Enter, OpenStreetMap. Seeded with the geographical data made publicly available by various governments and public universities, OpenStreetMap provides Free (as in freedom, licensed under CC-BY-SA) map data to anyone who wants it. The data is usually in pretty good shape because the initial measurements are in good shape. However, things aren’t perfect. Lucky for the web, OpenStreetMap.org allows users to help improve the data in a number of ways.

First, users can upload GPS traces to help improve the quality of unmapped regions such as seriously-rural areas along with bike and hiking trails. Second, users are able to tweak the mapping data to correct errors. There are a number of ways to do this but OpenStreetMap.org has an online editor which lets you overlay OSM data onto sattelite imagery so you can move those roads, landmarks and the like into the right location. In about an hour, I had cleaned up much of my hometown and began to add local landmarks, parks and buildings. It’s quite easy.

The project itself seems off to a great start and the planet shows a fair bit of activity. In particular, I like the idea of mapping parties where people get together and work on a given area. This seems like a great way to give back to the community and I plan to float the idea at the next SCOSUG meeting.

Wrong! Any good educator knows that test scores (especially from a single test) are not the only way to gain additional insight. While the strengths and weaknesses of the standardized-testing model are a different discussion entirely, suffice it to say that the community needs to remember that, when it comes to education, all numbers are fuzzy. The learning process is not discrete, definite or clean-cut so why should we expect a signle number to show singular accuracy with any great fidelity? In fact, we cannot and it is for this reason that an automatic evaluation of textual data might help educators make better decisions. Perhaps an example is in order.

Let us say that every so often in a math class, teachers write a brief one-paragraph essay about each student summing up their competency and general performance. Then let us also say that students are able to write a sefl-evaluation each time their teacher writes something. So after, a period of time, each student has a bit of text in addition to their test scores and general grades. I propose using some sort of automated classification mechanism to evaluate the textual data and produce best guesses as to the nature of the content. Afterall, if there are 25 students in a class and there are 10 classes taught each day, then that’s a lot of evaluation data to be read! So what about using something like a naive bayesian classifier to sort through things?

But wait, doesn’t this just give us another mechanism to boil down the real-world intuition of the educational system? Well, no. If we let go of the idea that these numbers are perfectly discrete (which we know they aren’t), then we can use them to inform our descisions rather than letting the data decide for us. Probabilities are ok so long as we use them correctly. Few people would wear shorts in the winter just because the weatherman said there’s a chance of sun. So how might such a system be used?

Well, the point of a naive classifier is that it needs to be trained. First, teachers would need to assmble a training data set of some sort. In younger grades, this might be quite easy because students have a more limited vocabulary and might not construct sentences with as much nuance as they learn to do in later grades. As for teacher evaluations, there is a somewhat-finite set of words in the vocabulary of an educator to usefully describe educational progress. Relying on the consistency of such a set nomeclature might very well yield consistent results. Though, all of this would need to be tested anyway, right? This is just a thought experiment…

So the system would be able to chew through these evaluations and produce a guess about whether they reflect positively on student learning or not. Perhaps they could even be used to demonstrate growth. Getting this right would take work but it might lead to a useful way to model evaluative-data. Obviously, relying too much on this might very well to a negation in the positive nature of narrative evaluations but it’s worth a try!

First and foremost, I enjoy the LKML Summary podcast put out by Jon Masters. He does an exceptional job of summarizing things and his side commentary is usually rather hilarious, actually.  I do wish he’d provide a touch more background on certain things as it can be hard to jump right into the high-level technical discussion on the mailing list. Masters’ radio-compatible voice is a pleasure to listen to in the car, even if each episode is only just under nine minutes long.

Next, I have Software Engineering Radio, which has some really neat discussions. The latest one is on APIs and then I’m going to listen to the one where they interview Odersky. The commentary on topics is quite lucid and I greatly appreciate the candor of guests when discussing specific issues. After all is said and done, the software community at large can be a political group (myself included) so it’s nice to have some really great technical discussions as well.

So far, that’s it. I want to also sample the OSNews podcast but haven’t gotten around to it yet. So with about 2 hours in the car every day, anyone know of anything else I should be listening to now that LugRadio is over? I’d be interested in some podcasts on the topics of emacs, Debian or Scala stuff.

The entire piece left me feeling really intrigued by the challenges of effectively integrating technology and education. The paper is very well researched and although I can’t articulate it,  I reached the last page of this paper feeling really good. Maybe it had to do with the enlightened view taken by the authors. Their writing is crisp and their outlook seems appropriately upbeat given the richness of the material and subject matter covered in the paper. The document bursts with elegant and thought-provoking stanzas:

Design based research is a methodology for the study of function. Often referred to as design research or design experiments, it is concerned with the design of learning processes, taking account of the involved complexities, multiple levels and contexts of educational settings. The primary aim is to develop domain-specific theories in order to understand the learning process.

Such succulent gems of insight are plentiful in the opening sections as Mor and Winters set the stage for a comprehensive reflection on the essences of design, science and learning. They are realistic about how “The complexity of classroom situations does not lend itself to the procedures of laboratory research” as they ask “To what extent are we driven by a pure quest for knowledge, and to what extent are we committed to influencing educational practice?”.

The paper continues into a very stimulating overview of design patterns and their application in the many areas of education. Though I have always liked the idea of design patterns in software, I have never been so enthralled by a discussion about the essential elements of design patterns. Also, this is the first time that I’ve heard of design patterns being used as a tool for analysis instead of construction and planning:

An important characteristic of a design pattern is that it has three facets: descriptive, normative, and collaborative. It is an analytic form, used to describe design situations and solutions, a meta-design tool, used to highlight key issues and dictate a valuable method of resolving them, and a communicative tool enabling different communities to discuss design issues and solutions.

The esteemed writers are careful to explain their thought processes without letting their comprehensive coverage become tangential. They expertly work in a mentioning of the political agendas of design pattern construction for city planning and network routing protocols to help illustrate their observations of how values influence design.

This paper is awash in fascinating pointers to further exploration and while I fully intend to follow up on some of their citations, something of immediate interest is a link to a very cool site called the Pedagogical Patterns Project which established a repository of educational design patterns. I need more time to explore but what they have seems to be very cool. It’s clear that I’ll refer back to this paper frequently as I strive to better understand the interactions of education and computing.

Mohan begins with a very logical stance on the dual subjects of technology and education by saying that “Some of the most cost effective and appropriate ways to use computers and modern technologies is to have close contact between the teachers and the taught.”. When I read this and the text before it, I wondered if all I would get would be a concise exposition detailing those business issues in India which dealt with college students. Instead, I got a whirlwind overview of select “reskilling” efforts thought (by Mohan) to be significant in the scope of the paper.

The paper is written in a casual-yet-technical style with a tone and focus that instantly reminded me of Thomas Friedman‘s many commentaries on the Indian tech sector. In fact, some of his more entertaining points might just be a tongue-in-cheek salute to the importance of education in a culture commonly associated with outsourcing:

A mixed approach to valuing staff by developing skills, providing interesting and motivating work while recognizing their individual contribution, alongside benefits and perks, will mean that you are an employer that employees don’t want to leave.

If this paper were any longer than it is, I would advise people to move along and skip it in favor of more detailed works. That being said, the topic was narrowed significantly and as such, could be considered to have an reasonably-appropriate length in addition to it’s generally generally-upbeat discourse. In fact, I actually found myself giggling at some of Mohan’s informalities and clear showings of enthusiasm.

Perhaps the most interesting aspect of this paper is it’s writing style. These authors have clearly given the subject a great deal of thought and have not been shy about getting philosophical while expressing their opinions. In fact, these authors have gone out of their way to use their variety of interdisciplinary sources to help illustrate the idea that issues in computer-based learning are never purely technical. One of the first communication models they discuss is the well known psychology concept of the double bind. While the concept isn’t worth explaining here (given the ubiquity of detailed explanations), their relation of the concept to educational evaluation is certainly significant.

Evaluation is also trapped in the double bind. Student and teacher or even the other characters such as colleagues and parents exchange many contradictory stimuli about learning. For example: have critical sense versus accept as truth what is in books, express yourself efficiently versus do not talk, concentrate on homework versus play with friends, etc. These situations are inherent to evaluation in the same sense the double bind is part of communication

The tensions described here are all-too-familiar to students, both past and present. Issues such as the ones mentioned in the paper are very real obstacles that must be overcome in classrooms all over while their complexities are only emphasized further by the still-developing experience of computer-based learning.

…the computer-based learning environment must support and, if possible, amplify the expression and the emergence of contradictory relations. These are essential to the evaluation process, since provocative statements may communicate how teacher and colleagues perceive one’s performance and understanding.

With this in mind, they conclude their discussion by explicitly stating the importance of letting real-world factors influence the design of learning systems. This exceptionally well thought-out piece of technical writing should be required reading for any educator considering the deployment of a computer-based learning system or struggling with the design of an alternative assessment mechanism.

After a brief overview of the proprietary software model, Hepburn devotes a solid page examining the issues surrounding using proprietary software in schools. He cites the cost of doing business with Microsoft (according to the Microsoft School Agreement), as of Winter 2005 with a school of 400 machines, to be US$7200 for the OS alone and US$19,200 for a complete desktop package. Additionally, he notes that, in general, “…using proprietary software requires a high degree of accountability” on account of license compliance issues and other legal liabilities. Alongside the financial downsides, Hepburn makes a very good point when examining “…school’s complicity in exposing students to commercial products and corporate interests”. The idea of a classroom as a corporate marketing machine is rather unappealing.

While it’s not hard to find literature extolling the virtues of F/OSS, Hepburn does a nice job of emphasizing the potential benefits for schools. One particular point that caught my eye was his comment that “Schools can also burn OSS on to a compact disc and give it to staff or students to take home and do what they wish with it”. Granted, projects like OpenDisc have been leveraging the flexibility of F/OSS licenses for some time now, but I have been toying with the idea of using virtual machines as distributable workspaces. Personally, I find the idea of being able to send a student home with their own system saved on a thumb drive very compelling.

After touching briefly on the subject of Linux, Hepburn goes on to discuss some of the neater software packages from the F/OSS world. In particular, OpenOffice.org gets a shout out though I don’t know if I agree with his insinuation that OO.org requires fewer system resources (specifically hardware) than MS Office. Overall, I do agree with his other major points which support the ideas that the F/OSS community is better equipped to respond to change and correct errors. Moreover, I fully support the idea that more diverse exposure to different types of software will lead to an overall greater computing literacy.

With a healthy sprinkling of Lawrence Lessig quotes and shameless support for F/OSS, this paper is definitely worth a read.

1. vditool COPYDD vbox-image.vdi raw-image.img
2. qemu-img convert -f raw raw-image.img -O qcow2 qemu-image.qcow

The first step copies the contents of the image (*.vdi is the VirtualBox filesystem image extension) to a raw disk image. Be advised: this file will be the full size of the virtual hard drive. That means that, unlike *.vdi and *.qcow formats, if the virtual disk has a maximum capacity of 8Gb, the raw image will be 8Gb in size regardless of how full the disk is.

Once you have the raw image, run the second step which uses the QEMU disk image manipulation tool, qemu-img, to convert the raw image into the QCOW2 format. The new QEMU image will be much smaller than the raw image was and it can be made smaller by passing qemu-img the -c option to enable transparent compression. However, seeing as how this just uses zlib on each cluster, this might introduce more overhead to I/O than is desired and will most likely degrade your overall VM performance.

UPDATE: 2010-05-14

It looks like vditool is no longer available. It also seems like you could use the VBoxManage tool included with VirtualBox to do the conversion but that option has also been removed. The good news is that qemu-img now has support for *.vdi files and can be used directly.

1. Finish my thesis proposal. It’s cool and I promise to post the completed copy)
2. Complete work on my final exam. I have the permission simulator written and it can actually store data. I still need to write test cases and debug the thing though. Additionally, once I have it working, it might be worth seeing how much of it I can refactor and tighten up. Like anyone, my code isn’t always great but it should at least be written well.
3. Clean up and finish the draft for the current tech report I am working on. Two tech reports in one academic quarter seems like a pretty good pace.
4. Cook for Shabbos dinner at the home of my beloved, revered and venerated faculty. Her clutch of dedicated students are planning a large dish involving many sautéed vegetables and rice. Perhaps I’ll post our methodologies if it turns out well.
5. Pack to go home on. I fly home early on Tuesday, 2007-12-11 so I need to have certain items like clothes, my tefillin, chargers for my various media devices, personal grooming equipment (razor, etc), books and assorted other required equipment.