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 ‘academia’ Category

MIT quits open-source Kuali project

Posted by Jenna McWilliams on June 18, 2010

What happened: Recently, MIT announced it would discontinue partnership with the Kuali foundation on an open-source project called Kuali Student. This came, according to an official press release, after extensive discussions with board members and people and groups directly involved in developing this student-administration software.

What the press release didn’t say is why MIT made this decision. It seems likely that the decision was financial. According to a Chronicle of Higher Education article, MIT is the second higher education institution in the last several months to pull out of Kuali Student; Florida State University withdrew in February due to budget cuts.

Why it matters: MIT has been a strong and vocal supporter of openness in higher education and research. During my employ at the Institute, administrators officially adopted an open access policy which was designed to support the widest possible circulation of ideas, projects, and research generated by MIT-affiliated researchers. MIT has embraced the open education movement, investing copious time, energy, and dollars into its OpenCourseWare project.

If MIT’s decision to withdraw from Kuali Student is primarily a cost-cutting measure–and again, we don’t know for sure if this is the rationale–this does not bode well for open education. It’s all too easy to treat the idea of openness as a luxury worth pursuing during times of plenty and simple to abandon during times of famine. But the openness movement, in all its iterations (software, hardware, education, access, and so on), is not a luxury. It’s a necessity. Transparency problems are part of what got us into this mess in the first place, especially in higher education where access to high-quality learning is still sequestered off behind a series of wrought-iron gates that cost too much–too much time, too much money, too much sacrifice–for many of our learners to be willing or able to gain entry.

We are no longer in an era where we can afford to make powerful, empowering education available only to the few. Indeed, one can easily argue that it’s not openness but opacity that is the luxury.

Posted in academia, education, intellectual property, MIT, open education, open source | 1 Comment »

omg I just talked to Howard Rheingold

Posted by Jenna McWilliams on June 16, 2010

You can keep your Robert Pattinsons and Miley Cyruses and whichever other beautiful prepubescent sexy people you young people idolize these days. My idols are people like these folks:

That guy in the lower lefthand corner is Howard Rheingold, who is by just about all accounts one of the kindest, happiest, most curious, most fascinating, most colorful, and most thought-provoking media theorists around. (If you want proof, take a look at this little gem of his writing.)

Because Howard is kind and supportive of other aspiring intellectuals, I’ve had email conversations and twitter conversations and blog conversations with Howard. There’s this interesting feature of the new technologies that swell around us, see: They efface the distance–perceived and real–between our idols and our selves. If you’re patient enough and quick enough, you can use these new technologies to climb right up on the pedestals your heroes are standing on and tap them on the shoulder.

And today in a webchat I got to talk to Howard–with my voice–about crap detection, participatory culture, and pedagogy. It. Was. Awesome.

It may soon enough be the case that the structures and norms that allowed us to toss up celebrities and intellectuals as cultural heroes–well, it may soon enough be the case that those structures crumble, leaving our heroes in the rubble at our feet. I’m young enough to hope it’ll happen in my lifetime but old enough that I may not be able to fully shake the notion of the celebrity as icon. After all, I grew up alongside this:

And yes, I know that a huge chunk of Americans have never even heard of Howard Rheingold (or Lisa Delpit or Paulo Freire or Jim Gee or Henry Jenkins or Yasmin Kafai) and that these people don’t count as ‘celebrities,’ as least not in the “zomg the paparazzi are everywhere” sense. I don’t care. As Intel explains, our rock stars aren’t like your rock stars.

Posted in academia, academics, awesome, blogging, fannish, Henry Jenkins, Howard Rheingold, Jim Gee, joy | 2 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 »

how Jim Gee and I soothe our guilty consciences

Posted by Jenna McWilliams on June 8, 2010

In the video below of a presentation to the Education Writers Association 2010 Annual Conference, Jim Gee says this about how to introduce innovative ideas into education:

There’s a choice of strategies here…. One strategy is: Let’s take our innovations to the center of the school system and spread them as fast and quickly as we can. People believe that this current school system as it is will just co-opt those innovations and make them … just better ways to do the old thing. Another strategy is: Let’s make these innovative learning and assessment tools and put them at the margins, in places that will tolerate innovation, and then show it works. Now if you think about it, in technology outside of schools, going to the margins first and then to the center–that’s always been the way innovation happens. The only place we’ve ever tried to keep putting the new thing right in the center at once is in schooling, and it’s never worked. What i would love to see is that we hive of some of the (Race to the Top) money for a national center that would trial these new assessments, show they work in places that tolerate innovation, and then spread them there, just the way you would want if we have to keep coal and oil–let’s at least have something trying out new forms of energy, so that we’re ready for these markets but also we can prove they work. if we don’t do that, we’re just gonna get a better mousetrap.

I absolutely agree with the sentiments in the quote above, except for the BP oil spill. Let’s say there’s some innovative energy research going on in the margins, ready to prove it works and to take over where coal and oil left off. That’s fantastic, and it doesn’t do a single goddamned thing to help the birds, the fish, the sea mammals, the tourist industry, the ecosystem, the fisheries, and the human residents of the Gulf Coast. Those are simply casualties, not a single thing we can do to help them now no matter what awesome innovative fuel source we finally embrace, no matter how much more quickly we may embrace a cleaner fuel source as a result. Even if tomorrow’s birds are safe from Big Oil, today’s birds are drowning right in front of us.

Working at the margins of education is a fantastic way to innovate and offer useful evidence that innovations work. I fully support this approach–but not at the expense of the kids who exist at the center of our education system today. Yes, the school system can and does and maybe always will co-opt any innovation we try to introduce. But that doesn’t excuse us from trying anyway. That doesn’t give us license to give up on today’s children, even if it keeps tomorrow’s children safe.

And of course this isn’t what Jim Gee wants to do, anyway. But the Jim Gees of the world who urge us to work at the margin live in symbiosis with the Jenna McWilliamses of the world who believe we must also work from the center, where–ironically–the most marginalized kids in education commonly reside. I can’t innovate as much as I’d like from the center, maybe I can’t help tomorrow’s marginalized kids as much as I’d like either.  And Jim Gee can’t help today’s marginalized kids as much as he’d probably like from the edges. So we need each other, if for nothing else than to assuage our guilty consciences for being unable to do more of what we know must be done.

I should probably also note that Jim Gee is one of my absolute all-time heroes, so I hope he’s not mad at me for this post.

This video also stars Daniel Schwartz, who I believe is one of the smartest guys thinking about assessment and learning these days. I had the great luck to attend an assessment working group with him and a big crew of assessment-focused researchers, and I was amazed and blown away by just about everything he said.

In a recent publication, Choice-Based Assessments in a Digital Age (.pdf), Schwartz and his co-author Dylan Arena make this argument:

Educational assessment is a normative endeavor: The ideal assessment both reflects and reinforces educational goals that society deems valuable. A fundamental goal of education is to prepare students to act independently in the world—which is to say, to make good choices. It follows that an ideal assessment would measure how well we are preparing students to do so.

I can’t remember when I’ve agreed more emphatically with the introductory sentence of a scholarly article about education.

Here’s the video, which is well worth a watch.

Posted in academia, assessment, education, Jim Gee, journalism, learning sciences, public schools, schools, teaching, technologies, video games | 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 »

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 »

NRA types should maybe just be quiet for a while: some thoughts on the University of Alabama shooting

Posted by Jenna McWilliams on February 13, 2010

I find it painfully appalling that some people are using the recent shooting on the campus of the University of Alabama-Huntsville to make arguments for looser gun control policies.

Details are still somewhat sketchy, but it appears that the perpetrator was a faculty member who was denied tenure. Biology professor Amy Bishop apparently brought a gun to a faculty meeting and, after learning she had been denied tenure for the second time in her career at Alabama, opened fire on her colleagues. Three people were killed and three others were wounded.

It beggars belief to hear some people arguing that the solution to incidents like this is actually more guns. According to msnbc, one student at the university said that she had requested that students with gun permits be allowed to carry their guns on campus and was turned down.

“I’m scared to go back to school,” (the student) said. “However, if they were to allow me to carry my pistol on campus, I would not be as scared…. I’m sorry that nobody in that room had a pistol to save at least one person’s life.”

To sum up, here’s the argument that the above student and others like her are making: that we need to allow more people to carry more weapons in more places. I reject outright such a monstrously irresponsible stance. Giving more people access to more guns is what makes America the gold-medal winner in First-World Gun Deaths.

And I don’t want to hear the argument that stricter gun control laws won’t stop gun violence since criminals and emotionally disturbed people like the woman who allegedly carried out yesterday’s campus shooting will always find ways to get their hands on weapons. That may very well be true, but looser gun control laws only make it more likely that those people will get their hands on weapons, while increasing the likelihood of more deaths resulting from their attacks.

Are you going to tell me that if anybody at that faculty meeting had been carrying a gun, they would have had the presence of mind to pull it out, aim it, and take a shot before Bishop opened fire?

Are you going to tell me that putting guns in the hands of young adults who are passing through some of the most emotionally tumultuous times in their lives is by any stretch of the imagination a smart idea? Drunk kids at house parties? Young romantics who have been spurned by the targets of their affections? Academically ambitious students for whom the C they just received in a class may end their dreams of becoming a lawyer or doctor?

Using shooting rampages to argue for looser gun control laws not only makes for a really bad argument, but it’s also socially irresponsible to an appalling degree.

Posted in academia, law, rage | 3 Comments »

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 »

"Math class is tough!" a few thoughts on a problematic metaphor for learning

Posted by Jenna McWilliams on January 21, 2010

Academics, and especially academics who think about culture (which is to say, more or less, all academics), seem to really like metaphors and similes. Here’s one that made me mad this week.

Jim Greeno: Learning how to participate is like being in a kitchen.
Situativity theorist Jim Greeno, in “Number Sense as Situated Knowing in a Conceptual Domain,” considers how people develop conceptual models for participating in disciplinary communities (what he calls “conceptual environments”). He explains that

knowing how to construct models in a domain is like knowing how to work in an environment that has resources for a kind of constructive activity, such as a woodworking shop or a kitchen.

A shop or a kitchen has objects, materials, and tools that can be used to make things. Knowing how to work in such an environment includes knowing what objects and materials are needed for various constructive activities, knowing where to find those objects and materials in the environment, knowing what implements and processes are useful for constructing various things, knowing how to find the implements, and knowing how to use the implements and operate the processes in making the things that can be made.

In constructing conceptual models, the ingredients are representations of specific examples of concepts…. We can think of the conceptual domain as an environment that has representations of concept-examples stored in various places. Knowing where to find these, knowing how to combine them into patterns that form models, and knowing how to operate on the patterns constitute knowledge of the conceptual domain. The representations of concept-examples have to be understood in a special way. They are not only objects that are drawn on paper or represented in the mind. They are objects in the stronger sense that their properties and relations interact in ways that are consistent with the constraints of the domain.

This example would be fine if everybody agreed on a.) where everything belongs in a kitchen; b.) what everything in the kitchen should be used for; c.) what activities afforded by the kitchen are most appropriate; and d.) whether the kitchen is appropriately and effectively designed.

Let’s say, just for kicks, that the cabinets are made for glass and have been installed at just the right height for someone who is, say, at least 5 feet 9.2 inches tall. I’m 5’3″. If I want to get to the materials I need to, I’m going to need to find something to stand on.

If there’s nothing to stand on (and if most people who use the kitchen stand around 5 feet 9 inches, there would be no reason to keep stepstools or the like around), I might try to climb up onto the counters. I might try to find some sort of utensil–a spatula, maybe, or a wooden spoon–to help me access the ingredients I need. If I’m really desperate, I might try to throw things in an effort to shatter the glass cabinet.

To an outside observor, none of the above activities would appear appropriate in the kitchen setting. The spatula is made for cooking, not for prying open cabinets. And shattering glass cabinets–that’s just destructive.

You see my point, I hope.

Then there’s the unavoidable issue of choice of metaphor. Greeno offers a kitchen or a woodworking shop, which we might say is a nice way to offer one example for each gender! But though it’s true that Greeno doesn’t take it a step farther to prescribe who gets to enter which type of space, the gendered nature of the examples is undeniable. These examples are not neutral, just as the practices that occur in the examples are not benign, at least not always, and not for everybody.

Metaphors do lots of good work for us; indeed, it may be that our entire culture rests on a bed of shared metaphors. As Bonnie Nardi and Vicki O’Day write in their 2000 book Information ecologies: using technology with heart,

Metaphors are a useful form of shorthand…. But it is important to recognize that all metaphors channel and limit our thinking, as well as bring in useful associations from other contexts. That is the purpose of a metaphor, after all–to steer us to think about the topic this way rather than some other way.

What are you doing? Stop–stop throwing soup cans at the cabinets! You’re liable to break something!

To which you respond: I never liked tomato soup much anyway. And I sure as hell hate glass cabinets. Good riddance, you say, even as you’re being hustled out of the kitchen. Good–

And that’s when you realize they’ve shut the door behind you. Maybe even locked it. See what kind of trouble metaphors get us into?

Posted in academia, education, feminism, gender politics, language, learning sciences, social justice, teaching | Leave a Comment »