Vviewpoints
DOI: 10.1145/1735223.1735235
education
how to Make Progress
in Computing education
Improving the research base for computing education
requires securing competitive funding commitments.
EdUCaTioN is The economic issue of the 21st century. Driven by global trade and a technologically connected, always-on global work force,
countries understand they must
innovate to succeed in the new business environment. A winning innovation policy is tricky to define, but it is
clear it starts with education—and it
starts early.
PhotograPh by dave bradley PhotograPhy/getty images
In the U.S., policymakers seem to
have heard the message. There is a national urgency to improve K– 12 education, and, in particular, ensure students
have a strong grasp of science, technology, engineering, and mathematics
(STEM) education. The Department of
Education is pouring an unprecedented hundreds of billions of dollars into
states to improve schools, help teachers, and support students. They want
to know this money is helping. If you
listen closely, you hear leaders from the
Secretary of the Education to members
of Congress talking about the need for
“evidence-based” reforms. Where does
this evidence come from? Largely, it
comes from measurement tools developed by education researchers.
At the same time, the computing
community sees a national urgency to
reform K– 12 computer science education. As computing transforms society
for the digital age, students need to be
able to think computationally about
the world to succeed in life. How do students really learn rigorous computing
concepts? We need research to tell us.
Computing is a relatively new disci-
pline with a small education research
base and limited assessments. Those
responsible for making policy deci-
sions in K– 12 are interested in adopt-
ing curriculum in schools where you
can assess how it is improving student
learning. They are also interested in fo-
cusing resources on the “core” that stu-
dents must know. Rigorous computing
courses, if they exist, aren’t typically in
the “core.” This leads to a chicken-and-
egg problem for K– 12 computer sci-
ence, where you can’t really measure
how students learn without putting it
in schools, but schools aren’t interest-
ed in it until you can measure it.
