My friend Lisa Neal has started a blog. For those who don’t know her, Lisa is one of the editors at eLearn Magazine and is also a usability expert.
Category: Ed Tech
The “Ed Tech” category includes posts about educational technology products themselves, including LMSs and other learning platforms, adaptive learning and other digital curricular materials products, learning analytics, and educational apps of all types. It also includes technical aspects of ed tech products, especially interoperability.
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My Sakai Widget
Cambridge now has made a “My Sakai” widget available that provisions information on recent activities, resources, and announcements from a Sakai installation into a Facebook application or a widget in iGoogle, Google Desktop, a Mac OS X desktop, or a Windows Vista desktop. This is somewhat the inverse to the idea of making the LMS a container for gadgets that I posted about earlier. (Incidentally, there are some good comments from a couple of Sakai developers on that previous post.)
In an ideal world, you’d have both, i.e., you’d be able to project stuff from the rest of the world into an LMS via gadgets and project stuff out into the rest of the world from the LMS via gadgets.
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EduPatent Busted! (But not the one you're thinking of…)
This good news in from John Lewis:
A long-time target of the Electronic Frontier Foundation’s Patent Busting Project has finally been destroyed. Back in 1999, Test.com patented for-fee testing over the Internet and has since approached a number of publishers and universities seeking licensing fees. The patent was reexamined last year and now the PTO has officially rejected all of the claims in the patent as “obvious and non-patentable”. Online testing is finally safe for the public domain.
One down….
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Blackboard v Desire2Learn Trial Is Coming Up
Since our last posting, we received word that the judge has decided not to rule on any summary judgment motions – he’s letting all issues go to trial. As a result, Desire2Learn’s legal folks – inside and outside counsel – have been working overtime preparing for trial.
We’re going to trial on February 11, in Lufkin, Texas. We anticipate that the trial will last approximately two weeks – both sides have been restricted to 18 hours each to present their cases. We continue to be grateful for the support of others in the industry. Most of the issues will be tried before a jury; inequitable conduct is tried before the judge. At this point, we’re (obviously) careful about divulging our trial strategy – we’re sorry we can’t share more.
As much as ever, we’re confident of our defenses, including the defense of the patent’s invalidity and inequitable conduct, and the fact that we do not infringe.
Looking for a warm place to spend a couple of weeks in February? Consider an early-spring trip to Lufkin!
If anybody is planning to go to the trial, please let me know.
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The Perils of Prediction
As we watch the spectacle of the jackasses in the mainstream media blithely continue to pretend to know what they’re talking about after being repeatedly and stunning wrong in the predictions of the U.S. Presidential primary, it’s worthwhile to look in the mirror. Stephen Downes has a good report card up for those of us who had the audacity to make predictions in last year’s eLearn Magazine‘s annual crystal ball reading. After giving each of us (including himself) a grade, he muses:
So that’s it. What did I learn from all this?
First, that there are two major types of predictions: one, which identifies a current trend, and says it will continue; and the other, that identifies something novel or unexpected. It seems clear that the former predictions are easy and safe and not especially useful. The latter, while not as safe, were much more useful to people.
There are also different types of predictions. Some predictions speak to attitudes. Others speak to trends (including a subset of these that suggest a trend will go mainstream). And still, others speak of technological or system-wide advances. And finally, the most useful predictions identify side-effects – the result of some unexpected event and development. For example: predicting people will want video is one thing, predicting that it will become popular is another, predicting that Flash video will help video become accessible is another, but predicting YouTube is most useful of all.
And third, scale is a tricky issue. There were many predictions that will probably come true – some day. But they did not come true in 2007. We want to reward such predictions, because we feel they are accurate, but unless it happens, it’s just another false prediction. Another trend was a slew (the perpetrators won’t be named) who correctly predicted last year’s event or trend.
Good points all. I try make predictions about areas where I have some personal knowledge of events that maybe not everybody has and to be as aggressive in my predictions as I feel that I realistically can, but I do tend to err on the side of caution. Sadly, I don’t think I’m nearly smart enough to predict something like YouTube so I generally don’t try to shoot the moon, so to speak. I think it’s good to know one’s own limitations.
