It's been 200 years since Pride and Prejudice was first published, and I can't let it go by without comment. I freely admit to being a huge Austen fan; she's one fantastic novelist, and Persuasion is my all-time favorite novel.
Years ago, when I'd worked through all of Austen, I decided to try reading some of the works that inspired her. This wasn't a very scientific endeavor (I started with books that are referenced in Northanger Abbey), but it was very interesting. The BBC recently posted a list of some of the novels that were popular at the time Austen was writing. Looking back I can see that I actually read a fair number of the listed works.
If all you ever read from the turn of the 19th century is Austen, you end up with a very different picture of that world than if you read more broadly. I can't say that any of the other authors have the gift of writing novels the way Austen does, but they certainly portray a wilder world. Burney, Edgeworth, and Lennox are packed with duels, cross-dressing, kidnapping, suicide, and monkey attacks. Yes, monkey attacks. And that list doesn't even include The Monk!
While Austen's work is truly wonderful, it can feel a bit sanitized. The gothic novels and picaresques of the 18th century certainly aren't any more realistic than Austen's work, but when all are read together it's easier to remember that the world wasn't actually a simpler, safer place back then. It just had less plumbing and a more complicated syntax.
Monday, January 28, 2013
Thursday, January 24, 2013
First Week in a MOOC
I just finished the first set of lectures and quiz in my attempt at taking a MOOC (massive open online course). So far, so good.
We'll see how I feel at the end of this experience, but at present it feels more like independent learning than a class. This is partly due to my own decision to have limited involvement in the discussion forums. I barely have time to devote to the 3-5 hours of required work each week, and online forums can be a complete time suck. So, yes, I'm mostly avoiding them.
I'm taking Data Analysis via Coursera, which is organized as a series of short lectures each week followed by a quiz. The short lectures make it possible to stretch them over the course of several days, which is very useful since I spend every lecture frequently pausing so I can take notes and go over the content of the slide a second time. The quizzes are more like complicated homework assignments than quizzes. They are not just "open book," but actually require that you go outside the course to find information that then is used to answer the question. It's not a traditional format for a quiz, but it does fit one of the points of this course: this course won't teach you everything, and you will need to learn how find answers to your data analysis questions.
Along those lines, one of the first lectures was 10 minutes on how to ask a question. As a reference librarian, this lecture really struck a chord. There may not be any stupid questions, but there sure are a lot of questions that are worded so poorly that no one has any hope of answering them. A colleague once referred to these as "word salad" questions, and that's what a lot of them look like. My favorite slide in the lecture showed "bad" questions, which in his mind included the word "HELP" and lots of exclamation points, but not much else. I have certainly seen my share of those. There are times that I wish everyone had to take an entire course in high school about asking questions. I'm sure that many doctors, mechanics, and other professionals working with specialized knowledge wish that as well.
It feels good to have successfully completed my first quiz. I'm still not sure that I'll survive this whole course, though. It requires learning how to use the R statistical package, with all of its programming codes, along with the course content. (Thanks Code School for getting me started with R!) I've also never taken a probability or statistics course, so there's a ton of new content here. Let's hope I've picked up enough knowledge as an academic librarian to quickly fit everything together into a coherent whole. I've got seven more weeks to figure it all out.
We'll see how I feel at the end of this experience, but at present it feels more like independent learning than a class. This is partly due to my own decision to have limited involvement in the discussion forums. I barely have time to devote to the 3-5 hours of required work each week, and online forums can be a complete time suck. So, yes, I'm mostly avoiding them.
I'm taking Data Analysis via Coursera, which is organized as a series of short lectures each week followed by a quiz. The short lectures make it possible to stretch them over the course of several days, which is very useful since I spend every lecture frequently pausing so I can take notes and go over the content of the slide a second time. The quizzes are more like complicated homework assignments than quizzes. They are not just "open book," but actually require that you go outside the course to find information that then is used to answer the question. It's not a traditional format for a quiz, but it does fit one of the points of this course: this course won't teach you everything, and you will need to learn how find answers to your data analysis questions.
Along those lines, one of the first lectures was 10 minutes on how to ask a question. As a reference librarian, this lecture really struck a chord. There may not be any stupid questions, but there sure are a lot of questions that are worded so poorly that no one has any hope of answering them. A colleague once referred to these as "word salad" questions, and that's what a lot of them look like. My favorite slide in the lecture showed "bad" questions, which in his mind included the word "HELP" and lots of exclamation points, but not much else. I have certainly seen my share of those. There are times that I wish everyone had to take an entire course in high school about asking questions. I'm sure that many doctors, mechanics, and other professionals working with specialized knowledge wish that as well.
It feels good to have successfully completed my first quiz. I'm still not sure that I'll survive this whole course, though. It requires learning how to use the R statistical package, with all of its programming codes, along with the course content. (Thanks Code School for getting me started with R!) I've also never taken a probability or statistics course, so there's a ton of new content here. Let's hope I've picked up enough knowledge as an academic librarian to quickly fit everything together into a coherent whole. I've got seven more weeks to figure it all out.
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