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 ‘literacy’ Category

SparkCBC takes on the issue of computational literacy

Posted by Jenna McWilliams on March 23, 2010

As I’ve explained in previous blog posts, I’m a fan of incorporating computational literacy education into the formal classroom–across curricula and content areas. So I was thrilled to see Spark Radio will be tackling the issue of computational literacy in an upcoming broadcast. Spark co-producer Dan Misener explains, using the user-friendly iPad as an example:

(T)he iPad (and its little brothers, the iPhone and iPod touch) abstract much of the computer away. Apple watcher and former Spark guest John Gruber says it’s a bit like the automatic transmission in a car:

Used to be that to drive a car, you, the driver, needed to operate a clutch pedal and gear shifter and manually change gears for the transmission as you accelerated and decelerated. Then came the automatic transmission. With an automatic, the transmission is entirely abstracted away. The clutch is gone. To go faster, you just press harder on the gas pedal.

That’s where Apple is taking computing. A car with an automatic transmission still shifts gears; the driver just doesn’t need to know about it. A computer running iPhone OS still has a hierarchical file system; the user just never sees it.

And from the standpoint of the vast majority of computer users, this abstraction can be a good thing. It makes computing simpler, easier, friendlier. Why should I need to understand what’s going on under the hood of my computer if all I want to do is send email to my friends?…

But I wonder, is the same attitude towards computers dangerous? Does oversimplifying technology –removing necessary complexity — have a downside? By making technology simple, easy, and convenient, do we risk a generation of people who can’t tell the difference between this blog post and the Facebook login page?

As I ponder this, I’m a bit torn. The technology populist in me wants to say, “Of course, make computers easy! What’s wrong with making computers as simple and friendly as possible?”

But another (geekier, snobbier) part of me wants to say, “Yes, computers are hard, and that can be a good thing. I don’t want to use technology designed for the lowest common denominator.”

The question this Spark show hopes to tackle is this:

If I don’t understand how to use my computer, whose fault is it? Is it my fault for not wanting to read manuals or spend time learning a new technology? Or is it the fault of the designers and engineers who build the technology we use?

You can weigh in on the discussion at the Spark blog, then listen in live or or download the podcast of the show; information on broadcast times and podcast download is available here.

Here’s my take on this issue, which I’ve also posted as a comment on the Spark blog:

This is a thorny issue, because easier interfaces help to drop the barriers to participation, but on the other hand this shift means we give up some degree of empowerment to make decisions about which sorts of interfaces, and by extension which sorts of technologies, work best for our specific needs. Indeed, the crafting and marketing of products like the iPad is deeply, deeply political, and the embedded politics that lead to the tools we use is not readily evident to those without a degree of computational literacy. And enormous swaths of the computer-using public are lacking in this area.

On the other hand, computational literacy is very much like other forms of literacy: reading, writing, mathematical literacy, and so on. We don’t blame the math-illiterate learner who has never been exposed to mathematics education, or whose math education was lacking in significant ways. This is the exact case with computational literacy education: It’s nearly nonexistent in formal classrooms, and has become the nearly exclusive domain of those with the luxury of access to computational technologies outside of school. In some ways, then, perhaps we get the technologies we deserve.

Posted in Apple, computational literacy, education, literacy, participatory culture, politics, reading, technologies, writing | 3 Comments »

notes from the {computational} revolution

Posted by Jenna McWilliams on March 2, 2010

As part of an ongoing effort to design a model for integrating computational technologies into the formal classroom, I have turned my focus to computational literacy. My current model already has a space for considering computational literacy, so in this post I want to spend some time exploring my definition of computational literacy. This includes a discussion of the key features of computational literacy and how these features might be taught. The models I’ve created are included at the end of this post.

I started learning to play the flute at age 8. I kept it up for 10 years. At age 15, I took a typing class and surprised myself by how easily I mastered the QWERTY system. At my fastest (in my early 20’s, when I was a reporter), I could type more than 160 words per minute. I’m a fan of languages, studied French from high school all the way through a master’s-level class, picked up enough German during a 2-week visit to Austria to order my food, ask for directions, and hold a basic conversation with a native Austrian. I studied computer science for about a minute in college –I hated it, I was no good at it–but I’ve taken to html, CSS, and other simple programming languages that support my ongoing efforts at web-based social revolution. I don’t understand, though I wish I did, the inner workings of computer hardware. I don’t understand the difference between Newtonian and pre-Newtonian physics, though I know the pre-Newtonian stuff is naive and kinda wrong. I build web pages for fun, mainly relying on templates but recently branching off into my own web design. Fairly soon, in fact, I will be leaving Blogspot behind in order to build a brand new website to my exact specifications. I have an M.F.A. in Creative Writing, with an emphasis in poetry.

I don’t understand physics. I don’t like most programming languages. I play the flute and like to tinker with language. I’m a fast typist but a slow web designer. I am a computational thinker.

Computational literacy is like all true categories of literacy: a cluster of practices whose meaning emerges as the learner deploys those practices in increasingly knowledgeable, increasingly socially valuable ways.

And increasingly, computational literacy is both part of and separate from other clusters of literacy practices. Computational proficiencies are similar to but distinct from those proficiencies we label “new media literacies,” and they’re similar to but distinct from those proficiencies we label, for lack of a better phrase, “traditional literacies.” They’re often but not always, and not fully, aligned with the “hacker mentality”: an attitude that treats nearly everything as potentially bendable to the user’s will.

Like all other forms of literacy, computational literacy can be taught–though not if we treat it, as Jeanette Wing does in her 2008 treatise “Computational thinking and thinking about computing,” as a set of abstractions. Wing writes that “the nuts and bolts in computational thinking are defining abstractions, working with multiple layers of abstraction and understanding the relationships among the different layers. Abstractions are the ‘mental’ tools of computing.”

You don’t have to be much of a hacker to know that Wing misses something essential here. It may be that the language of a program is abstract, and that programming is dealing in abstractions, but only in the sense that letters, words, and sentences are abstractions leading to language. Even fairly young children develop an innate sense of grammar and know when a speech act violates the rules.

This is to say that the elements of language may very well be abstract communicative units, but native speakers develop a concrete mastery over their language nonetheless. (Though this mastery is often belied by our near absolute inability to articulate a single grammar rule.)

Teaching in support of computational literacy
My focus is on the English / Language Arts classroom, or what I’ve lately been calling the “literacy sciences” classroom. In describing the categories below, then, I’ve included a few ideas about how these aspects of computational literacy might be fostered in the secondary literacy sciences classroom.

I believe that computational literacy is comprised of the following sets of proficiencies:


Programming skill: This may include proficiency with one or more programming languages; or it may include creativity with language (the primary programming language of our culture); or it may include mathematical or scientific know-how.

What to teach: Basic web design can help to foster some foundational programming skills. Students might start a blog or, working within a closed social network like Ning, build personal profile pages complete with modified color templates and extra widgets. For many, the notion that what users see gets controlled by a kind of puppet master can be both surprising and empowering.

Technical expertise: Colin Lankshear and Michele Knobel might refer to this category as “the technical stuff.” One feature of new media, for example, is its modularity–the ease with which we can copy, remix, and move media elements. Technical ability includes facility with the tools that allow for this kind of work, as well as ease with unfamiliar interfaces and comfort with just-in-time learning.

What to teach: I’ll never forget hearing games and education expert Katie Salen talk about the approach her Quest2Learn school takes toward computer literacy. She wondered why we have computer classes where kids learn how to use word processing, spreadsheet, and similar programs instead of folding that instruction into authentic learning experiences. “Why not teach kids how to use Word in the context of having to write something for their English class?” she asked. And she’s right. Of course, this means that English teachers will need to start developing more technical know-how–we’re long past the days when facility with Microsoft Word was a sufficient condition for effective writing, even in the English classroom. Let’s start having students use email programs, work with social networks, do some basic image and video editing with the programs that come standard on most newer computer systems.

Hand-eye coordination: Another feature of new technologies is that they often stretch across the virtual and the physical. I busted laptop screens and frayed charging cables until I learned to work with the physical affordances of computing technologies; I’m graced with excellent typing skills; these make any task that requires text generation between 20 and 40 percent easier than they would be for the typist of a more average speed.

What to teach: Typing is of course an important skill, though many kids build up their dexterity through text messaging. I’m going to argue for the practice of building things in the English classroom. There is, for example, the brilliant piece of rhetoric embodied in this recent OkGo music video:

You can’t tell me that the building of that enormous mousetrap didn’t foster not only increased hand-eye coordination but a deeper sense of space and rhetoric, as well. We may not have the tools for building a better mousetrap in the typical classroom, but the building of small sets for video productions, the designing of costumes and backdrops and other visuals, can help support increased motor confidence in learners.

Visual literacy: Lev Manovich explains the visual basis for all digital media, and even goes so far as to explain that even the very letters and numbers we see on our computer screens have been converted into binary code, then converted back into visual representations so that we can easily make sense of the information. This brings a new imperative to visual literacy. Previously, visual literacy was treated as the ability to think critically about advertising, television, and films; today, we add a near-limitless number of visual media formats in addition to our new roles as producers of visual media in addition to our role as consumers.


What to teach: Visual rhetoric is a growing field. Many teachers are already incorporating video projects, website design, and other forms of visual rhetoric into their classrooms, and we can look to them for advice on how to proceed in this area.

Tolerance for tinkering: Pastimes like crocheting, woodworking, and gardening took up time but didn’t necessarily take up all of our attention. When we weren’t counting or focusing on a particularly difficult maneuver, we could talk or watch TV or sing a song. Coding doesn’t allow for this split of attention. Neither does building a digital scrapbook or designing a webpage or building a virtual model. At best we can devote all of our attention for a time to the code, then shift our full attention away, then shift our full attention back again. Mimi Ito and her colleagues talk about “geeking out,” and part of geeking out is hours passed immersed in one activity or another, sometimes to the exclusion of all else. As a culture, we haven’t really had much tolerance for geeking out, though that’s starting to change. What we need now is to build up a tolerance for geeking out in our learners. There are those who argue that we lost something when young people stopped reading books–that those children lost the ability to immerse themselves in an entire world. It’s possible that what’s been lost in the decline of books can be compensated for through the emergence of computational thinking–of geeking out.

What to teach: Immersive, lengthy projects. We might consider trying to turn the classroom into a structured workshop space, much as fine arts programs balance studio time with critique. We’re already halfway there with peer review and collaborative activities; if we can just shift the focus away from critique and toward construction of powerful projects, we can easily build a tinkering-tolerant learning community.

I’m not saying it’s easy to support computational literacy in the formal classroom. What I am saying is that it’s necessary.






Posted in education, Joshua Danish, literacy, reading, social revolution, teaching, writing | 5 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 »

a model for designing the ELA classroom in support of "literacy science"

Posted by Jenna McWilliams on February 7, 2010

You guys, I think I have a model to show you.

This makes me extremely happy, because as I’ve explained (more than once), I’ve struggled mightily with the very concept of modeling. I’ve also struggled with representation. The purpose of designing this model is to show my take on the role of new technologies in educational environments. But articulating a theory, even a working theory, about the role of technologies has been such an insurmountable challenge for me–which technologies? for which students? and for what purpose?

But the elements for building this rudimentary model have been around me for some time. It just took time and reflection for me to be able to put the elements together.

(image description: this is a pen-and-ink drawing of a classroom. In the center of the room, the class is seated, facing each other, around a square of tables; on the table in front of them are combinations of books, notebooks, and electronic equipment. Around the edges of the room are, clockwise from the upper lefthand corner: an easel labeled “representational literacy;” a table with extra pens and extra notebooks; a chalkboard with a variety of marks on it, labeled “design thinking”; book shelves; a workbench labeled “computational literacy”; open space lining most of one wall; a laptop labeled “new media literacy”; a safe filled with bundles of cash; and a laptop cart. Below the picture is the phrase, “If you can’t build it, then you don’t understand it.”)

Inspiration for this model
Design of the periphery: Multiple intelligences schools. A few years ago, I read the 25-anniversary edition of Howard Gardner’s Multiple Intelligences. Throughout the book, Gardner describes a variety of approaches to integrating his theory of multiple intelligences into learning environments, and one description–of the Key Learning Community in Indianapolis–has stuck with me. In this school, students work in “pods” that represent each type of intelligence outlined by Gardner; a founding principle of this school, he explains, “is the conviction that each child should have his or her multiple intelligences stimulated each day. Thus, every student at the school participates regularly in the activities of computing, music, and bodily-kinesthetics, in addition to mastering theme-centered curricula that embody standard literacies and subject matter.”

You don’t have to agree with this approach to appreciate its effort at offering a range of avenues for learning to happen. From time to time I think about those multiple intelligences schools and wonder what aspects might be applied to my current area of focus, the English / Language Arts classroom. Clearly, more avenues toward literacy is better than fewer avenues; and since we know that traditional literacy practices taught through traditional means are insufficient preparation for the types of literacy practices people are called upon to demonstrate in real life, we might think of “pods” for different groupings or categories of literacy learning.

Design of the center and periphery: A real life ELA classroom. I’ve had the unBELIEVABLE good luck to sit in on Becky Rupert’s ELA classroom at Aurora Alternative High School here in Bloomington, IN. Much of the design of this model is based on how she has arranged her class. To begin with, the main focus of the room is a square of tables where students meet at the beginning of each class. My model does not identify the teacher’s location; that’s because in Becky’s classroom, she sits at the table right alongside her students. She does this on purpose, and it works in service of developing a learning community.

Becky’s classroom is absolutely stuffed with books–you have to move books in order to get to other books. A new addition this year is a laptop cart, which sits against the far wall of the room.


Inclusion of design thinking: my work with SociaLens. For the last several months, I’ve been working with a new organization called SociaLens. The purpose of this organization is to consult with businesses and offer strategies for integrating new types of communications tools and ways of thinking into their organizational plans, with a particular eye toward social media technologies. Two key categories that we think make for highly adaptive, potentially highly successful organizations are new media literacies and design thinking.

Until I started working with SociaLens, I had not thought to consider the connection between these categories. I also hadn’t thought about what educational researchers can learn from corporate innovators and vice versa. But what has been seen cannot now be unseen. I’ve come to see design thinking as an essential element of literacy learning, and especially if you believe (as I do) that computational flexibility (which I’ll describe briefly below) is key to preparation for success in a new media age.


Inclusion of new media literacy, representational literacy, design thinking, & computational literacy “pods”: Some stuff I’ve read. I’ve been immersed in new media literacy research for a good chunk of years, and I drank that kool-aid long ago. If you believe in the value of teaching new media literacy practices in schools, then computational literacy kind of comes with the territory. These categories of literacy are similar in lots of respects: Both are better described as a set of proficiencies and attitudes–what Lankshear and Knobel call a combination of “technical stuff” and “ethos stuff”–than as concrete, teachable skills. Both require a kind of openness–a flexibility–to meet the quickly changing demands with emerging technologies. But new media literacies are the required skills to engage in collaborative knowledge-building or collective meaning-making or problem-solving activities, while computational literacy is, in my mind, linked to a kind of “hacker’s mentality.” It’s the act of simultaneously making use of and resisting the affordances of any technology; of knowing when and how to say “no” if a technology doesn’t meet your purposes; and of finding (or developing) a new technology that better meets your needs and interests.

Design thinking, as I mention above, comes out of my work with SociaLens and the (admittedly very surface-level) reading I’ve done about this approach to problem-solving. This type of thinking has also made an appearance in the recent work I’ve been reading about research in science and math instruction. Many researchers whose work focuses on supporting an inquiry-based focus in science instruction, in particular, emphasize the value of embracing the epistemological basis of science-as-inquiry. As William Sandoval and Brian Reiser explain in their 2004 piece, “Explanation-Driven Inquiry: Integrating Conceptual and Epistemic Scaffolds for Scientific Inquiry,” the epistemic elements of this approach include

knowledge of the kinds of questions that can be answered through inquiry, the kinds of methods that are accepted within disciplines for generating data, and standards for what count as legitimate interpretations of data, including explanations, models, and theories. Placing these epistemic aspects of scientific practice in the foreground of inquiry may help students to understand and better conduct inquiry, as well as provide a context to overtly examine the epistemological commitments underlying it.

Wilensky & Reisman, in their work with computer-based modeling, argue in support of what they call “the engineer’s dictum”: “If you can’t build it, then you don’t understand it.” They work with a modeling language called NetLogo, which is a loose descendant of Seymour Papert’s Logo program. The program requires students to solve problems by developing models of real-world processes like population fluctuation within predator-prey (wolf-sheep) communities and the phenomenon of fireflies synchronizing their flashes. The authors make a strong case that model-based thinking–or what we might also call “design thinking”–is key to students’ ability to engage in deep learning about a specific phenomenon and about scientific inquiry more broadly.

I included a pod for “representational literacy” in this model because of my own recent experience grappling with model-building. The ability to design, critique, and modify representational models is a set of skills with relevance across content areas, and we don’t typically think of it as extremely valuable in the literacy classroom. But it should be news to nobody that “literacy” is becoming an increasingly visual category of proficiencies, and that representational literacy is quickly becoming even more tightly bound up with traditional literacies than it ever was before.

What I haven’t yet noted is that these categories of literacy practices make up what we might call “literacy science.” I mean this term to hold the same place in the literacy classroom as “mathematician” or “scientist” or “historian” or “musician” hold in their respective classroom-based environments. As a culture, we haven’t spent enough time yet thinking about the purpose we hope the new literacy classroom to serve. Science class is supposed, ideally, to get students thinking like scientists; in math class you (ideally) learn to think like a mathematician; in history class you think like a historian; but in general English class has been designed as a sort of catch-all, a place where students can learn the basic reading and writing skills that enable them to think like historians, mathematicians, and so on.

What if we shifted the focus of the ELA classroom to more explicitly broach the notion of “literacy science”: A way of being in the (literate) world characterized by an ethos, a set of skills, and a set of norms and behaviors? What would it mean to turn the ELA classroom into a place where we support the growth of literacy scientists?


Inclusion of open space: a nod to the future work of literacy science. Howard Gardner’s list of multiple intelligences has grown over the years, and my model is designed to accommodate new categories of literacy practices. Filling up the entire classroom does nobody any good, especially since we know–we absolutely know–that new valued practices are emerging along with the breakneck speed of emergent technologies.

I should mention, too, that my model includes a safe filled with bundles of cash. This is a nod not only to the future work of literacy science but also to the current conditions of the typical public school. On top of the training required, every one of the pods in my model costs money, and it’s money that schools simply don’t have.

So that’s it: That’s my current model for the role of technologies in the literacy classroom. I would love to know your thoughts. Comments, questions, and suggestions are most welcome and will be read with great joy, thoughtfulness, and enthusiasm.

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

Wilensky, U. & Reisman, K. (2006). Thinking like a Wolf, a Sheep or a Firefly: Learning Biology through Constructing and Testing Computational Theories — an Embodied Modeling Approach. Cognition & Instruction, 24(2), pp. 171-209. http://ccl.northwestern.edu/papers/wolfsheep.pdf.

Sandoval, W., A., & Reiser, B.J. (2004). Explanation-driven inquiry: Integrating conceptual and epistemic scaffolds for scientific inquiry. Science Education, 88:3, 345-372.

Posted in creativity, education, Joshua Danish, learning sciences, literacy, new media, participatory culture, pedagogy, schools, teaching | Leave a Comment »

let’s all agree to pretend it’s not ironic that we ask experts to weigh in on the changing nature of expertise

Posted by Jenna McWilliams on November 20, 2009

An astounding phenomenon of participatory culture is this: If you toss yourself around in it enough, and you bang hard enough on everything you think might be a door, and you try to do your very best to toss yourself around and bang on doors in articulate, responsible, and interesting ways, sometimes you get lucky and someone opens the door to figure out what all the ruckus is about.

I got lucky this week, when CBC Radio called to interview me about new media literacy. The resulting interview, posted to the CBC program Spark, was my chance to try to say something reasonably articulate and unembarrassing about strategies for navigating the new credibility issues that emerge out of a cultural moment in which, as National Writing Project Co-Director Elyse Eidman-Aadahl put it in a recent panel on digital writing, we have the technologies and the potential to foster universal authorship in tandem with universal literacy.

The interview, with Spark host Nora Young, has been posted in full online (here and here). A shorter version will air on CBC Radio soon. Try not to pay attention to the eye-crossing, jaw-dropping irony of the argument I make that the very nature of expertise and credibility have changed, all the while acting as if I were an expert on the issue of expertise.

Another interesting feature of participatory culture is that there are still plenty of opportunities for people to act as the Sage on the Stage, despite the fact that the wisdom they impart often comes through deep collaboration and interaction with many people. In this case, the ideas I brought to this interview came through conversation with my buddies Rafi Santo, Katie Clinton, Michelle Honeyford and Becky Rupert. It’s strange to me sometimes that the person who makes the most noise so often ends up being the one who gets handed the bullhorn and an audience to address.

By the way, the example I give of the stakes in finding out the year Mickey Mantle was born came directly from Rafi Santo. I stole it and he deserves all the credit.

Posted in awesome, literacy, participatory culture | Leave a Comment »

a note on critical computational literacy

Posted by Jenna McWilliams on November 9, 2009

In Changing Minds: Computers, Learning, and Literacy, Andrea DiSessa sets forth a definition of literacy that emphasizes the socially constructed nature of the term. He writes:

Literacy is a socially widespread patterned deployment of skills and capabilities in a context of material support (that is, an exercise of material intelligence) to achieve valued intellectual ends….

Although I wring just a bit more specificity out of our preliminary definition in a moment, there is a fundamental lesson here. We must recognize an inescapable diversity in the phenomenon of literacy. There is no essential, common basis of literacy along any of the dimensions listed or along any other similar ones. There are no fixed basic human skills on which it builds.

DiSessa’s point, quite simply, is that we should never forget that the skills we gather under the umbrella term “literacy” are neither firm nor fixed, neither intrinsic nor fundamental to human discourse.

This approach aligns nicely with the critical literacy approach forged by social justice-focused thinkers like Paulo Freire, Howard Zinn, Henry Giroux, Michael Apple, and others. Now, with an increased focus on a new category of literacy that DiSessa Mitchel Resnick, and others have labeled ‘computational literacy,’ we get to think of the social dimensions and equity issues linked to this new (enhanced?) set of social practices. We get to consider what it might mean to develop critical computational literacy.

And a visualization: Check out this page and this page for my take on a few key readings on computational literacy. And one more, here, that I feel is the best of the bunch.

And below, you can scan my very first custom gadget EVAR. Am I a programmer? Am I now? Now?

now?

Posted in culture, education, literacy, Paulo Freire | 2 Comments »

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 »

liveblogging the Home Inc Conference: keynote speaker Alan November

Posted by Jenna McWilliams on October 24, 2009

From Alan November’s website:

Alan November is an international leader in education technology. He began his career as an oceanography teacher and dorm counselor at an island reform school for boys in Boston Harbor. He has been director of an alternative high school, computer coordinator, technology consultant, and university lecturer. He has helped schools, governments and industry leaders improve the quality of education through technology.

His opener:
“I used to think I knew the truth. I don’t know it anymore. So whatever I say is only good enough to criticize.”

Here’s why, according to Alan November, we’ve been able to spend over $10 billion on putting technology into schools over the last decade without making any gains on learning. He pulls much of his arguments from Shoshana Zuboff’s 1989 book, The Age of the Smart Machine: The Future of Work and Power.


1. The real solution isn’t bolting technology on top of what we used to do.
November pointed to Zuboff’s notion of “automating,” which is the process of using technology to automatically transfer information. “When you automate,” November said, “at best, you only get incremental improvement. Not surprisingly to me, you often get a decline in quality.

According to November, connecting our classrooms to the Internet has lowered the quality of education int he U.S. Plagiarism has skyrocketed. “Everywhere I go,” he said, “teachers complain about how students are taking the easiest route to learning” through copying and pasting and other plagiaristic approaches.

2. The real issue isn’t technology; the real issue is control. We have teachers and administrators controlling learning and we need to ask how well (or poorly) that serves the needs of the learners.

Here are the solutions November offers:


Zuboff’s notion of informating:
Giving people access to information they’ve never had before. “I’ve been to schools that are technology-rich and information-poor. Teachers don’t have the right information at the right time to do the right job. Students don’t have the right information at the right time to do the right job. Parents do not have the right information–ever, hardly.”

Identify new opportunities for collaboration. This is, according to November, a mark that you’re beginning to use technology well.
“The one-room schoolhouse was a great idea. We need to go back to that. The very structure of the school system is what’s in the way. That structure is a control model.”

If you do those two things well, November argued, then more and more people become self directed. They don’t need an organization to tell them what to do. That’s the ultimate skill, according to November.

“One of the most important questions we need to ask is: Who should own the learning?” Since technology is typically used to reinforce teacher control, we need to think of new strategies for using technology to shift control over learning toward learners and, November argues, parents. He argued that the best thing schools can do is to “build capacity in every family as centers of learning.

“But I can say this until I’m blue. i don’t think anybody’s going to do this–because it falls outside of the boundaries of the current collaboration people have.”

Time? Money? Energy? “It’s all red herrings,” said November. “It’s all about control!”

November says the biggest technology from his perspective that can help lead to a shift in control is Skype.

my thoughts on November’s keynote:

It’s refreshing to see his energy and enthusiasm about rethinking the use of technology in the classroom. I worry, though, that his stance on transferring agency to the family could just shift the control issues from the schools to the family structure. In brief, it’s not just control that makes schools worrisome institutions; it’s the colonizing effect of middle class values on members of non-dominant classes and ethnicities. Collaborate with families and you get the same old divide we’ve been seeing for much more than the last decade. Middle class kids will get inculcated with middle class values, which we know lead to success; lower class kids will learn a different set of values, thereby reifying the divide between the haves and the have-nots.

Add to this the increasing influence of new media technologies–and the participation gap that Henry Jenkins has pointed to–and this concern becomes even more vital.

Control, after all, is much less simple (and simplistic) than we try to make it appear. Add to that the fact that institutional control has nuances that aren’t easy to talk about in the keynote structure.

“If you don’t have the right mission,” November said, “it doesn’t matter what technology you have.” Yes, and we need to consider the broader (if tacit and unexplored) mission of the American education system.

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