Pages Navigation Menu

Course Review – Elementary Statistics MOOC from Udacity

People who have been following my Degree of Freedom One Year BA project will know that the Udacity Elementary Statistics MOOC is the course I had the most trouble completing.

Statistics MOOCs

Matt Buck via Flickr

This was mostly due to the fact that as an asynchronous course, this was a class I was able to start and stop as I pleased. And when my work load climbed to seven simultaneous courses in April and May, Stats became the easiest class to push out until such time as I was able to give it more complete attention.

But I’ll also admit to a certain difficulty getting through the first half of the material, largely due to my own learning issues with regard to abstract vs. applied mathematics. Having recently dug up a copy of my original college transcript, it all came back to me how much I struggled for Bs in classes like calculus and linear algebra, even as I comfortably received higher grades in subjects like physical chemistry that applied those same mathematical concepts to real-world issues (at least on the atomic and molecular level).

What this translated to with regard to Udacity’s Elementary Statistics MOOC is that it took me several repeat viewings to grasp the basic statistical concepts that made up the first half of the course, but once the class moved onto subjects such as ANOVA and regression testing (statistical tools I actually made a fair amount of use of during my years working in field of professional testing), everything became easier.

But personal issues aside, how does Elementary Statistics stack up as a MOOC course?

Well, as Degree of Freedom followers know, I’ve got a bit of a soft spot for Udacity’s course format. For unlike the majority of MOOC courses that simply point the camera at the professor and shoot (with editing often consisting of little more than breaking hour-long lectures into ten- or fifteen-minute segments), Udacity takes a different cinemagraphic approach to its courses; utilizing the electronic white board as their canvas for lectures made up of dozens of very short videos (each 1-2 minutes in length) strung together to build a lesson.

The most interesting aspect of Udacity’s approach is their integration of assessment into their lessons with a majority of micro-videos ending with a problem that needs to be solved before students are allowed to move onto the next video. And a quiz appears at the end of each multi-video lesson (re-enforcing learning with more assessment), with cumulative exams asking still more questions greeting you at the end of every few lessons.

Because of the numerical nature of the material, many of these assessment questions are open ended, requiring you to massage numbers, perform calculations and look up information (such as critical values associated with various statistical tests) in order to solve a problem. So passing the course required far more than being able to answer a handful of multiple choice questions (the assessment method used in a majority of my other MOOC classes).

Now the numerical nature of the subject matter meant the Udacity approach was ideal for the study of statistics (as opposed to my other Udacity class in Building a Startup where assessment consisted of more of the easy-to-answer multiple-choice questions I’ve become familiar with in other courses).

Udacity’s focus on assessment as a key component of learning may explain why this MOOC provider has focused more on quantitative subjects like math, science and technology, rather than topics involving subjective content such as philosophy (although I’m looking forward to starting Udacity’s Psychology course later this quarter to see how well that content fits their teaching format).

All that said, Udacity’s approach does take a bit of getting used to. I’ve already mentioned that their courses are asynchronous, meaning you can take as long as you like to complete a course. And for a subject like statistics that builds from one topic to the next, starting and stopping often requires repeating earlier lessons (at least it did for me) rather than simply picking up where you left off.

The fact that students are not taking the class on a common calendar also changes the nature of discussion boards, turning them primarily into a resource students use to support their work as they make their way assessment questions (rather than a place for more general discussion). And because class plays out almost entirely on the whiteboard, you should expect to spend very little time looking at your professor vs. his or her hands which dance across the screen (often struggling for something to do when all diagrams and formulas have been sketched out but further explanation continues).

And speaking of professors, I need to mention that while this course starts out by introducing you to the two San Jose State University professors (Sean Laraway and Ronald Rogers) who are the PhD’s behind the class, the vast majority of teaching is done by the Udacity course developer and educational consultant Katie Kormanik.

Now Kormanik is a skilled instructor who has mastered the medium of the Udacity teaching environment, so I had no issues learning from her vs. from the professors she worked with to develop the course. But this choice (combined with the other unique aspects of the class structure noted above) did leave me wondering whether I was taking the equivalent of a college course vs. an e-learning class similar to training programs like SkillSoft that many corporations make available to employees for independent online study.

Statistics seems to be a popular subject in the MOOCiverse with all of the major MOOC providers offering at least one course on the topic. (Udacity’s Intro to Statistics MOOC was reviewed previously by Shaw Yasser.) So students interested in finding out how to make, accept or reject hypotheses have choices in how they want to approach learning the subject. But I can attest that, even with the challenges I personally faced in getting through the course, Udacity’s Elementary Statistics MOOC was an effective means to master a subject too few of us understand – despite how much statistics (including the statistics surrounding many discussions on how well educational tools – including MOOCs – are doing) underlie so many of the questions we need to answer in our professional and personal lives.

Editor’s note: This guest post is from Jonathan Haber at Degree of Freedom, who is tracking his progress in trying to learn in just twelve months everything he would if enrolled in a four year liberal arts BA program and using only free resources.  Along the way he is writing reviews of courses he completes, some of which he generously allows us to republish here. To get all of Jonathan’s MOOC reviews, and more, be sure to sign up for the weekly Degree of Freedom Newsletter.

 

Jonathan Haber (19 Posts)

Jonathan Haber is a Boston-based writer and educational specialist whose Degree of Freedom project is experimenting with whether it's possible to learn everything you would get from a four year liberal arts degree in just twelve months using only free educational resources. You can follow his progress at www.degreeoffreedom.org.