It’s been a while, and I’ve put zero effort into learning stats via OER since my last post. This is really a result of too many work projects, conference season, and my kids staying up later with the arrival of longer summer days.  In other words, typical constraints that the average self-directed adult learner faces in trying to fit any lifelong learning project into their life.  However, some of the projects on my plate for September are going to require a more than introductory understanding of quantitative methods, so the extrinsic motivation factor might actually start kicking in.

Recently I came across a new resource that I think will be fabulous in my continued effort to learn basic stats for research purposes.  Being the research methodology junkie that I am, I began following Methodspace on Twitter, which lead me to this resource.  I’ve signed up for the LEMMA course, and it seems to have everything I’m going to need, including the pretest and quizzes that I was looking for. Plus it’s specifically targeted for a researcher audience, so I’m going to give it a go, and see how successful I am.

On a related note, I’m presenting at the OpenEducation 2009 conference in Vancouver, and was thrilled to see on the program Barbara Illowsky, one of the authors of the  Connexions open textbook that I have found very useful, Collaborative Statistics,  (and a commenter on this blog).  It won’t be a session that I’ll miss, and I think it would be a treat to meet her in person.

It occurred to me that I might want to do a pretest/posttest method if I’m going to attempt to measure whether I learned anything as a result of my OER experiment.  It would also be a useful way for me to focus my learning a bit more–for example, I spent some time today at http://www.statsoft.com/textbook/stathome.html  (which was incredibly hard to read on the screen due to all the background noise, confirming my belief that looks actually do matter in OER development) and found myself encountering a fair amount of basics that I already knew.

So, I’m putting it out there…does anybody know of a quick pretest I could do to help me pinpoint what I do and don’t already know?

I spent about 30 minutes today listening the entire first chapter of the video resource that comes with the Collaborative Statistics open textbook.  I had read the chapter that it referenced about a a month ago, but hadn’t done anything since, so it served as a very useful refresher.  In fact, I really appreciated the video, since it allowed me to fold laundry, and do a bit of yoga  while I listened.  Most of the video was listenable (no looking at talking head required) but occasionally I had to jump back to the video when something was being demonstrated.  What was nice was that for the most part, the speaker gave an audio cue as to when something was about to be demonstrated, making the process a bit more seamless.  I’m not sure this was deliberate or not, but in the context of OERs, mobility, and usability, I thought this was something I would want to remember. Video was clearly the good choice of tool for this chapter, since the visual demonstrations (which, pen on paper, were extremely low tech but effective) really enhanced my learning.  But I found myself imagining myself with my nano on a lunch hour walk, or on the bus somewhere, and these cues coming being really useful.

Since I have a strong interest in the feasibility of OERs being adapted in low resource locations where translation from English is required, I found myself reflecting on what might be required to allow for localisation of this  particular resource.  A few things stood out when I thought about it with this lens, although I’m fully aware that the intended audience of this resource might have been much smaller.

First, there were several useful examples being used to demonstrate key concepts of statistics, such as sampling.  In this particular case, the notion of sampling  a few vs entire population was described in terms of using a toothpick check a batch of brownies cooking in the oven to see if they were done.  This example really worked for me,  since a:  being North American  I know what brownies are and; b:  I have done a fair amount of baking and know what it means to put a toothpick into a pan to test for readiness.  But I was reminded that the entire year I lived in Malaysia I never once saw a brownie, nor saw an oven used (if they had one) in any of the kitchens, since baking in tropical weather doesn’t really appeal.

One of the features of the video that I quite like is that it provides close captioning, which I can see of huge value to a more global audience, in that it provides a way of checking what you’ve heard. I can think of how this can be useful at least one situation.  Regardless of whether English is your first language, when encountering new terminology or concepts, the close captioning provides a feedback system on your own understanding of what you’ve heard on a linguistic level.  Providing a text transcript (which shouldn’t be hard since the cc is already there) would be a huge bonus with anybody actually tasked with translating the audio–it’s much quicker to translate with a text transcript than having to actually generate one first for translation.  Since translation is pretty resource intensive/costly, this would make the reuse of this OER a little more accessible.

One final point: the video opened with a reference to Math 10, which wasn’t in keeping with the title of the OER-Collaborative Statistics, but also left me feeling a bit sheepish that despite a PhD in Education, I’m still at a Grade 10 math level.  It’s really an ego thing, and quite trivial, but again, what does Math 10 mean to somebody from an entirely different education system?  

My rating for this OER:  4 out of 5 stars

It’s hard to believe it’s been a month since I last dove into some statistics.  A crazy, unpredictable holiday, followed by a busy schedule at work has meant I’ve had to neglect this little project, but it is by no means abandoned.  I’ll likely get going again next week, and see whether picking up where I left off is even feasible.

I was perusing the original link to the Collaborative Statistics book, discovering that there were updates made on Dec 5 (maybe an RSS feature here would be useful, although I see that they are tracked), and found a section on resources that contains a half hour video lecture to accompany each of the chapters.  Maybe this is new too, or maybe I missed it the first time around.  Regardless, this OER is setting the access bar even higher by including close captioning for the video, and a link to the right of the video that takes me to the relevant chapter of the book.  This is a nice navigational feature.

Judy Baker kindly provided me with a link to a very interesting video series called Against All Odds but I can’t open any of the Windows Media Player files (despite having downloaded it and updated all my applications–I’m on a Mac OSX).  This took me back to my 2001 experiment where I spent about 30% of my self-directed study time locating resources and downloading an assortment of pesky plug ins.  I certainly understand why Quicktime is a player of choice in Distance Education development, and perhaps in the interest of OER accessibility some of these things need to be addressed.

Nov 26

I’m up to page 20 of the Collaborative Stats book. This has been a good place to start—it’s written in a very accessible style, with lots of examples.  I’m getting familiar with some of the concepts, and they even make sense, but I’m not sure I could apply any of them at this point.  The book is so good I’m wondering whether this is will be 80% of what I need.

Time spent: approx 20 min

Right now what I would really like is an “affinity group” (as James Gee would call it).  Some place like Ravelry that gathers all the enthusiastic quantitative research people in a network. I think I’d lurk for a while, then add some quantitative research friends, and hit them up for research design advice or questions.  Some place where newcomers and experts could share and hang out.  I’ve noticed that crafters are really good at sharing and helping each other out, and I wonder how this could be transferred to an OER experience. It almost makes me wonder whether “informal” disciplines such as knitting should be examined for their ability to create such collaborative communities.  

Update:  My search for a stats or quantitative research social network turned up some groups on Ning, but alas, all were protected.  I joined the Sew-What’s-New community and discovered there are almost 7000 members.

I like this template a lot for the ability to categorize the collection of links I’m accumulating on the right.  I’ve begun adding descriptions to the links (hovering will reveal comments) as a way of rationalizing my selection of the resources, and documenting why some OERs will or will not work for me.

Googled  syllabus quantitative methods and education and came across an entire program .  I think I’m at the top of the list, needing Basic Statistics.  This  also came up:  not a syllabus but a nice start.

A syllabus here but bonus–lots of helpful looking hands-on assignments.

Time spent exploring today:  approx 30 minutes.  I’m clearly still in a stage of gathering resources. Or else procrastinating. But not really clear on what I need to learn. Since I abhor numbers in general, I would really like somebody to tell me exactly where to start, and what I need to learn that is relevant to education.

So begins Day 1 of the OER project.

Nov 19. 

Did a perusal of different searching sites (freelearning, thanks Scott) and OER commons and searched for statistics, quantitative methods in education, statistics for education.

Variety of resources, a bit over and underwhelming—some clicks lead me to some open but incomplete pages of textbooks (O’Reilly?).   Collaborative statistics, a module found via connexions via freelearning looked promising, especially in its approach, and the fact that its target audience is outside of math or engineering. After this initial search I’d almost really like some short video lectures or demos to supplement all the text I seem to be finding.

Realized since I can’t find a course called statistics for education research, I need to find a syllabus that will tell me what I need to learn.  Then maybe I can pull something together. 

Next steps:  google a course outline or syllabus.

Time spent: Approx 15 min.