faculty at Georgia Institute of Technology, where our Online-MS in CS (OMS
CS) was praised by President Barack
Obama for its innovative accessibility
and low cost.
In the last six years, we have also
come to understand who is taking
MOOCs. We now know that MOOC students tend to be older than traditional
college students, have above-average
wealth, and are well educated. MOOCs
do not serve the masses. They do not
serve to replace traditional education,
but to augment it. They do not “
democratize education” as many had hoped.
Recent innovations in online learning are proving to have a “rich get
richer” effect—those already likely to
succeed benefit, and those left behind
are left at an increased disadvantage.
We argue that our current technology is
further undermining educational equity.
Computer science departments have
an ethical mandate to do better.
Is it OK to work to help the already advantaged? Certainly, the latest smartphone and the latest luxury car are
unapologetically created for the privileged. Our current education system
is regrettably not so different from a
luxury car—for a price, deluxe experiences are available that advantage the
children of the rich and help reproduce
their privilege. However, we have higher aspirations. We hope education can
serve as a leveler, helping everyone to
reach their full potential.
Some difference in privilege is necessary and even desirable to create a thriv-ing culture. How much privilege is OK?
What are our obligations to work toward
greater equity, for a society that aspires
to be just? These profound questions
were most eloquently addressed by the
philosopher John Rawls. Rawls was an
ethicist who argued that for a just society, “social and economic inequali-ties are to be arranged so that they are
both to the greatest benefit for the least
advantaged and attached to offices and
positions open to all under conditions
of fair equality of opportunity.”6 Rawls
called this “the difference principle.”
Most undergraduate computer
science majors are taught about
Rawlsian Justice. ABET-accredited
programs must include a course in
computing and society, which in-
We used to think
MOOCs were going
to change higher
cludes ethical frameworks. This definition of justice is ours. It is the one
we teach our own students.
Using Evidence to Tell Us If We Are
Reaching the Least Advantaged
We used to think MOOCs were going
to change higher education and would
democratize education. In 2012, a
reasonable person might have seen
development of MOOCs as a way to
bridge social and economic inequi-ties. By creating MOOCs, CS departments could reasonably claim they
were using their privilege to provide
great benefit to the least-advantaged
members of society.
Today, we have evidence MOOCs do
not work like that.
People who take MOOCs already
have access to education and tend to
be wealthy. Over 60% of MOOC participants already have undergraduate degrees.1 People who take MOOCs tend
to be wealthy. A 2015 paper5 reports,
“[MOOC] registrants on average live in
neighborhoods with median incomes
approximately .45 standard deviations
higher than the U.S. population.”
Analyses of Georgia Tech’s OMS CS
shows the students who apply to the
program are demographically different from those who take a face-to-face
MS CS program.4 The average OMS CS
applicant is a 34-year-old mid-career
American, while the average in-person
applicant is a 24-year old non-American. MOOCs reach a population that
would be unlikely to get a master’s
degree in another way. The program
is transformative for mid-career professionals—people who are already
successful, but aspire to more in their
careers. As information technology is
increasingly becoming critical to every
aspect of our society, OMS CS is playing a global role in preparing us for the
future. MOOCs are well worth offering,
but the population being served tends
not to be the least advantaged.
We now know that MOOCs as we
have used them so far violate Rawls’ Difference Principle—we are further advantaging the already advantaged. We
have an ethical mandate to do better.
We Have to Check
If We Are Doing Better
How do we reach the least-advantaged
students? Around the U.S., we can see
CS departments trying a lot of ways to
provide access to CS education. They are
offering summer camps, putting their
undergraduates into high school and
elementary classrooms to help teach
CS, or creating “road shows” to demonstrate computer science to elementary
or secondary school students who may
not know what computer science is.
Some of these work. Many do not.
Often, providing computing educational opportunities to “everyone”
operationally means only the most-ad-vantaged students actually get access.
Free and open summer camps are often filled first by the most-privileged
students who tend to hear about the
camps and fill them before less-privi-leged students get a chance.
It is challenging to figure out how
to make free and open resources available to less-advantaged students. For
example, our colleague Betsy DiSalvo
found that many free CS learning resources are never discovered by disadvantaged families simply because the
families do not know the right terms
to search for.2 The for-profit companies are better at tailoring their websites so their resources are the first to
appear for the terms that (for example)
immigrant families use when searching for learning resources.
Researchers are still working to
understand why MOOCs fail students
from less-advantaged backgrounds.
Access is part of the problem. An experiment offering Udacity MOOCs to
San Jose State University students was
ended early because the online students had disappointing performance
compared to the face-to-face students.
Part of the problem there was that the
online students did not always have
access to broadband Internet when at