Social Network Analysis

After posting (yesterday) about the Coursera Social Network Analysis MOOC I received a form email that impressed me. It looks like the Coursera staff are monitoring the Web for conversation about this particular MOOC. The email was well crafted and balanced, conveying respect for those who wanted to blog about the course but reminding students of the honour code.

To summarize the email:

Posting solutions to quiz problems is not allowed.
Sharing experiences, ideas, and examples that go beyond the assignments is allowed.
Sharing/discussing assignments after the deadline is allowed, but this should not take place publicly (i.e. on a blog)

The email concluded with a reminder of the Coursera honor code:

My answers to homework, quizzes and exams will be my own work (except for assignments that explicitly permit collaboration).

I will not make solutions to homework, quizzes or exams available to anyone else. This includes both solutions written by me, as well as any official solutions provided by the course staff.

I will not engage in any other activities that will dishonestly improve my results or dishonestly improve/hurt the results of others.

I was impressed that Coursera is actively communicating and reinforcing the honor code. I have noticed that for other/older Coursera courses that some students have posted old quiz questions and possible solutions. Hopefully the reminder emails will limit the sharing of assignment information.

I am watching the Week 1 videos as I travel too and from work. Being able to download the videos to a tablet, and then watching them on the El has been very helpful. In my last course the instructor positioned the camera in such a way to capture footage of him working with a Wacom Cintiq display and splitscreen the results with Camtasia (on the Mac). This instructor is using a splitscreen that mixes PowerPoint slides with a talking head – the downside of this is sometimes the experience is akin to the “uncanny valley,” the instructors eyes and attention is directed away from the camera (towards off-camera notes) and the communication does not work as well. But when you get the “direct eye contact” the presentation comes across particularly well, and the instructors passion for the subject makes the topic come alive.

I definitely get the opinion that the Coursera MOOCs (and maybe all MOOC in general) are faculty-driven. The faculty are doing this because they love the topics and the idea of open education.

Just started my second Coursera MOOC (Social Network Analysis). Very interesting to notice the changes and improvements going forward. Coursera is now sending an updated email alert when the course is about to start:

Today’s the first day of Social Network Analysis. Here’s checklist to help you get started:

✔ Log in to the course and review the syllabus
✔ Watch the first lecture
✔ Go to the forum and introduce yourself (i.e. Hi! My name is Gustavo and
I’m from San Francisco.) Don’t worry, they won’t bite!
✔ Schedule a time to watch the video lectures and do the assignments
each week
✔ Visit meetup.com/coursera to see if there’s a in-person meetup
happening in your area
✔ Fill out your profile (if you haven’t already!)
✔ Have fun!

Let the learning begin!

Your Coursera Team

Logging into the course for the first time, students are now presented with these honour code statements:

In order to ensure fairness, all students participating in any of our online classes must agree to abide by the following code of conduct:

I will register for only one account.
My answers to homework, quizzes and exams will be my own work (except for assignments that explicitly permit collaboration).

I will not make solutions to homework, quizzes or exams available to anyone else. This includes both solutions written by me, as well as any official solutions provided by the course staff.

I will not engage in any other activities that will dishonestly improve my results or dishonestly improve/hurt the results of others.

The first assignment looks very interesting, and involves downloading data from my Facebook network (195 contacts) and loading this into Gephi. Looking forward into how things progress.

One of my initial observations is how the grading policy for this course is markedly different to the previous one. I don’t know how much direction Coursera provides to faculty. Policy is as follows:

Grading scheme
non-programming option 8 homework assignments are worth 10 points each. The 7 highest scores will be counted toward 70% of the grade (i.e. I will be dropping the lowest score from your assignments) . The final exam (multiple choice + short answer) counts for 30% of the final grade. A certificate will be issued to those achieving 80%+ of the total points possible.

programming option If you select this option, in addition to the regular assignments there will be ~4 programming assignments, the last of which will be a an independent mini-project to be peer-evaluated. The projects can optionally be submitted to the forum. Those voted up by the community will be featured and discussed in a Google Hangout session.

Late policy
I realize that many of you are leading busy lives and may not always be able to meet the deadlines. You can always skip one of the assignments (only the top 7 will be counted). You also have an allocation of late days (8 in total). If you don’t allocate late days, the assignment will be marked down 10%/day. These lenient policies are meant to encourage you to submit work throughout the course without stressing too much about deadlines.

Also, there are four teaching staff rather than one in my previous course. I wonder if this is a model Coursera is moving towards, or if this was just a decision for this course and the nature of the assignments.

One thing of particular note with the Coursera videos, is that they provide subtitles as a standard. The FAQs indicate that the primary focus here is for students where English is not their first language, not students with disabilities.