How I completed 7 Online Courses in my spare time
Note: This post is was originally written for NM3204, an E-Learning course I took while studying abroad at NUS. I adapted it slightly for Medium. Since originally writing this post I’ve also interned at Udacity as a Software Engineer, but my thinking on online courses was shaped before my internship (and, of course, these viewpoints are my own).
After hearing that I had completed 7 online courses, a professor in one of my traditional, in-person courses commented:
Wow — you are one of few people I know to have completed so many MOOC courses — would love to hear more about how you kept to each courses’ schedule/requirements…
In this post, I’d like to outline the two reasons I was able to successfully complete so many MOOCs (Massively Open Online Courses).
- The Material — MOOCs are at the cutting-edge of current educational technology. Thus, many of the courses on Coursera/Udacity/EdX are teaching the newest material, especially when it comes to Computer Science. For instance, close to all of Udacity’s programming courses are taught using Python, a much more modern and beginner-friendly language than Java which is used in many traditional university settings. Additionally, both Coursera and Udacity have introduced Data Science specializations. Data Science is a new and evolving field that combines software engineering, statistics, data analysis and more. Most traditional universities don’t have programs that cover this emerging topic, but both leading MOOC providers do. This is just one example of how MOOCs are providing the most up-to-date material. I attribute much of my success in the software engineering job market to the MOOCs I’ve completed. [Note: I talk a little more about the content of Web Development, a Udacity course, and how it helped me become a better programmer in this Quora answer].
- The Delivery Format — There has been much discussion about the low completion rates of MOOCs and how the delivery format can be improved to bring those numbers up. The conventional wisdom is that in-person classes are better at delivering information to students and therefore have a higher completion rate. I am going to disagree with the conventional wisdom. For some students, me included, I think the MOOC delivery model is actually better than the classic in-person 1–2 hour lecture. Studies show that the average student can only pay attention in 10–15 minute bursts. Why then do we subject them to 90-minute lectures? Most MOOCs have videos with lengths of less than 10 minutes each, broken up by multiple choice or other types of quizzes. Udacity takes this even further with an average video length of 1–3 minutes and the opportunity to put what you have just learned to practice after almost every video (in the form of a quiz or programming challenge). For me, this format of learning-doing-learning-doing, along with the self-paced nature of the online courses, worked better to teach me material than the classic lecture-stye class. Udacity’s courses, in my opinion, have taken the pedagogy to a higher level than Coursera’s courses, which are more akin to simply videotaping lectures, splitting them up into 10 minute segments, and putting those videos online. [Note: I explain why I think Udacity is the best of the “Big Three” MOOC providers in this review on Quora from March 2013].
Feel free to comment with any questions you may have about my MOOC experience. The MOOC landscape is evolving quickly, with Coursera introducing “specializations” and Udacity “pivoting” to job-preparation courses (although remember that Udacity’s partnership with Georgia Tech for the $7,000 CS Masters degree is just beginning and is already the #1 online CS degree program).
And for those curious, the list of courses I’ve completed (so far!) is:
- Intro to Computer Science on Udacity
- Web Development on Udacity (my personal favorite, I highly recommend this course)
- Georgia Tech’s Computational Investing, Part 1 on Coursera
- University of Washington’s Introduction to Data Science on Coursera
- Stanford’s Startup Engineering on Coursera
- Stanford’s Algorithms: Design and Analysis, Part 1 on Coursera
- UC San Diego’s Learning How to Learn on Coursera
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