Note: I wrote this post for
Simply Statistics
at the request of Jeff Leek after several conversations
we had about building online courses.
Over the past few months I’ve been helping Jeff develop the Advanced Data
Science class he’s teaching at the Johns Hopkins Bloomberg School of Public
Health. We’ve been trying to identify technologies that we can teach to
students which (we hope) will enable them to rapidly prototype data-based
software applications which will serve a purpose in public health. We started with
technologies that we’re familiar with (R, Shiny, static websites) but we’re
also trying to teach ourselves new technologies (the Amazon Alexa Skills API,
iOS and Swift). We’re teaching skills that we know intimately along with skills
that we’re learning on the fly which is a style of teaching that we’ve practiced
several
times.
Jeff and I have come to realize that while building new courses with
technologies that are new to us we experience particular pains and frustrations
which, when documented, become valuable learning resources for our students.
This process of documenting new-tech-induced pain is only a preliminary step.
When we actually launch classes either online or
in person our students run into new frustrations which we respond to with
changes to either documentation or course content. This process of quickly
iterating on course material is especially enhanced in online courses where the
time span for a course lasts a few weeks compared to a full semester, so kinks
in the course are ironed out at a faster rate compared to traditional in-person
courses. All of the material in our courses is open-source and available on
GitHub, and we teach our students how to use Git and GitHub. We can take
advantage of improvements and contributions the students think we should make
to our courses through pull requests that we receive. Student contributions
further reduce the overall start-up pain experienced by other students.
With students from all over the world participating in our online courses we’re
unable to anticipate every technical need considering different locales,
languages, and operating systems. Instead of being anxious about this reality
we depend on a system of “distributed masochism” whereby documenting every
student’s unique technical learning pains is an important aspect of improving
the online learning experience. Since we only have a few months head start
using some of these technologies compared to our students it’s likely that as
instructors we’ve recently climbed a similar learning curve which makes it
easier for us to help our students. We believe that this approach of teaching
new technologies by allowing any student to contribute to open course material
allows a course to rapidly adapt to students’ needs and to the inevitable
changes and upgrades that are made to new technologies.
I’m extremely interested in communicating with anyone else who is using similar techniques, so if you’re interested please contact me via Twitter (@seankross) or send me an email: sean at seankross.com.
Note: I wrote this post for
Simply Statistics
at the request of Jeff Leek after several conversations
we had about building online courses.
Over the past few months I’ve been helping Jeff develop the Advanced Data
Science class he’s teaching at the Johns Hopkins Bloomberg School of Public
Health. We’ve been trying to identify technologies that we can teach to
students which (we hope) will enable them to rapidly prototype data-based
software applications which will serve a purpose in public health. We started with
technologies that we’re familiar with (R, Shiny, static websites) but we’re
also trying to teach ourselves new technologies (the Amazon Alexa Skills API,
iOS and Swift). We’re teaching skills that we know intimately along with skills
that we’re learning on the fly which is a style of teaching that we’ve practiced
several
times.
Jeff and I have come to realize that while building new courses with
technologies that are new to us we experience particular pains and frustrations
which, when documented, become valuable learning resources for our students.
This process of documenting new-tech-induced pain is only a preliminary step.
When we actually launch classes either online or
in person our students run into new frustrations which we respond to with
changes to either documentation or course content. This process of quickly
iterating on course material is especially enhanced in online courses where the
time span for a course lasts a few weeks compared to a full semester, so kinks
in the course are ironed out at a faster rate compared to traditional in-person
courses. All of the material in our courses is open-source and available on
GitHub, and we teach our students how to use Git and GitHub. We can take
advantage of improvements and contributions the students think we should make
to our courses through pull requests that we receive. Student contributions
further reduce the overall start-up pain experienced by other students.
With students from all over the world participating in our online courses we’re
unable to anticipate every technical need considering different locales,
languages, and operating systems. Instead of being anxious about this reality
we depend on a system of “distributed masochism” whereby documenting every
student’s unique technical learning pains is an important aspect of improving
the online learning experience. Since we only have a few months head start
using some of these technologies compared to our students it’s likely that as
instructors we’ve recently climbed a similar learning curve which makes it
easier for us to help our students. We believe that this approach of teaching
new technologies by allowing any student to contribute to open course material
allows a course to rapidly adapt to students’ needs and to the inevitable
changes and upgrades that are made to new technologies.
I’m extremely interested in communicating with anyone else who is using similar techniques, so if you’re interested please contact me via Twitter (@seankross) or send me an email: sean at seankross.com.
