on rural science education by researcher Jeong-Hee Kim and teacher-researcher Deb Abernathy, spoke of the far-reaching implications of the local decisions we make:

As we sit here, I have people visiting me from China. They are here to study No Child Left Behind, and they are here to study performance pay. All of the decisions we make that that principal and Deb and you are struggling against are not just struggles in the United States, they are truly global—so that the decisions we make impact not just the kids in the rural areas of the United State, but the rural areas of the people who are invisible, the same people who deconstruct our computers.

Dave Stovall, from the University of Illinois in Chicago, underscored the need to think of the global implications of the policy decisions that intersect within the realm of education:

Arizona is Texas is Greece is Palestine is where we are. This day and time is serious. When a person in Texas cannot say the world capitalism in a public school, we live in serious times. When a person in Arizona can be taken out of a classroom at five years old, to never return, we live in serious times. When we can rationalize in the state of Illinois and city of Chicago that having 5 grams of heroin on a person accounts for attempted murder, we’re living in different times. When we can talk about in Palestine that young folks have now been deemed the most violent threat to the Israeli state, we’re living in different times. And now, how do we engage and interrupt those narratives based again on the work we do?

These times are different and serious, and talking about critical computational literacy may make me look a little like Nero with his fiddle. But critical computational literacy, or indeed its paucity in our education system, is the dry kindling that keeps Rome burning.

I’ll explain why. Let’s talk for a minute about another Apple, the electronics company Apple Corp. The year 2010 marked the release of Apple’s iPad, a tablet computer designed as a multipurpose information and communication tool. Despite mixed reviews of its usability and features, records show an estimated 500,000 units sold between pre-orders and purchases in the first week after the iPad’s release.

This has been accompanied by a push for consideration of the iPad’s utility for education, especially higher education, with schools working to develop technical support for iPad use on campus and at least one university, Seton Hall, promising to provide all incoming freshmen with iPads along with Macbooks. One question—-how might the iPad transform education?-—has been the topic of conversation for months.

“The iPad,” crowed Neil Offen in the Herald-Sune (2010), “could be more than just another way to check your e-mail or play video games. It has the potential to change the way teachers teach and students learn.”

Certainly, these conversations reflect a positive shift in attitudes about what comprises literacy in the 21st Century. If you attended the fantastic symposium on Sunday called “Leveraging What We Know: A Literacy Agenda for the 21st Century,” you heard from the panelists a powerfully persuasive argument that “literacy” is no longer simple facility with print media. Indeed, facility with print media may still be necessary, but it’s no longer sufficient. As the emergence of the iPad, the Kindle, and similar literacy tools make evident, the notion of “text” has become more aligned with Jay Lemke’s (2006) description of “multimedia constellations”—loose groupings of hypermediated, multimodal texts that exist “not just in the imagination of literary theorists, but in simple everyday fact” (pg. 4). Add to this the ongoing contestation of the tools we use to access and navigate those constellations of social information, and the urgency of a need to shift how we approach literacy becomes increasingly obvious.

As anyone who works in the literacy classroom knows, this is by no means a simple task. This task is complicated even further by the dark side of this new rhetoric about literacy: There’s a technological determinism hiding in there, an attitude that suggests an educational edition of Brave New Worldism. Offen’s celebration of the iPad aligns with the approach of Jeremy Roschelle and his colleagues (2000), who a decade ago trumpeted the transformative potential of a range of new technologies. In explaining that “certain computer-based applications can enhance learning for students at various achievement levels,” they offer descriptions of
promising applications for improving how and what children learn. The ‘how’ and the ‘what’ are separated because not only can technology help children learn things better, it also can help them learn better things” (pg. 78, emphasis mine).

More recently, the media scholar Henry Jenkins (2006) described the increasingly multimodal nature of narratives and texts as “convergence culture.” As corporate and private interests, beliefs, and values increasingly interact through cheaper, more powerful and more ubiquitous new technologies, Jenkins argues, our culture is increasingly defined by the collision of media platforms, political ideologies, and personal affinities. Jenkins celebrates the emergence of this media convergence, arguing that “(i)n the world of media convergence, every important story gets told, every brand gets sold, and every consumer gets courted across multiple media platforms” (pg. 3).

Brave new world, indeed. But there is reason to wear a raincoat to this pool party, as a cursory examination of the developing “Apple culture” of electronics confirms. The iPad, celebrated as a revolution in personal computing, communication, and productivity—and marketed as an essential educational tool—is a tool with an agenda. The agenda is evident in Apple’s decision to block the educational visual programming software Scratch: Though Apple executives have claimed that applications like Scratch may cause the iPad to crash, others argue that the true motivation behind this decision is to block a tool that supports media production. The Scratch application allows users to build new applications for the iPad, which Bruckman (2010) suggests goes far beyond Apple’s unstated interest in designing its products primarily for media consumption.

There is no closest competitor to the iPad, so users who want to leverage the convenience, coolness, and computing power of this product must resign themselves to the tool Apple provides. Similarly, as Apple develops its growing monopoly in entertainment (iPods), communications (iPhone), and portable computing (Macbook), Apple increasingly has the power to decide what stories to tell, and why, and how.

Now let’s go back to the other Apple, Michael Apple, who argues quite convincingly about the colonization of the space of the media by the political right wing (2006). We have, he argues, politicians deciding what we pay attention to, and we have corporations deciding how we pay attention to it. This makes the need for critical computational literacy even more important than ever before. Perhaps it’s more important than anything else, though I’ll leave that to the historians to decide.

What is this thing I’m calling “critical computational literacy”? Since I’m almost the only person using this term, I want to start by defining it. It has its roots in computational literacy, which in itself bears defining. Andy diSessa (2001) cautions us against confusing computational literacy with “computer literacy,” which he describes as being able to do things like turning on your computer and operating many of its programs. His definition of computational literacy, he explains, makes computer literacy look “microscopic” in comparison (p. 5). For him, computational literacy is a “material intelligence” that is “achieved cooperatively with external materials” (p. 6).

This is a good start in defining computational literacy but probably still not enough. And please do remember that I will not let you leave this room without marching orders; and if I want you to know what to do, I have to finish up the definition. Let’s add to diSessa’s definition a bit of the abstraction angle given to us by Jeanette Wing (2008), who shifts the focus slightly to what she labels “computational thinking.” She describes this as

a kind of analytical thinking. It shares with mathematical thinking in the general ways in which we might approach solving a problem. It shares with engineering thinking in the general ways in which we might approach designing and evaluating a large, complex system that operates within the constraints of the real world. It shares with scientific thinking in the general ways in which we might approach understanding computability, intelligence, the mind and human behaviour. (pg. 3716)

For Wing, the essential component of computational thinking is working with abstraction, and she argues that an education in computational thinking integrates the “mental tool” (capacity for working with multiple layers of abstraction) with the “metal tool” (the technologies that support engagement with complex, abstract systems).

So. We have diSessa’s “material intelligence” paired with Wing’s “computational thinking”—a fair enough definition for my purposes. But what does it look like? That is, how do we know computational literacy when we see it?

The answer is: it depends. Though we have some nice examples that can help make visible what this version of computational literacy might look like. Kylie Peppler and Yasmin Kafai (2007), who by the way have a new book out on their work with the Computer Clubhouse project (you can buy a copy up at the book fair), offer instructive examples of children working with Scratch. Jorge and Kaylee, their two case studies, are learners who make creative use of a range of tools to build projects that extend, as far as their energy and time will allow, the boundaries of what is possible to make through a simple visual programming language. Bruce Sherin, Andy diSessa, and David Hammer (1993) give an example of their work with Dynaturtle to advance a theory of “design as a learning activity”; in their example, learners work with the Boxer programming language to concretize abstract thought.

Certainly, these are excellent examples of computational literacy in action. But I would like to humbly suggest that we broaden our understanding of this term far beyond the edges of programming. Computational literacy might also be a form of textual or visual literacy, as learners develop facility with basic html code and web design. It might be the ability to tinker—to actually, physically tinker, with the hardware of their electronics equipment. This is something that’s typically frowned upon, you know. Open up your Macbook or your iPhone and your warranty is automatically null and void. This is not an accident; this is part of the black box approach of electronics design that I described earlier.

Which leads me to the “critical” component of computational literacy. This is no time for mindless tinkering; we are faced with a war whose terms have been defined for us by members of the political Right, and whose battles take place through tools and technologies whose uses have been defined for us by corporate interests. Resistance is essential. In the past, those who resisted the agendas of software designers and developers were considered geeks and freaks; they were labeled “hackers” and relegated to the cultural fringes (Kelty 2008). Since then, we have seen an explosion in access to and affordability of new technologies, and the migration to digitally mediated communication is near-absolute. The penetration of these technologies among young people is most striking: (include statistics). Suddenly, the principles that make up the “hacker ethos” (Levy, 1984) take on new significance for all. Suddenly, principles that drove a small subset of our culture seem more like universal principles that might guide cultural takeup of new technologies:

  • Access to computers—and anything which might teach you something about the way the world works—should be unlimited and total.
  • All information should be free.
  • Mistrust authority—promote decentralization.
  • Hackers should be judged by their hacking, not criteria such as degrees, age, race, sex, or position.
  • You can create art and beauty on a computer.
  • Computers can change your life for the better. (Levy 1984)

If these principles seem overtly ideological, overtly libertarian, that’s because they are. And I’m aware that in embracing these principles I run the risk of alienating a fairly significant swath of my audience. But there’s no time for gentleness. This is no time to hedge. I believe, as Michael Apple and Dave Stovall and Rich Ayers and others have argued persuasively and enthusiastically, that we are fighting to retrieve the rhetoric of education from the very brink. It’s impossible to fight a political agenda with an apolitical approach. We must fight now for our very future.

That’s the why. Now I’d like to tackle the how. If we want our kids to emerge from their schooling experience with the mindset of critical computational literacy, we need to first focus on supporting development of critical computational literacy in our teachers. They, too, are subject to all of the pressures I listed earlier, and add to the mix at least one more: They are subject to the kind of rhetoric that Larry Cuban (1986) reminds us has characterized talk of bringing new technologies into the classroom since at least the middle of the 20th century. As he researched the role of technologies like radio, film, and television in schools, he described the challenges of even parsing textual evidence of technologies’ role:

Television was hurled at teachers. The technology and its initial applications to the classroom were conceived, planned, and adopted by nonteachers, just as radio and film had captured the imaginations of an earlier generation of reformers interested in improving instructional productivity…. Reformers had an itch and they got teachers to scratch it for them. (p. 36)

This certainly hearkens, does it not, of the exhortation of Jeremy Roschelle and his colleagues? I repeat:

promising applications for improving how and what children learn. The ‘how’ and the ‘what’ are separated because not only can technology help children learn things better, it also can help them learn better things.

Teachers are also faced with administrators who say things like these quotes, taken from various online conversations about the possible role of the iPad in education.

I absolutely feel the iPad will revolutionize education. I am speaking as an educator here. All it needs are a few good apps to accomplish this feat.

Tablets will change education this year and in the future because they align neatly with the goals and purposes of education in a digital age.

And finally, the incredibly problematic:

As an educational administrator for the last eleven years, and principal of an elementary school for the past seven…after spending three clock hours on the iPad, it is clearly a game changer for education.

Three hours. Three hours, and this administrator is certain that this, more than any previous technology, will transform learning as we know it. Pity the teachers working at his school, and let’s hope that when the iPad gets hurled at them they know how to duck.

We must prepare teachers to resist. We must prepare them to make smart, sound decisions about how to use technologies in the classroom and stand tall in the face of outside pressures not only from political and corporate interests but from well-meaning administrators and policymakers as well. There is a growing body of evidence that familiarity with new tools is—just like print literacy—necessary but not sufficient for teachers in this respect.

There is evidence, however, that experience with new technologies when paired with work in pedagogical applications of those technologies can lead to better decision-making in the classroom. I recommend the following three-part battle plan:

First, we need to start building a background course in new media theory and computational thinking into our teacher education programs. My home institution, Indiana University, requires exactly one technology course, and you can see from the description that it does its best to train pre-service teachers in the use of PowerPoint in the classroom:

W 200 Using Computers in Education (1-3 cr.)Develops proficiency in computer applications and classroom software; teaches principles and specific ideas about appropriate, responsible, and ethical use to make teaching and learning more effective; promotes critical abilities, skills, and self-confidence for ongoing professional development.

Fortunately, we can easily swap this course out for one that focuses on critical computational literacy, since the course as designed has little practical use for new teachers.

Second, we need to construct pedagogy workshops that stretch from pre-service to early in-service teachers. These would be designed to support lesson development within a specific domain, so that all English teachers would work together, all Math teachers, all Science teachers, and so on. This could stretch into the early years of a teacher’s service and support the development of a robust working theory of learning and instruction.

Finally, we might consider instituting ongoing collaborative lesson study so that newer teachers can collaborate with veteran teachers across disciplines. I offer this suggestion based on my experience working in exactly this environment over the last year. In this project, teachers meet monthly to discuss their curricula and to share ideas and plan for future collaborative projects. They find it intensely powerful and incredibly useful as they work to integrate computational technologies into their classrooms.

I’m near the end of my talk and would like to finish with a final set of marching orders. If we want to see true transformation, we need first to tend our own gardens. Too often—far, far too far too often—we educational researchers treat teachers as incidental to our interventions. At the risk of seeming like an Apple fanboy, I return once again to the words of Michael Apple, who argued brilliantly this week that it’s time to rethink how we position teachers in our work. We say we want theory to filter down to the “level” of practice; the language of levels, Apple says, is both disingenuous and dangerous. Let’s tip that ladder sideways, he urges us, and he is absolutely correct. We live and work in the service of students first, and teachers second. We should not forget this. We should take care to speak accordingly.

These are your marching orders: To bring the message of critical computational literacy and collaboration during this time of great urgency back to your home institutions, to the sites where you work, to the place where you work shoulder to shoulder with other researchers, practitioners, and students. I urge you to stand and to speak, loudly, and with as much eloquence as you can muster, about the issues of greatest urgency to you. This is no time to speak softly. This is no time to avoid offense. In times of great urgency, it’s not enough to be the change we wish to see in the world; we need to be the chainsaws that we wish to see in the world. That is what I hope you will do when you leave this convention center. Thank you.

References
Apple, M.W. (2006). Educating the “right” way: Markets, standards, God, and inequality. New York: Routledge.
Bruckman, A (2010, April 15). iPhone application censorship (blog post). The next bison: Social computing and culture. Retrieved at http://nextbison.wordpress.com/2010/04/15/iphone-application-censorship/.
Carnoy, M. (2008, August 1). McCain and Obama’s educational policies: Nine things you need to know. The Huffington Post. Retrieved at http://www.huffingtonpost.com/martin-carnoy/mccain-and-obamas-educati_b_116246.html.
Carter, D. (2010, April 5). Developers seek to link iPad with education. eSchool News. Retrieved from http://www.eschoolnews.com/2010/04/05/ipad-app-store-has-wide-selection-of-education-options/.
Cuban, L. (1986). Teachers and machines. New York: Teachers College Press.
diSessa, A. A. (2000). Changing minds : Computers, learning, and literacy. Cambridge, Mass.: MIT Press.
Jenkins, H. (2006). Convergence culture: Where old and new media collide. Cambridge, MA: MIT Press.
Kelty, C. (2008). Two bits: The cultural significance of free software. Durham, NC: Duke University Press.
Kolakowski, N. (2010). Apple iPad, iPhone Expected to Boost Quarterly Numbers. eWeek, April 18, 2010. Retrieved at http://www.eweek.com/c/a/Desktops-and-Notebooks/Apple-iPad-iPhone-Expected-to-Boost-Quarterly-Numbers-825932/.
Korn, M. (2010). iPad Struggles at Some Colleges. Wall Street Journal, April 19, 2010. Retrieved at http://online.wsj.com/article/SB10001424052748703594404575192330930646778.html?mod=WSJ_Tech_LEFTTopNews.
Lemke, J. (2006). Toward Critical Multimedia Literacy: Technology, research, and politics. In M.C. McKenna et al. (Eds.), International handbook of literacy and technology: Volume II. Mahwah, NJ: Lawrence Erlbaum Associates Inc. (3-14).
Levy, S 1984. Hackers: Heroes of the computer revolution. New York: Anchor Press/Doubleday.
McCrae, B. (2010, Jan. 27). Measuring the iPad’s potential for education. T|H|E Journal. Retrieved from http://thejournal.com/articles/2010/01/27/measuring-the-ipads-potential-for-education.aspx.
New York Times (2010, March 17). Editorial: Mr. Obama and No Child Left Behind. New York Times Editorial Page. Retrieved from http://www.nytimes.com/2010/03/18/opinion/18thu1.html.
Offen, N. (2010, Jan. 28). The iPad and education. The Herald-Sun. Retrieved from http://www.heraldsun.com/view/full_story/5680899/article-The-iPad—education?instance=main_article.
PBS (2010, Jan. 7). How will the iPad change education? PBS TeacherLine Blog. Retrieved from http://www.pbs.org/teacherline/blog/2010/01/how-will-the-ipad-change-education/.
Peppler, K. A., & Kafai, Y. B. (2007). From SuperGoo to Scratch: exploring creative digital media production in informal learning. Learning, Media and Technology, 32(2), 149-166.
Roschelle, J. M., Pea, R. D., Hoadley, C. M., Gordin, D. N., & Means, B. M. (2000). Changing how and what children learn in school with computer-based technologies. The future of children, 10(2), 76–101.
Sherin, B., DiSessa, A. A., & Hammer, D. M. (1993). Dynaturtle revisited: Learning physics through collaborative design of a computer model. Interactive Learning Environments, 3(2), 91-118.
Smith, E. (2010, April 16). The Texas Curriculum Massacre. Newsweek. Retrieved at http://www.newsweek.com/id/236585.
Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical Transactions A, 366(1881), 3717-3717.

 

**Update, 5/6/10, 1:09 p.m.: I have changed this post slightly to remove an unfair attack against a presenter at this year’s AERA Annual Meeting. He points out in the comments section below that my attack was unfair, and I agree and have adjusted the post accordingly.

Posted in academia, computational literacy, conferences, convergence culture, education, graduate school, Henry Jenkins, Jim Gee, Joshua Danish, President Obama, public schools, schools, teaching, Twitter | 7 Comments »

how to make like an ally

Posted by Jenna McWilliams on April 11, 2010

You read Sady Doyle’s blog Tiger Beatdown, right? Everybody reads Sady Doyle’s blog Tiger Beatdown. If you’ve never been to this site, may I suggest you leave my blog immediately in order to immerse yourself in the glory and ladyrage that is Tiger Beatdown? Here, I’ll even do something I never ever do: I’ll give you a link to her blog that takes you directly away from my blog and deposits you at her blog, which if you haven’t read her blog is actually where you belong anyway.

Today I want to direct your attention to the most recent Tiger Beatdown post, which is about feminist allies and offers a nice description, in the person of one Freddie de Boer, of how not to be an ally. Freddie, it appears, is Sady Doyle’s enemy in the worst way: He explains that, as a feminist man, he’s tired of being silenced by feminist women who purport to have more right to speak about sexism than he does!

Well, Sady gives ol’ Freddie a glorious smackdown, which I’m sure he has already interpreted as yet another example of why we shouldn’t let ladies speak their minds. In the middle of her smackdown, Sady offers up what I consider to be most excellent advice for anybody who wants to serve as an ally to a marginalized group. I’m going to include an abridged version of her advice below, though this should in no way hinder your intention to read the entire post in its gorgeous entirety.

Sady writes:

A common phrase, which just about every ally has ever heard or been instructed to heed, is, “if it’s not about you, don’t make it about you.” That is: If someone is describing a gross, oppressive behavior that some people in your privileged group engage in, then there is no reason to get defensive unless you personally engage in that behavior, in which case you need to stop complaining about your hurt feelings and focus on how quickly and completely you can cut that shit out. And rushing to the defense of people who do engage in the oppressive behavior, even if you don’t engage in it, is not acceptable, because you’re showing solidarity with your privilege, rather than with the people who are being hurt or oppressed. There is no better way to announce that you seriously don’t care about racism than to leap to the defense of some racist-ass people and ask people of color to stop talking about them in such a critical tone, for example.

To illustrate what the ally behavior Sady describes above actually looks like on the ground, I want to tell a story about my friend Adam, in whom I recently–and unexpectedly–found an ally.

I have a history of being a woman, and I also have a history of being involved in romantic relationships with women. I talk about the first thing all. the. effing. time. I haven’t done much talking about the second thing, though I’m proud to announce that I’m getting better at talking about it.

I was out with a group of friends a few nights ago and decided to talk about it. Specifically, I decided to talk about my tendency to judge people who affiliate with organizations that make it their business to try to keep gay people as unhappy and unable to live freely and without risk of personal or psychological harm as possible. (I do not accept ignorance or political apathy as an excuse, in case you were wondering.) Uproar ensued around the table, which was filled with people who to my knowledge did not have any history of dating people of the same gender. Everybody wanted to weigh in on whether I was right or wrong to judge others. Everybody wanted to weigh in on whether I was being closed minded. Which was fine with me, really. These guys are my friends, and they seem to like me an awful lot, and I wasn’t mad or upset or anything. I was interested in learning how each of my friends (some of whom belong to their own marginalized–or even doubly marginalized–groups) understood the notion of marginalization. I was intensely interested in fighting about this issue for as long as they were willing to fight.

But Adam, who I believe to be a straight white man, did something I didn’t expect: He acted as my ally. He participated in the conversation, but he mainly did so to help me to clarify my stance and open up space for me to speak. He did this so gracefully and so intelligently that I assumed he agreed with me but only later realized I actually don’t know his opinion on my stance toward people who affiliate with anti-gay organizations. I don’t think he ever weighed in.

Adam is a classmate, and he’s near the end of his graduate career. In class, he’s kinda pushy and extremely talkative; he tends to dominate discussions and it’s sometimes hard to get a word in. But on the other hand, he knows an awful lot about his field and has a lot to say about it.

So I know Adam can dominate a conversation, which means that in Friday night’s discussion, he chose to stand back in order to give me more room to speak.

This is Adam:

Adam knows a thing or two about how to listen. Adam is an ally. I didn’t thank him on Friday night, so Adam, consider this my thanks.

Posted in awesome, bigotry, feminism, gay rights, gender politics, graduate school, human rights | Leave a Comment »

why I am not a constructionist

Posted by Jenna McWilliams on April 6, 2010

and why you should expect more from my model for integrating technologies into the classroom

I recently showed some colleagues my developing model for integrating computational technologies into the classroom. “This is,” one person said, “a really nice constructionist model for classroom instruction.”

Which is great, except that I’m not a constructionist.

Now, don’t be offended. I’ll tell you what I told my colleague when she asked, appalled, “What’s wrong with constructionists?”

Nothing’s wrong with constructionists. I just don’t happen to be one.

a brief history lesson
Let’s start with some history. Constructionism came into being because two of the greatest minds we’ve had so far converged when Jean Piaget, known far and wee as the father of constructivism, invited Seymour Papert to come work in his lab. Papert later took a faculty position at MIT, where he developed the Logo programming language, wrote Mindstorms, one of his canonical books, and laid the groundwork for the development of constructionism.

Here’s a key distinction to memorize: While constructivism is a theory of learning, constructionism is both a learning theory and an approach to instruction. Here’s how the kickass constructionist researcher Yasmin Kafai describes the relationship between these terms:

Constructionism is not constructivism, as Piaget never intended his theory of knowledge development to be a theory of learning and teaching…. Constructionism always has acknowledged its allegiance to Piagetian theory but it is not identical to it. Where constructivism places a primacy on the development of individual and isolated knowledge structures, constructionism focuses on the connected nature of knowledge with its personal and social dimensions.

Papert himself said this:

Constructionism–the N Word as opposed to the V word–shares constructivism’s connotation to learning as building knowledge structures irrespective of the circumstances of learning. It then adds the idea that this happens especially felicitously in a context where the learner is consciously engaged in constructing a public entity whether it’s a sand castle on the beach or a theory of the universe.

Examples of constructionist learning environments include the well known and widespread Computer Clubhouse program, One Laptop Per Child, and learning environments built around visual programming tools like Scratch and NetLogo.

why I am not a constructionist
Constructionism is really neat, and some of the academics I respect most–Kafai, Kylie Peppler, Mitch Resnick, Idit Harel, for example–conduct their work from a constructionist perspective. A couple of things I like about the constructionist approach is its emphasis on “objects to think with” and some theorists’ work differentiating between wonderful ideas and powerful ideas.

Constructionist instruction is a highly effective approach for lots of kids, most notably for kids who haven’t experienced success in traditional classroom settings. But as Melissa Gresalfi has said more than once, people gravitate to various learning theories when they decide that other theories can’t explain what they’re seeing. Constructionism focuses on how a learning community can support individual learners’ development, which places the community secondary to the individual. I tend to wonder more about how contexts support knowledge production and how contexts lead to judgments about what counts as knowledge and success. If it’s true, for example, that marginalized kids are more likely to find success with tools like Scratch, then what matters to me is not what Scratch offers those kids that traditional schooling doesn’t, but what types of knowledge production the constructionist context offers that aren’t offered by the other learning contexts that fill up those kids’ days. I don’t care so much about what kids know about programming; I’m far more interested in the sorts of participation structures made possible by Scratch and other constructionist tools.

If you were wondering, I’m into situativity theory and its creepy younger cousin, Actor-Network Theory. So what I’m thinking about now is what sorts of participation structures might be developed around a context that looks very much like the diagram below. Specifically, I’m wondering: What sorts of participation structures can support increasingly knowledgeable participation in a range of contexts that integrate computation as a key area of expertise?


why I’m mentioning this now
My thinking about this is informed of late by what I consider to be some highly problematic thinking about equity issues in technology in education. A 2001 literature review by Volman & vanEck focuses on how we might just rearrange the classroom some to make girls feel more comfortable with computers. For example, they write that

to date, research has not produced unequivocal recommendations for classroom practice. Some researchers found that girls do better in small groups of girls; some researchers argue in favor of such groups on theoretical grounds (Siann & MacLeod, 1986, Scotland; Kirkup, 1992, United Kingdom). Others show that girls perform better in mixed groups (Kutnick, 1997, United Kingdom) or that girls benefit more than boys do from working together (Littleton et al., 1992, United Kingdom). Other student characteristics such as competence and experience in performing the task seem in any case to be equally important, both in primary and secondary education. An explanation for girls’ achieving better results in mixed pairs is that they have more opportunity to spend time with the often-more-experienced boys. The question, however, is whether this solution has negative side effects. It may all too easily confirm the image that girls are less competent when it comes to computers. Another solution may be that working in segregated groups compensates for the differences in experience. Tolmie and Howe (1993, Scotland, secondary education) argue strongly for working in small mixed groups because of the differences they identified between the approaches taken by groups of girls and groups of boys in solving a problems.

For the love of pete, the issue is not whether girls feel more comfortable working in small groups or mixed groups or pairs or individually; the issue is why in the hell we have learning environments that allow for these permutations to matter to girls’ access to learning with technologies.

Also, just for the record, the gender-equity issue in video gaming cannot be resolved just by building “girl versions” of video games, no matter what Volman and vanEck believe. They write:

Littleton, Light, Joiner, Messer, and Barnes (1992, United Kingdom, primary education) found that gender differences in performance in a computer game disappeared when the masculine stereotyping in that game was reduced. In a follow-up study they investigated the performance of girls and boys in two variations of an adventure game (Joiner, Messer, Littleton, & Light, 1996). Two versions of the game were developed, a “male” version with pirates and a “female” version with princesses. The structure of both versions of the game was identical. Girls scored lower than boys in both versions of the game, even when computer experience was taken into account; but girls scored higher in the version they preferred, usually that with the princesses.

I don’t think that the researchers cited by Volman and vanEck intended their work to be interpreted this way, but this is exactly the trouble you get into when you start talking about computational technologies in education: People think the tool, or the slight modification of it, is the breakthrough, when the breakthrough is in how we shift instructional approaches through integration of the tool–along with a set of technical skills and practices–for classroom instruction.

Looking at my developing model, I can see that I’m in danger of leading people to the same interpretation: Just put this stuff in your classroom and everything else will work itself out. This is what happens when you frontload the tool when you really mean to frontload the practices surrounding that tool that matter to you.

This is the next step in the process for me: Thinking about which practices I hope to foster and support through my classroom model and deploying various technologies for that purpose. I’ll keep you posted on what develops.

One last note
I’ve included here a discussion about why I’m not a constructionist along with a discussion of gender equity issues in education, but I don’t at all want anybody to take this as a critique of constructionism. I declare again: Nothing’s wrong with constructionism. I just don’t happen to be a constructionist. Also, I think a lot of really good constructionist researchers have done some really, really good work on gender equity issues in computing, and I’m just thrilled up the wazoo about that and hope they can find ways to convince people to stop misinterpreting constructionism in problematic ways.

References, in case you’re a nerd

Joiner, R., Messer, D., Littleton, K., & Light, P. (1996). Gender, computer experience and computer-based problem solving. Computers and Education, 26(1/2), 179–187.
Kafai, Y. B. (2006). Constructivism. In K. Sawyer (Ed.), Handbook of the Learning Sciences (pp. 35-46). Cambridge, MA: Cambridge University Press.
Kirkup, G. (1992). The social construction of computers. In G. Kirkup and L. Keller (Eds.), Inventing women: Science, gender and technology (pp. 267–281). Oxford: Polity Press.
Kutnick, P. (1997). Computer-based problem-solving: The effects of group composition and social skills on a cognitive, joint action task. Educational Research, 39(2), 135–147.
Littleton, K., Light, P., Joiner, R., Messer, D., & Barnes, P. (1992). Pairing and gender effects in computer based learning. European Journal of Psychology of Education, 7(4), 1–14.
Papert, S., & Harel, I. (1991). Situating Constructionism. In Papert & Harel, Constructionism. Ablex Publishing Corporation. Available online at http://www.papert.org/articles/SituatingConstructionism.html.
Siann, G., & MacLeod, H. (1986). Computers and children of primary school age: Issues and questions. British Journal of Educational Technology, 2, 133–144.
Tolmie, A., & Howe, C. (1993). Gender and dialogue in secondary school physics. Gender and Education, 5(2), 191–210
Volman, M., & van Eck, E. (2001). Gender Equity and Information Technology in Education: The Second Decade. [10.3102/00346543071004613]. Review of Educational Research, 71(4), 613-634.

my model, in case you were wondering

Posted in computational literacy, education, feminism, gender politics, graduate school, Joshua Danish, schools, teaching, technologies | 15 Comments »

update: model for integrating technology into the literacy classroom

Posted by Jenna McWilliams on February 14, 2010

I’ve upgraded.

As part of an ongoing assignment for a course I’m taking called Computational Technologies in Educational Ecosystems, I’ve been designing and modifying a model for the role of technologies in the classroom. A previous version, a cellphone picture of a drawing on a sheet of notebook paper, looked like this:

Well. This is for a class on computational technologies, so a hand-drawn model would never do. Besides, one of the more useful affordances of new design technologies is the ease with which designs can be modified–not the case with hand-drawn designs.

So I upgraded. The upgrade looks like this:

(You can click the image to enlarge it; if it’s still too small, you can open a powerpoint version here.)

As I mentioned in my previous post, I’m focusing in on the English / Language Arts classroom–what I’ve begun to call the “literacy sciences” classroom. I’m calling it this to reflect my vision for the kind of learning that can happen in the ideal ELA classroom. It’s a community where class activities reflect the real-world practices of people engaging in authentic, valuable and valued reading and writing practices. In the real world, reading and writing practices cross multiple media and platforms; and they’re all bound up in the context for which they’re necessary and useful.

Which is why this version includes one tiny but important addition: The open door leading to other content areas. This addition was inspired by reading I’ve done this week on participatory simulations and wearable computing. Vanessa Colella’s 2000 piece, “Participatory Simulations: Building Collaborative Understanding through Immersive Dynamic Modeling,” describes one aspect of these types of simulations: That they treat the classroom as what she labels a “cognitive system.” Colella describes the cognitive system as one comprised of all people, tools, data, and discourse that are both part of and a product of class activities.

What Colella doesn’t point out is that the simulations she describes call for a cognitive system not bound by any specific content domain. Her simulation is of a fast-spreading virus similar to HIV or influenza, and though students’ primary goal is to solve the problem of how the virus spread and to whom, related social and cultural implications are hinted at and have educational potential.

Indeed, the real-world literacy practices of literacy science are not bound to any domain. It’s hard to imagine what “pure” literacy science would look like: A solitary reader, engaging in literary analysis in a room by herself, without any tools other than her eyes and her mind and her memory? Though the cognitive systems that surround literacy performances are not always clear and not always stable, one thing we can say is that they extend far beyond the domain of English / Language Arts.

We must, therefore, prepare learners for this reality by opening up the doors and letting content bleed across boundaries, and letting readers move between contexts. The problems learners must be prepared to address–the deep, thorny problems of our time–call for a breaking down of content silos.

One other addition here is the citations around the borders. These are linked to varying extent to course readings; I’ve added a few other names where relevant. Upon completion of this project, I’ll post a list of all relevant resources, in case you’re interested in perusing them.

Posted in academia, education, graduate school, Henry Jenkins, Joshua Danish, literacy, patent pending, reading, schools, teaching, writing | Leave a Comment »

on conceptual models, native competence, and (not) learning to play rugby

Posted by Jenna McWilliams on February 5, 2010

I had the deeply unsettling experience recently of feeling like the stupidest person in the room. This type of experience is (both fortunately and unfortunately) fairly rare for the typical educational researcher, though it’s far more common for members of the learning communities researchers study. For this reason, I believe it’s incredibly important for researchers to examine the contexts that make them feel stupid, if only so they can better understand the groups they’re studying.

The context was a graduate-level class. I’m one of just under a dozen students; the class, “Computational Technologies in Educational Ecosystems,” draws students from my university’s school of education and from the Informatics Department. A key assignment in the course is design, reflection on, and revision of a model that represents our take on the role of technologies in learning environments.

I have previously noted my despair over my apparent inability to complete this assignment in a meaningful way. The most progress I’ve been able to make was in presenting an unfinished model that draws the vaguest possible connection between humans and technology:

Then in class this week we spent a large chunk of time working with a representation developed by the instructor, the fanTASTIC Joshua Danish. His representation, which is also available on his website, is intended to point to key features of the week’s readings on cognitive tutors, Teachable Agents, and computer-aided instruction. Here’s the representation:

This representation literally carries no meaning for me. I mean, I get the basic idea behind it, but only because I did the assigned reading and get the basic themes and goals of computer-aided instruction. I get that research in this area focuses on domain-oriented issues, learning theories, and the role of these tools in classroom environments; but I do not understand how the above representation articulates this focus.

Yet I sat there in class and listened to my classmates interpreting the representation. They understood it; they could ‘read’ it; they could point to areas of weakness and suggest corrections to improve it.

The experience reminded me of the time I tried to learn rugby by joining an intramural team. After 20 minutes of basic instruction, we all got thrown into a game and the first time I got the ball, I apparently did something wrong and the team captain tackled me hard, hollering at me as she pulled me down. I never did find out what I’d done wrong. And actually, I didn’t much care. That was the last time I tried rugby.

Of course, Joshua’s never tackled anybody. He’s a fantastic teacher–one of the best I’ve ever had–who’s deeply invested in fostering an authentic learning community and supporting his students in their growth. But I sat there, watching my classmates speak a language I didn’t understand, getting more and more frustrated, and I absolutely felt like walking right off the field and never coming back.

At least two important lessons are nested in this experience, and one is linked to the other.


1. There are kids who feel this way all the time, every day. It’s easy for educational researchers to forget this point, mainly because most (though certainly not all) of us have experienced raging success in our own educational experiences. We got A’s in everything. Or we found a niche within a certain content area and pursued it with a fair amount of success. Or we figured out how to game the system, so that even if we didn’t get A’s in everything, we still felt somehow smarter than everyone else. Or if we had bad experiences with school early on, we still came to think of ourselves as smart, or at least smart enough to deserve advanced study in education.

So maybe we know in theory that schools are stacked against some kids, that the entire education system is designed on the premise that some kids will always be labeled the failures, the losers, the learning disabled, the stupid. (If it weren’t for the stupid kids, after all, how would we know what an A student is worth?) We know in theory that some kids feel frustrated and lost in school, and that some kids end up feeling like it’s hopeless to even bother trying.

But the fact is that we don’t know how it feels in practice. We can’t know how it feels. And we should never be allowed to forget this.

Even as I was feeling like the stupidest person in the room, I also felt an absolute certainty that this wasn’t my fault. Here, too, my experience diverges from that of many learners in the classrooms we study. I knew that my experience was neither right, nor fair, nor my fault; because of this, I knew to curb my strong initial impulse, which was to throw things, to disrupt the class, to walk out and never return. Instead of following my gut, I saved up all that frustration and spent it on a short burst of research. Which is how I got to my second point:


2. Modeling ability is a disposition, one that is (or is not) cultivated through sustained educational focus. Andrea diSessa calls this disposition “metarepresentational competence”; by this, he means a learner’s ability to:

  • Invent or design new representations.
  • Critique and compare the adequacy of representations and judge their suitability for various tasks.
  • Understand the purposes of representations generally and in particular contexts and understand how representations do the work they do for us.
  • Explain representations (i.e., the ability to articulate their competence with the preceding items).
  • Learn new representations quickly and with minimal instruction.

As Richard Lehrer and Leona Schauble point out, model-based reasoning is not only essential to the established practices within many varied domains, but it’s also a set of proficiencies that can and must be cultivated through focused instruction. In offering their own discussion of metarepresentational competence, they write:

Modeling is much more likely to take root and flourish in students who are building on a history of pressing toward meta-representational competence (diSessa, 2004). Developing, revising, and manipulating representations and inscriptions to figure things out, explain, or persuade others are key to modeling but are not typically nurtured in schooling. Instead, students are often taught conventional representational devices as stand-alone topics at a prescribed point in the curriculum, and may be given little or no sense of the kind of problems that these conventions were invented to address. For example, students might be taught in a formulaic manner how to construct pie graphs, but with no problem or question at hand to motivate the utility of that design over any other, students are unlikely to consider the communicational or persuasive trade-offs of that or any alternative representational form.

Though modeling has its application in most, if not all, content areas, it’s typically emphasized in science and math classes and de-emphasized or ignored in the social sciences and reading and writing instruction. At best, students are told to make a timeline to represent the events of the Civil War (without being shown the affordances and constraints of this sort of representation); or they’re required to make a diorama (or, now, a digital version of a diorama) to prove they understand a key scene in a literary text.

Representations don’t always take the shape of graphs or pictures; in fact, we might say that a musical score or a piece of descriptive writing is a representation in its own right. But as Lehrer and Shauble point out, a thing is only a model insofar as it is treated as such. “One might suggest,” they write, “that a pendulum is a model system for periodic motion. Yet, for most, the pendulum simply swings back and forth and does not stand in for anything other than itself.”

Some disciplines, in fact, actively resist the notion of representation, of language as representational. In a previous iteration, I was a poet and even spent several years’ worth of sustained study in an undergraduate, then a graduate, creative writing program. In the MFA program especially, I was immersed in a sustained discipline-wide effort to divorce language from its representative nature. There was an effort to fight against narrative, against what many writer-types believed was “easy” poetry. This is, as poets are wont to remind us, the basis of Postmodernism.

Though I’m in a Learning Sciences graduate program, I am by no means a scientist, at least in the more general sense of the term. This is even more true if we think of modeling as a key element of scientific practice. For multiple reasons, I do not have what diSessa calls “native competence,” which he explains is a proficiency that develops over time both in and out of school. I could point, for example, to the shame I felt in 6th grade when I was required to build a model of the solar system using styrofoam and coat hangers; my final product, the absolute best work I could have done, was pitiful and humiliating. I remember thinking: everyone else can do this; what’s wrong with me?

Now I know it’s not a problem with me but with a system of schooling, which helps me direct my rage outward but still doesn’t really solve the problem of how I’ll ever build a goddam model that makes any sort of sense to anybody at all.

In case you’re interested in reading the work I reference above, here are the citations:

diSessa, A. A. (2004). Metarepresentation: Native competence and targets for instruction. Cognition and Instruction, 22, 293-331.
Lehrer, R., & Schauble, L. (2006). Cultivating Model-Based Reasoning in Science Education. In R. Keith Sawyer (ed.), The Cambridge Handbook of the Learning Sciences. Cambridge: Cambridge University Press.

Posted in academia, conspiracy theories, graduate school, Joshua Danish, learning sciences, Ph.D. | Leave a Comment »

devising a model for technology in education: my version of writer’s block

Posted by Jenna McWilliams on February 2, 2010



I believe the following principles to hold true:

  • Human goals are mediated by, and thenceforth only achieved through, the widespread adoption and use of new technologies.*
  • Human purposes for adopting and making use of new technologies are often highly individualized (though nearly always aligned with an affinity group, even if that group is not explicitly named and even if that group is not comprised of other members of the learning community).
  • While no educational researcher is qualified to articulate achievable goals for another human, the researcher is ethically obligated to support learners in articulating, and achieving, ethical educational goals.
  • The efficacy and success of new technologies can be measured through multiple lenses, among which only one is the achievement of mainstream educational goals as articulated and assessed through traditional, often standardized, measurement tools.

If you (a) know me, (b) follow me on Twitter or a similar social network, or (c) read my blog, you know that being at a loss for something to say just doesn’t happen to me. (On the one hand, this makes me perfectly suited to social media, blogging, and academia; on the other hand, it means I’ll mouth off about the social revolution in nearly any social situation.)

But for weeks now, I’ve been trying to devise a model to represent the role of computational technologies in education. And for weeks, I’ve been failing miserably. Here’s the closest I’ve come:

As you can see, this model is incomplete. I was in the middle of drawing an arrow from that word “technology” to something else when I realized that this model would never, ever do. So I tried to approach modelling from other perspectives. I tried backing my way in, by thinking of technologies metaphorically; I’ve tried presenting technology integration in the form of a decision tree. Which is fine, except that these don’t really work as models.

And I have to come up with a model. I do. Though I don’t often mention this, I’m not actually only a blogger. In real life, I’m a graduate student in Indiana University’s Learning Sciences Program. Because I believe in the value of public intellectual discourse, I’ve chosen to present as much of my coursework as possible on my blog or through other public, persistent and searchable communications platforms.

I will, at some future point, discuss the challenges and benefits of living up to this decision. For now, you guys, I just need to come up with a goddam model that I can live with.

I tried thinking of technologies as sleeping policemen; or, in other words, as objects that mediate our thoughts and actions and that have both intended and unintended consequences. This was a reaction to a set of readings including a chunk of Bonnie Nardi’s and Vicki O’Day’s 1999 book, Information Ecology: Using Technology with Heart; a Burbules & Callister piece from the same year, “The Risky Promises and Promising Risks of New Information Technologies for Education”; and Stahl & Hesse’s 2009 piece, “Practice perspectives in CSCL.” The theme of these writings was: We need to problematize dominant narratives about the role of technologies in education. Burbules & Callister categorize these narratives as follows:

  • computer as panacea (“New technologies will solve everything!”)
  • computer as [neutral] tool (“Technologies have no purpose built into them, and can be used for good or evil!”)
  • computer as [nonneutral] tool (the authors call this “(a) slightly more sophisticated variant” on the “computer as tool perspective”)
  • balanced approach to computer technologies (neither panacea nor tool, but resources with intended and unintended social consequences)

Nardi & O’Day, who basically agree with the categories identified above, argue for the more nuanced approach that they believe emerges when we think of technologies as ecologies, a term which they explain is

intended to evoke an image of biological ecologies with their complex dynamics and diverse species and opportunistic niches for growth. Our purpose in using the ecology metaphor is to foster thought and discussion, to stimulate conversations for action…. [T]he ecology metaphor provides a distinctive, powerful set of organizing properties around which to have conversations. The ecological metaphor suggests several key properties of many environments
in which technology is used.

Which is all fine and dandy, except the argument that precedes and follows the above quote is so tainted by mistrust and despair over the effects of new technologies that it’s hard to imagine that even Nardi and O’Day themselves can believe they’ve presented a balanced analysis. Reading their description of techno-ecologies is kind of like reading a book about prairie dog ecologies prefaced by a sentence like “Jesus Christ I hate those freaking prairie dogs.”

So the description of technologies as sleeping policemen was an effort to step back and describe, with as much detachment as possible for an admitted technorevolutionary like me, the role of technologies in mediating human activity.

But the metaphor doesn’t really have much by way of practical use. What am I going to do, take that model into the classroom and say, well, here’s why your kids aren’t using blogs–as you can see (::points to picture of speed bump::), kids are just driving around the speed bump instead of slowing down….?

This became clear as I jumped into a consideration of so-called “intelligent tutors,” which I described briefly in a previous post. Or, well, the speed bump metaphor might work, but only if we can come up with some agreed-upon end point and also set agreed-upon rules like speed limits and driving routes. But the problem is that even though we might think we all agree on the goals of education, there’s actually tons of discord, both spoken and unspoken. We can’t even all agree that what’s sitting in the middle of that road is actually a speedbump and not, for example, a stop sign. Or a launch ramp.

The Cognitive Tutors described by Kenneth Koedinger and Albert Corbett are a nice example of this. Researchers who embrace these types of learning tools see them as gateways to content mastery. But if you believe, as I do, that the content students are required to master is too often slanted in favor of members of dominant groups and against the typically underprivileged, underserved, and underheard members of our society, then Cognitive Tutors start to look less like gateways and more like gatekeepers. Even the tutoring tools that lead to demonstrable gains on standard assessments, well…ya gotta believe in the tests in order to believe in the gains, right?

So I’m back to this:

A “model,” explains Wikipedia,

is a simplified abstract view of the complex reality. A scientific model represents empirical objects, phenomena, and physical processes in a logical way. Attempts to formalize the principles of the empirical sciences, use an interpretation to model reality, in the same way logicians axiomatize the principles of logic. The aim of these attempts is to construct a formal system for which reality is the only interpretation. The world is an interpretation (or model) of these sciences, only insofar as these sciences are true….

Modelling refers to the process of generating a model as a conceptual representation of some phenomenon. Typically a model will refer only to some aspects of the phenomenon in question, and two models of the same phenomenon may be essentially different, that is in which the difference is more than just a simple renaming. This may be due to differing requirements of the model’s end users or to conceptual or aesthetic differences by the modellers and decisions made during the modelling process. Aesthetic considerations that may influence the structure of a model might be the modeller’s preference for a reduced ontology, preferences regarding probabilistic models vis-a-vis deterministic ones, discrete vs continuous time etc. For this reason users of a model need to understand the model’s original purpose and the assumptions of its validity.

I’m back at the original, simple, incomplete model because I’m not ready to stand in defense of any truth claims that a more complete model might make. Even this incomplete version, though, helps me to start articulating the characteristics of any model representing the role of computational technologies in education. I believe the following principles to hold true:

  • Human goals are mediated by, and thenceforth only achieved through, the widespread adoption and use of new technologies.
  • Human purposes for adopting and making use of new technologies are often highly individualized (though nearly always aligned with an affinity group, even if that group is not explicitly named and even if that group is not comprised of other members of the learning community).
  • While no educational researcher is qualified to articulate achievable goals for another human, the researcher is ethically obligated to support learners in articulating, and achieving, ethical educational goals.
  • The efficacy and success of new technologies can be measured through multiple lenses, among which only one is the achievement of mainstream educational goals as articulated and assessed through traditional, often standardized, measurement tools.

Ok, so what do you think?

*Note: I’m kinda rethinking this one. It reads a little too deterministic to me now, a mere hour or so after I wrote it.

Posted in academia, education, graduate school, lame, obnoxious, patent pending, public schools, schools, social media, social revolution, teaching, technologies | Leave a Comment »

you have to watch this vlogpost

Posted by Jenna McWilliams on October 27, 2009

file under: world’s most awesome 16-hour vlog project

This link to pure awesomeness comes to you courtesy of my buddies, Jeffrey Kaplan and David Phelps. If you care about literacy or the learning sciences, you will die of joy.

Posted in awesome, creativity, graduate school, joy, learning sciences, literacy, poetry | 1 Comment »

my first vlogpost: how blogging has shaped my reading and writing practices

Posted by Jenna McWilliams on September 27, 2009

You guys, I think this is my very first vlogpost.

According to Wikipedia, video-blogging, or vlogging, is

a form of blogging for which the medium is video.Entries are made regularly and often combine embedded video or a video link with supporting text, images, and other metadata. Entries can be recorded in one take or cut into multiple parts.

The open content site at public radio station WGBH clumps vlogs with blogs and offers one definition for both; presumably, this means that both offer the same kind of content, using different media delivery formats.

In that case, here you go: my very first vlogpost, a video project (filmed and edited by me!) explaining how I read and write through my primary identity as a blogger.

Posted in blogging, graduate school, literacy, reading, writing | 2 Comments »