Comment by minimaxir | Hacker News Reader

Comment by minimaxir | Hacker News Reader

Working up a few quick statistics:

- Of the people that finished a course, male students had an average grade of 83.8%, female students had an average grade of 82.7%.

- The correlation between the grade of students who finished a course and the usage of supplemental materials is positive, but weak (0.16 for each variable, except for forum posts, which are complete uncorrelated with grade).

- The easiest course was HarvardX/CS50x/2012, with a perfect 100% average grade from all students who finished the course [EDIT: this course has pass/fail assignments]. The hardest was HarvardX/CB22x/2013_Spring, with an average score of 73.3% (the class, unsurprisingly, is about Ancient Greek Heroes)

- The course with the highest completion rate (# completed / # registered) is MITx/14.73x/2013_Spring at 7.48% (The Challenges of Global Poverty). The worst completion rate is HarvardX/CS50x/2012 at 0.07% (Introduction to Computer Science I, note that this is also the most registered course by a large margin)

- All classes have more male students than female students. The class with the highest Male/Female ratio is MITx/2.01x/2013_Spring at 17:1 (Elements of Structures). The class with the lowest ratio is HarvardX/PH278x/2013_Spring at 1.03:1 (Human Health and Global Environmental Change)

Let me know if you have any statistical ideas.

Your gender-related analysis is a bit incomplete. You should state that you're only including records for which gender is specified.

- Overall, 20.4% of the records have an unknown or unspecified gender, for which the average grade is 84%.

- Every class has between 6-29% with unspecified genders. In four of the courses, there are more unknowns than the difference between male and females.

A more interesting analysis (to me) is completion and grade vs. engagement, which they're clearly trying to track by including data about student events. I'm not sure how to approach this. On first glance, it seems that for some courses, it's equally likely a student in the top 10% of engagement (going by # days student interacted with site), will have achieved either a spectacularly high or low grade.

Maybe it's time I take one of those Data Science courses, myself.

On gender: are those meaningful differences? Does it make sense for me to ponder about why those with unspecified gender have better results?

Not really. The differences aren't very large, and there are pretty obvious causes.

Clearly the big variations in gender enrollment rate (and the likely different pass rates) and presumably the different pass rates is almost certain to be the biggest cause.

A 1% difference is not likely to be statistically significant.

Regarding easiest vs. hardest, while I'd tend to agree with the conclusion, the logic is just plain wrong. Final course scores depend more on grading structure than anything.

Many of the best courses use mastery learning. You can keep trying until you get it. This usually leads to 100% averages, actually quite well-deserved, since all students learn everything.

Heroes was a course which encouraged different levels of participation. It's probably the best MOOC ever run, but explicitly designed so you'd get out what you put in, and to accommodate all levels. Many students chose to put less in.

The course has 1287 graduates, all with a perfect score, so I believe your conclusion is correct. Edited OP.

Opinions differ I guess. I signed up for that class with a fair bit of anticipation and couldn't make it through the first lecture. It just didn't engage me at all. But a lot of people apparently felt differently.

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