I really shouldn’t share these tricks since they are secret weapons for massive research productivity (SWMRP), but I hope some of you will share your own research productivity tricks also, so that academic bloggers will quickly dominate the research world.

• Use Firefox! If you do, you can add citeseer, google scholar and wikipedia to your quick search bar. When (academic) research becomes intensive, make google scholar or citeseer your default Firefox search engine! If you do this, your research productivity will jump. I hope you will then give me credit in all future papers you write! I could use the fame.
• (From Suresh) You can use citeulike to collect references for papers, and export the result to bibtex at the end. Don’t forget to add the bookmarklet to your bookmarks for extra convenience. I have my own citeulike library though I haven’t used it for collecting references for a paper, so far.
• Similarly, for tracking random web sites, del.icio.us is a must. Don’t forget to install the Firefox plugin for extra convenience.
• A little known fact is that Google Scholar can be configured (see “preferences”) to export search results to bibtex. Again, this is the sort of thing that can make your productivity jump so that you’ll be tempted to start all your papers by “Daniel Lemire made this paper possible…” Ok, maybe not, but close.
• Subscribe to lots and lots of mailing lists and newsletters, but instead of reading them all, just have your mail client flag those whose text contain keywords you are interested in. This is especially powerful to monitor interesting call for papers.

Disclaimer: if you use these tricks, you ought to be able to easily write 15 papers a year. Ah! But why don’t I write so many papers? Because I’ve got bad habits such as constantly changing my field of research, thinking for a very long time about non-paperable ideas or writing code, sometimes pointless code, for months at a time, just because I like playing with live algorithms. Also, I’m a little bit dumb and ignorant.

Thomas Easton promotes algorithms as a higher form of science in his paper Beyond the algorithmization of the sciences:

Algorithms have thus made biology as useful a science as physics, chemistry, and computer science. But are algorithms enough to move biology closer to the throne? Are they math?
(…)
Five decades ago, most mathematicians would have said no. Then in the 1970s, they discovered the value of computers for “proving” theorems (…)

Myself, I haven’t had time to spend much time thinking about it, but it is quite clear that I value algorithms at least as highly as I value theorems.

There might be hope for Java after all. Google just published is AJAX-based web toolkit in Java. Cross-browser compatibility is a major pain with AJAX, but this toolkit solves it all. Or so says Google.

Michael Feldstein, Assistant Director, SUNY Learning Network, says that there is no such thing as a learning object.

We learn by doing. We consider. We compare. We measure, discuss, debate, critique, test, and explore. We try, fail, and try again. Learning is an activity. It’s a process. Given this undeniable fact, the term “learning object” can only be an oxymoron. An object is a thing. We don’t learn from things. We learn from doing things.
(…)
I believe the term “learning object” has become harmful. It hides the same old, bad lecture model behind a sexy buzz phrase.

David Wiley said that learning objects are a bad idea. Albert Ip points out that standards in eLearning technology bring no visible benefit. Now, Harold Jarche adds his two cents to this “debate” (if “debate” there is):

In a recent project where I reviewed the business case for SCORM implementation, I found no evidence of a market for digital learning objects. There were several vendors offering SCORM conversion or SCORM implementation assistance, but no one was actually buying and selling objects. The bet seems to be that standards will create the market, as shipping containers enabled the free flow of goods over various forms of transportation. Here I disagree, because learning cannot be “containerised”.
In theory, reusable digital learning objects make sense, but in practice they don’t work. The problem is that learning objects cannot be separated from their context.

In the drive to make money in the learning business, too many people are trying to find a way to codify pieces of the messy, personal process known as learning. The learning content market is based on the premise that these pieces can be quantified and therefore owned by someone.

JabRef reference manager is a Java-based tool to manage your BibTeX references. “JabRef runs on the Java VM (version 1.4.2 or greater), and should work equally well on Windows, Linux and Mac OS X.”

(Thanks to Harold Boley for pointing it out.)

A pretty exciting article in the New York Times about what is “talent”. The short story is that you should practice hard while ensuring you have immediate feedback and have clearly defined goals.

when it comes to choosing a life path, you should do what you love — because if you don’t love it, you are unlikely to work hard enough to get very good. (…) what they really lack is the desire to be good and to undertake the deliberate practice that would make them better.

(..) there is surprisingly little hard evidence that anyone could attain any kind of exceptional performance without spending a lot of time perfecting it.

(…) Students should be taught to follow their interests earlier in their schooling, the better to build up their skills and acquire meaningful feedback. (…)

(…) two key elements of deliberate practice: immediate feedback and specific goal-setting.

(Got it from Unreasonable.)