What I Learned Today

I’ve been experimenting with some of the new massively multiplayer online course offerings from Coursera. In the spring, I took Cryptography, and I am now taking Fantasy and Science Fiction: The Human Mind, Our Modern World. These courses are offered for free, for anyone who wants to take them. I’ve been curious about the (eventual) business model, since there will have to be some way to recoup the investment in web site architecture and content. The lectures do seem to be “record once, replay forever”, but it’s still a big effort to do up front.

One way they’ve kept the ongoing costs reasonable, though, is by offloading one of the biggest time consumers in traditional education: grading. The Cryptography course was conducted in an entirely auto-grading mode. The homeworks each week were a series of multiple-choice or fill-in-the-blank questions. The feedback was actually quite good from these exercises — if you got something wrong, there might be a clue as to where to look, and if you got it right, there was usually an explanation, which you could learn from if you’d just gotten lucky with your choice. Further, you could attempt each homework 4 times, a process designed to encourage “mastery” (progressive learning). I know what you’re thinking. Four tries on a multiple-choice test should basically ensure you get 100%, since you could explore all possible options. Not so! They’ve made the process more sophisticated, producing a new mixture of answers for each question each time you attempt it. You really do have to think through the problems each time. I approve.

The F&SF class is different. Our assignments consist of 300-word essays, which can’t be auto-graded (with any real reliability). First I must note that I found WRITING a 300-word essay to be particularly challenging. How can you say anything of substance in 300 words? How can you call out something of interest in a 400-page book using only 300 words? But, as in haiku, the limitations of the medium are themselves a spur to inspiration. So then, how to grade them? Coursera has adopted a peer grading strategy, in which you are assigned to grade a random set of your classmates’ essays, and your essay correspondingly is sent to a random set of peers to be graded. In this class, we’re required to grade four peers, but allowed to grade more. The grading itself is very coarse: you assign one score for Form (grammar, organization, etc.) and one for Content. Each can be given a score of 1 (poor), 2 (average), or 3 (exceptional). You are also required to provide some text feedback.

So far, I found the grades I received from my peers to be fair, but I don’t think I’ve learned much from them. Most of the feedback was compliments, with a few rather surface-level critiques, rather than the kind of feedback you’d get from a professor or TA. But one reason for this is the bizarre organization of this particular class. You are required to do the reading, write an essay blind (on no suggested topic, simply something that “will enrich the reading of an intelligent, attentive fellow student”), and only THEN are you permitted to view the professor’s videos with his analysis of the readings. Perhaps this is intended to reduce “bias” from the instructor, but ultimately all it does is set you up to be evaluated tabula rasa (with respect to the course content), so I don’t see how the assessment has anything to do with what you have learned. These should be pre-tests rather than the sum of the grade. With the current scheme, the lectures themselves unfortunately become less of a priority, because by the time they’re available, you should already be moving on to read and plan an essay on the next reading. That’s a shame, because Dr. Rabkin is clearly a thoughtful and knowledgeable source. I’ve found most of his lectures to be interesting and thought-provoking (even though I disagree violently with some of his analysis of Grimm’s Fairy Tales! Ugh!). So, two weeks in, I’m not very enamored of this kind of peer grading. I hope Coursera continues to experiment with new strategies.

You can check out Coursera’s statement of pedagogy in which they explain their design choices and include references to some external work on their efficacy. It’s mostly reasonable arguments. I’m on board with the mastery learning comment, for example. However, I found the argument for peer grading to be weaker. The main motivation (never articulated) has got to be the challenge of providing feedback for thousands (or hundreds of thousands) of students, which is a scaling issue. Instead they cite research on the benefits of peer review, which are valid, but I think never intended to be the SOLE source of feedback for students, and the strengths of crowd-sourcing, which depends on large numbers for reliability, which four random grades from others in the class don’t provide. I’m not asserting that this is an invalid method of instruction, but I’m not convinced by the evidence they’ve offered.

In working through these courses, I’ve already gotten ideas for how I would experiment creatively with this new teaching medium. Watching slides is boring. Watching a talking head is boring. I love, however, the occasional pauses that require you to answer a question (pop quiz!) to proceed. It’s great for capturing attention that may have been wandering. The Cryptography class made good use of these. The F&SF class doesn’t use them at all. If I were teaching, I’d also bring in props or direct students to relevant websites or otherwise increase the level of activity and interactivity as much as possible. Right now, the only interaction in the F&SF course is through the essays (anonymized) and the discussion forums (which no one can keep up with). I’d like to foster more interaction with the professor, without inundating that person. I think well crafted video lectures can improve on this front.

Distance learning has great potential to reach a wide array of students, or just to cut down on commuting. Four years ago, I took a class on remote sensing through USC’s Distance Education Network as part of my Master’s degree work in geology. While I was delighted to not have to drive down into L.A. that semester, and I enjoyed being able to eat dinner or knit while viewing the lectures, I did feel that the experience lacked something — real-time engagement with the professor and other students.

But technology and pedagogy have been adapting and improving over time. I recently watched a recording of an open house for the San Jose State University’s School of Library and Information Science. Their entire program is offered through distance learning, even for local students; there are no physical classrooms. As a result, if the Open House is any sample, the professors have developed excellent ways to conduct an online class meeting that involves and engages students beyond passively listening to a lecture. Contrary to my initial reservations, I came away impressed by the use of technology and the clear commitment to a quality experience. There were interactive quizzes, discussion of the results, and a live chat window. I think I was most impressed by the presenter’s comfort with the online environment; she noticed and responded to every comment made in the chat window, seamlessly blending those topics into the flow of her presentation.

SJSU’s program involves ~2500 students (again, all online), with a 25-30 student enrollment limit in each class (interesting given that it’s offered online!). The required introductory course has a peer mentoring component. Students have the option of getting course credit for in-person internships with their local libraries. At the culmination of the degree, students can choose to assemble an ePortfolio demonstrating 15 core competencies or a research thesis. Recent theses cover a fascinating range of topics, including:

• The impact of Hurricane Katrina on Gulf Coast libraries and their disaster planning
• Historical archaeologists’ utilization of archives: an exploratory study
• The rise of Mormon cultural history and the changing status of the archive
• Libraries in American German prisoner of war camps during World War II

The course offerings broadly address issues of how to organize, catalog, access, and share information. There are classes on how “interview” patrons (to zero in on what they’re really looking for), the library’s role in intellectual freedom, archives and preservation, and the history of books and libraries.

I noticed a few interesting differences in word use from what I’m used to. “Research”, in the library context, refers to the process of looking up a desired piece of information, rather than developing new algorithms and conducting experiments. “Implementation” means to install or put something in place, not to write code.

Here stands revealed another world of new ideas and information to learn. And with distance learning, it’s made super easy! Hmm…

Every since I discovered The Teaching Company’s excellent lecture courses, I’ve been a fan. Apparently, Orson Scott Card is too. He wrote an article about how great the Great Courses are (scroll down about 3/4 of the way). I know just what he means when he writes:

“Why am I going on about these courses? Because I believe education should never end. I don’t think education is something you “get,” and degrees don’t impress me. […] the truth is I read constantly, and take these course[s], for love. It bothers me when there are things I don’t know or don’t quite understand. I hate it that I only speak a couple of languages. There just hasn’t been time to learn all that I’ve wanted to in my life.”

He recommends the following Great Courses professors:

• Brian Fagan: human prehistory
• Elizabeth Vandiver: Herodotus’ history
• Jennifer Paxton: medieval English history
• Kenneth R. Bartlett: history of Renaissance Italy
• Louis Markos: writings of C.S. Lewis
• Marshall C. Eakin; discovery and conquest of the Americas
• Peter Rodriguez: economics
• Philip Daileader’s three courses on early, “high” and late Medieval Europe
• Robert L. Dise Jr.: ancient empires before Alexander the Great
• Scott McEachern: origin of civilization: “begins badly – start with lecture 3”
• John McWhorter: intro to linguistics: “best teacher I’ve encountered in the Great Courses so far”

… none of whom I’ve yet sampled. My own current favorite is Prof. Rufus Fears, who created the excellent “Books That Have Made History: Books That Can Change your Life” course (currently discounted). I’m not sure I always agree with his conclusions, but the aim of a great course should be to inspire you to think on your own, not just adopt every opinion and interpretation professed by the instructor. Dr. Fears is always entertaining — sometimes a bit excessively so, as when his lectures become more of a dramatic reading or interpretation of the book under study than an analysis of the great ideas and themes it contains. I am eagerly working my way through this course and hope to learn more from him in the future.

Given Card’s recommendation, I may also be trying Prof. McWhorter as well! I’ve always been interested in linguistics, but have never taken an official course on the subject. A “Teach Yourself Linguistics” book is on my to-read list. Maybe McWhorter’s course will be the impetus for finally making that happen. As Card notes, the best strategy is to wait until the course you’re interested in goes on sale — their sales are phenomenal. Meanwhile, I also have “Building Great Sentences: Exploring the Writer’s Craft”, “The English Novel”, and “Stress and Your Body” to enjoy and learn from. Here’s to an educational sabbatical!

From the What I Learned Yesterday files…

I have always loved numbers, especially in terms of manipulating them. Remember those arithmetic drill books, endless columns of 3 + 6 and 12 – 5 and every other possible combination? I loved paging my way through them, filling up all of the blank spots. My grandmother’s living room had a big bay window with a flat base I could crawl onto (I don’t think it was intended as a seat), behind the curtains, and I loved to hole up there with that book. Even *better* was when I encountered those drills in elementary school, and they were *timed*! Hooray, a race!

But even before those memories glows a beautiful eureka moment I hope I’ll never forget. I was in daycare, somewhere between 4 and 5 years old, musing about multiplication (for no reason I can recall), when suddenly I Got It. I jumped up and ran around trying to share the shining vision that I’d had. The best I could do then was, “But it’s so simple! Two times two is just 2, two times!”

I still remember those words, and I remember the lack of a similarly excited response from the other kids. Was it incomprehension? Disinterest? I couldn’t seem to put my revelation into words that made sense to anyone else, and I was buzzing with commingled frustration and joy. At that moment, the “x” sign had ceased being an arbitrary symbol specifying a relation to be memorized. Instead, it had *meaning*. I was swimming in triumph at the feeling of having *cracked the code*, seeing yet another pattern but also the whys behind the pattern. (Of course, when I reached elementary school, I then got to memorize the multiplication tables, like everyone else. So much for eureka…)

I have a handful of other memories from that daycare. Conspiring with a friend to stash our pears from lunch, which we hated, in our pockets for later disposal. Sprawling on threadbare green carpet in front of the TV and goggling at afternoon cartoons. Singing “This Old Man, he played one, he played knick-knack on his thumb…” Discovering awe and predation on finding a black widow spider out back. Discovering how surprisingly hard other kids can pinch if you don’t wear green on St. Patrick’s Day. Shivering at horror stories about loose baby teeth being tied to a door and extracted with a slam, then rushing to the bathroom to inspect my own teeth for any worrisome looseness. But these have all faded in a way that my “2, two times” moment has not. And it left me with an appetite for that feeling of “Oh wow, I get it!” that is what makes the study of anything new so very delicious. More learndorphins, anyone?

An xkcd comic led me to the Simple English Wikipedia. This wikipedia aims to provide simplified versions of articles from the Ordinary English Wikipedia by limiting the vocabulary used, grammar complexity, and sentence length. I admire the motivation behind this resource: to make general knowledge accessible to non-native speakers, youthful readers, or those with disabilities. Yet to an adult native English speaker, the language of these articles can be gratingly unaesthetic (and imprecise). For example, consider this excerpt from the page on Mars:

The planet Mars is made of rock. The ground there is red because of iron oxide (rust) in the rocks and dust. The planet has a small carbon dioxide atmosphere. The temperatures on Mars are colder than on Earth, because it is farther away from the Sun. There is some ice at the north and south poles of Mars, and also frozen carbon dioxide.

This is all factually accurate, but achingly simplistic (especially the “because it is farther away from the Sun” statement — the atmospheric composition is also a critical player). On the other hand, if I had to read wikipedia in, say, French, I would no doubt appreciate the simplicity!

But I experienced even more wincing when reading pages about topics from Computer Science, such as the neural network page, half of which consists of:

What is important in the idea of neural networks is that they are able to learn by themselves, an ability which makes them remarkably distinctive in comparison to normal computers, which cannot do anything for which they are not programmed.

(Technically, they don’t learn by themselves — they require supervision in the form of labeled examples — and any machine learning method exhibits the learning property, not just neural networks, and what is a “normal computer” anyway? A neural network is an algorithm for learning a model, not a special-purpose computer. Finally, even neural networks cannot do anything for which they are not programmed! More accurate: “Neural networks can learn from examples, allowing them to make predictions about objects they may never have seen before (generalize).”)

Or consider this part of the page on Computer Science itself:

A computer is a device which takes orders as fast as you can give them to it and works as fast as it can to solve the orders.

(makes a computer sound like an active agent (e.g., waiter), which it isn’t) or from Computer programming:

The instructions in “machine form” are usually in a .EXE file (which is called an executable, because it can be executed). These machine-instructions will by default open a black “command-prompt” window, but can open games as well as other things.

(Well, am I really surprised that “simple” computer programming has such a strong Windows bias? ;) )

There’s an interesting issue at the heart of this project: how do you talk simply without talking down? (Or worse, misleading the reader!) Clear, simple language has real value even outside of this venue. However, translating all value judgments into the simple words “good” or “bad” not only gives the text a childlike sound but also gives its meaning a childlike interpretation, and important distinctions may be lost.

I actually find this wikipedia harder to read, not easier; the stilted sequences of simple sentences dominate my attention with their awkward rhythms and unanticipated gaps (likewise, you may have found my alliteration distracting :) ). Good writing blends its details in to the background and leaves you room to think about the ideas being presented. But yes, I know: I’m not the target audience for this product. I expect that many people are benefiting from much of the information in the Simple English Wikipedia. Hopefully they also get a chance to dig deeper for the real details on their subjects of most interest or need.