Wednesday, February 6, 2013

Adventures in MOOC

I am now in my third week of a MOOC adventure. In case you are not familiar with the term, MOOC is a massively open online class.

In particular, I am enrolled in an eight-week Data Analysis class from the John Hopkins Bloomberg School of Public Health, offered through the Coursera platform.

Professor Jeff Leek describes the R statistical programming course as:

"This course is an applied statistics course focusing on data analysis. The course will begin with an overview of how to organize, perform, and write-up data analyses. Then we will cover some of the most popular and widely used statistical methods like linear regression, principal components analysis, cross-validation, and p-values. Instead of focusing on mathematical details, the lectures will be designed to help you apply these techniques to real data using the R statistical programming language, interpret the results, and diagnose potential problems in your analysis. You will also have the opportunity to critique and assist your fellow classmates with their data analyses. Here is a post where I describe how data analysis fits in with other quantitative subjects: http://simplystatistics.org/2013/01/10/the-landscape-of-data-analysis/"

Being "massively open" means that there can be lots of students. I cannot find a good indicator of how many students there really are, but one discussion board forum has almost 3,000 page views. One student also put together a Google Map of where around the world people are located. While not everybody probably participated in the map, I guess there are at least hundreds if not thousands of students in class with me. 

From NY Times Published: January 26, 2013
From NY Times, Published: January 26, 2013
In a recent article, Thomas Friedman wrote about a Coursera "revolution" after learning there were almost two and a half million people taking Coursera courses. That is up from just 300,000 students less than one year ago. 

With thousands of people in each course, a teacher is not going to have time to get to know the students, grade their quizzes, answer their questions, or perform other typical teacher activities. Instead, the MOOC solution is to have the students do things themselves. 

To enable students, Coursera courses consist of many self-service components:
  • Online videos
  • Downloadable lecture notes
  • Self-scoring online quizzes
  • Lots of auxiliary reference material
  • Course Wiki 
  • Course discussion forums 
  • Course Meetups 
  • Assignments which are peer graded 

My first surprise was the weekly quiz. They are along the lines of "Using the knife and bottle of whiskey under your seat, perform a self-appendectomy..." 

Back in my college days, you had to have all of the quiz answers safely stored within your head. That is no longer true in today's world of MOOCs. 

Instead, the quiz question might ask you to download a comma-separated file from a website and load it into a "data frame" using the R programming language. From there, you need to follow a list of instructions such as create a subset of data, perform data "munging"--I have been doing IT for over thirty years and that was a new term to me--and then answer a final question like: "On rows 124, 246, and 368, what are the values of ABCVAR?" 

Once I realized the quiz expects you to search for answers, I was fine. 

Like work at my Christian college, there is an honor code. At Valparaiso University, I always wrote at the bottom of each test: "I have neither given nor received, nor will I tolerate, the use of unauthorized aid." Coursera has a check-box version of this oath. 

If MOOC students get past the initial fear--I closed the first quiz for an entire day before venturing back for a second look---I think most will pass with flying colors. The reason being you can take each quiz up to four times, with your recorded grade being the very last attempt. 

Now, if the Coursera system gave you another set of random questions each time, it would be tough.

However, it graciously just gives you the same questions again and even shows you which ones you got right and wrong. They might put the multiple-choice answers in a different sequence and rewrite the question a little, but the quiz basically stays the same. 

So if you were given a question with four multiple-choice answers along with four attempts to solve it, I do believe most people would be able to pass the test (if not get 100%). These tests are half of the total score, so pretty much a given. 

The two assignments that make up the other half of the score might be a different issue. Those are to be graded by your peers according to a published rubric. I apology to my peers, but I am concerned about their ability to grade. 

But that will be another blog posting. 

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About Me

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I am a project-based consultant, helping data-intensive firms use agile methods and automation tools to replace legacy reporting and bring in modern BI/Analytics to leverage Social, Cloud, Mobile, Big Data, Visualizations, and Predictive Analytics. For several world-class vendors, I led services teams specializing in providing software implementation and custom application development. Based on scores of successful engagements, I have assembled proven methodologies and automated software tools.

During twenty years of technical consulting, I have been blessed to work with smart people from some of the world's most respected organizations, including: FedEx, Procter & Gamble, Nationwide, The Wendy's Company, The Kroger Co., JPMorgan Chase, MasterCard, Bank of America Merrill Lynch, Siemens, American Express, and others.

I was educated at Valparaiso University and the University of Cincinnati, graduating summa cum laude. In 1990, I joined Information Builders, the vendor of WebFOCUS BI and iWay enterprise integration products, and for over a dozen years served in branch leadership roles. For several years, I also led technical teams within Cincom Systems' ERP software product group and the custom software services arm of Xerox.

Since 2007, I have provided enterprise BI services such as: strategic advice; architecture, design, and software application development of intelligence systems (interactive dashboards and mobile); data warehousing; and automated modernization of legacy reporting.