Posts tagged ‘science education’
Joan Ferrini-Mundy spoke at our White House Symposium on State Implementation of CS for All (pictured above). Joan is the Assistant Director at NSF for the Education and Human Resources Directorate. She speaks for Education Research. She phrased her remarks as three research areas for the CS for All initiative, but I think that they could be reasonably interpreted as three sets of warnings. These are the things that could go wrong, that we ought to be paying attention to.
1. Graduation Requirements: Joan noted that many states are making CS “count” towards high school graduation requirements. She mentioned that we ought to consider the comments of organizations such as NSTA (National Science Teachers Association) and NCTM (National Council of Teachers of Mathematics). She asked us to think about how we resolve these tensions, and to track what are the long term effects of these “counting” choices.
People in the room may not have been aware that NSTA had just (October 17) come out with a statement, “Computer Science Should Supplement, not Supplant Science Education.”
The NCTM’s statement (March 2015) is more friendly towards computer science, it’s still voiced as a concern:
Ensuring that students complete college- and career-readiness requirements in mathematics is essential. Although knowledge of computer science is also fundamental, a computer science course should be considered as a substitute for a mathematics course graduation requirement only if the substitution does not interfere with a student’s ability to complete core readiness requirements in mathematics. For example, in states requiring four years of mathematics courses for high school graduation, such a substitution would be unlikely to adversely affect readiness.
Both the NSTA and NCTM statements are really saying that you ought to have enough science and mathematics. If you only require a couple science or math courses, then you shouldn’t swap out CS for one of those. I think it’s a reasonable position, but Joan is suggesting that we ought to be checking. How much CS, science, and mathematics are high school students getting? Is it enough to be prepared for college and career? Do we need to re-think CS counting as science or mathematics?
2. Teacher Credentialing: Teacher credentials in computer science are a mishmash. Rarely is there a specific CS credential. Most often, teachers have a credential in business or other Career and Technical Education (CTE or CATE, depending on the state), and sometimes mathematics or science. Joan asked us, “How is that working?” Does the background matter? Which works best? It’s not an obvious choice. For example, some CS Ed researchers have pointed out that CTE teachers are often better at teaching diverse audiences than science or mathematics teachers, so CTE teachers might be better for broadening participation in computing. We ought to be checking.
3. The Mix of Curricular Issues: While STEM has a bunch of frameworks and standards to deal with, we know what they are. There’s NGSS (Next Generation Science Standards) and the National Research Council Framework. There’s Common Core. There are the NCTM recommendations.
In Computer Science, everything is new and just developing. We just had the K-12 CS Framework released. There are ISTE Standards, and CSTA Standards, and individual state standards like in Massachusetts. Unlike science and mathematics, CS has almost no assessments for these standards. Joan explicitly asked, “What works where?” Are our frameworks and standards good? Who’s going to develop the assessments? What’s working, and under what conditions?
I’d say Joan is being a critical friend. She wants to see CS for All succeed, but she doesn’t want that to cost achievement in other areas of STEM. She wants us to think about the quality of CS education with the same critical eye that we apply to mathematics and science education.
I’ve only just started reading this new report from National Academies Press, but am finding it useful and interesting. What do we mean when we say that we want people to be scientifically literate? It’s an important question to ask when considering the goal of computational literacy.
Science is a way of knowing about the world. At once a process, a product, and an institution, science enables people to both engage in the construction of new knowledge as well as use information to achieve desired ends. Access to science—whether using knowledge or creating it—necessitates some level of familiarity with the enterprise and practice of science: we refer to this as science literacy.
Science literacy is desirable not only for individuals, but also for the health and well-being of communities and society. More than just basic knowledge of science facts, contemporary definitions of science literacy have expanded to include understandings of scientific processes and practices, familiarity with how science and scientists work, a capacity to weigh and evaluate the products of science, and an ability to engage in civic decisions about the value of science. Although science literacy has traditionally been seen as the responsibility of individuals, individuals are nested within communities that are nested within societies—and, as a result, individual science literacy is limited or enhanced by the circumstances of that nesting.
Science Literacy studies the role of science literacy in public support of science. This report synthesizes the available research literature on science literacy, makes recommendations on the need to improve the understanding of science and scientific research in the United States, and considers the relationship between scientific literacy and support for and use of science and research.
This is a really cool announcement. I believe that computing helps with all kinds of STEM learning, and admire the work at Northwestern on Agent Based Learning in STEM, Project GUTS, and Bootstrap. It’s particularly important for getting CS into schools, since so few schools will have dedicated CS teachers for many years yet (as described here for Georgia). I’m excited to see that Bootstrap will be moving into Physics as well as Algebra.
Bootstrap, one of the nation’s leading computer science literacy programs, co-directed by Brown CS faculty members Shriram Krishnamurthi and Kathi Fisler (adjunct), continues to extend its reach. Bootstrap has just announced a partnership to use its approach to building systems to teach modeling in physics, an important component of the Next Generation Science Standards (NGSS). This project is a collaboration with STEMTeachersNYC, the American Association of Physics Teachers, and the American Modeling Teachers Association.
The August issue of Communications of the ACM (see here) includes a paper in the Viewpoints Education column by Uri Wilensky, Corey E. Brady, and Michael S. Horn on “Fostering Computational Literacy in Science Classrooms.” I was eager to get Uri’s perspective on CS education in high schools into the Viewpoints column after hearing him speak at the January CS Education Research workshop.
Uri suggests that the best way to get computational literacy into high schools is by adding computer science to science classes. He’s done the hard work of connecting his agent-based modeling curriculum to Next Generation Science Standards. In Uri’s model, Computer Science isn’t a “something else” to add to high school. It helps science teachers meet their needs.
Uri isn’t the only one pursuing this model. Shriram and Matthias suggested teaching computer science through mathematics classes in CACM in 2009. Bootstrap introduces computer science at the middle school level as a way to learn Algebra more effectively. Irene Lee’s GUTS (“Growing Up Thinking Scientifically”) introduces computation as a tool in middle school science.
In most states today, computer science is classified as a business/vocational subject, called “Career and Technical Education (CTE).” There are distinct advantages to a model that puts CS inside science and mathematics classes. Professional development becomes much easier. Science and mathematics teachers have more of the background knowledge to pick up CS than do most business teachers. CS becomes the addition of some modules to existing classes, not creating whole new classes.
It’s an idea well worth thinking about. I can think of three reasons not to pursue CS through math/science model, and the third one may be a show-stopper.
(1) Can science and math teachers help us broaden participation in computing? Remember that the goal of the NSF CS10K effort is to broaden access to computing so as to broaden participation in computing. As Jane Margolis has noted, CTE teachers know how to teach diverse groups of students. Science and mathematics classes have their own problems with too little diversity. Does moving CS into science and mathematics classes make it more or less likely that we’ll attract a more diverse audience to computing?
(2) Do we lose our spot at the table? I’ve noted in a Blog@CACM post that there are computer scientists annoyed that CS is being classified by states as “science” or “mathematics.” Peter Denning has argued that computer science is a science, but cuts across many fields including mathematics and engineering. If we get subsumed into mathematics and computer science classes, do we lose our chance to be a peer science or a peer subject to mathematics? And is that going against the trend in universities? Increasingly, universities are deciding that computer science is its own discipline, either creating Colleges/Schools of CS (e.g., Georgia Tech and CMU) or creating Colleges/Schools of Information/Informatics (e.g., U. Washington, U. Michigan, Drexler, and Penn State).
(3) Do we lose significant funding for CS in schools? Here’s the big one. Currently, computer science is classified as “Career and Technical Education.” As CTE, CS classes are eligible for Perkins funding — which is not available for academic classes, like mathematics or science.
I tried to find out just how much individual schools get from Perkins. Nationwide, over $1.2 billion USD gets distributed. I found a guide for schools on accessing Perkins funds. States get upwards of $250K for administration of the funds. I know that some State Departments of Education use Perkins funding to pay for Department of Education personnel who manage CTE programs. To get any funding, high schools must be eligible for at least $15K. That’s a lot of money for a high school.
The various CS Education Acts (e.g., on the 2011 incarnation and on the 2013 incarnation) are about getting CS classified as STEM in order to access funding set aside for STEM education. As I understand it, none of these acts has passed. Right now, schools can get a considerable amount of funding if CS stays in CTE. If schools move CS to math and science, there is no additional funding available.
Perkins funding is one of the reasons why CS has remained in CTE in South Carolina. It would be nice to have CS in academic programs where it might be promoted among students aiming for college. But to move CS is to lose thousands of dollars in funding. South Carolina has so far decided that it’s not in their best interests.
Unless a CS education act ever passes Congress, it may not make economic sense to move CS into science or mathematics courses. The federal government provides support for STEM classes and CTE classes. CS is currently in CTE. We shouldn’t pull it out until it counts as STEM. This is another good reason to support a CS education act.
After the NCWIT Summit, we had two days of meetings with ECEP State Partners and our Advisory Board, hosted by Debra Richardson at the University of California at Irvine. Then, Barbara and I got a chance to visit with Alan Kay for a few hours on Friday. As always, we came away with pages of notes and a long list of things to read and think about. All of these meetings were productive and interesting, but the next stage on our California adventure has had me thinking about how we teach hard science and hard computer science.
A former student at Georgia Tech and one of the first MediaComp Teaching Assistants, Jim Gruen, now works at SpaceX. He invited Barb and I to come up for a tour. We rented a car and drove to Hawthorne.
Barb at SpaceX
What an amazing place! The front third of the building are where the 40 programmers (“Everything is software,” Jim told us) sit with other engineers and developers. The back 2/3’s of the building is the factory floor where rockets are assembled. As you walk onto the floor, there is mission control to your right, and above your head is the actual Dragon capsule that first docked with the International Space Station. It is an inspiring sight as you walk onto the factory floor.
We saw rockets being built! Jim showed us where engines are being assembled into racks, where carbon composites are molded into parts, where detailed metal parts are made with 3-D (metal!) printers, and where the parts of the fuel tanks are welded together then painted. We saw the shop where they’re making prototype space suits. We saw via live video stream (on a giant TV on the wall of the developers’ floor) the amazing Dragon Taxi that was just recently unveiled. We saw lots of people (mostly men, unfortunately) working to build a future where humans are space-faring.
I was deeply impressed. SpaceX has a corporate goal to put human beings on Mars. What a noble goal! (Perhaps we could compare that to a corporate goal of, say, getting more people around the world to drink fizzy, flavored sugar-water?)
Jim does kernel-level hacking. He works on the boot sequence for the flight computer, networking, and device drivers. He showed us his current project. He is integrating in the module responsible for firing the rocket that will pull the astronauts off of the rocket in case there is an explosion during take-off.
I left the SpaceX feeling like I just had a glimpse of the future. The discussions when I tell people about our visit have had me thinking about how we prepare students for that future.
SpaceX is exciting and motivating to everyone I’ve talked to. Admittedly, I tend to hang out with people interested in science and engineering. Our daughters were jealous that we got to visit SpaceX. The other night, my 16 year old daughter had a girlfriend over for dinner, and the friend had questions for me about SpaceX. I was shocked — my teenage daughter is telling her female friends stories about her parents’ adventures?!? All the undergraduate and graduate students that I have told about SpaceX were impressed and had questions about our visit, both male and female students.
I do believe in the literature that suggests that women are socialized to be motivated to help people, and that efforts like service learning can motivate women to study CS. That’s part of the motivation for efforts like HFOSS. Many people are asking the question why women aren’t pursuing the “hard sciences.”
Maybe we’re using the wrong context in the hard sciences. Many people (not just women) don’t get too excited about physics, chemistry, and engineering. Everyone I’ve talked to is very excited about SpaceX. Working at SpaceX requires lots of “hard science.” The stuff that Jim is doing is low-level and geeky — rebuilding the Linux kernel stuff. My kids are still fascinated about it. Maybe women and other students would be more excited about science if the connection was made to end goals like SpaceX and to helping get humans onto other planets.
Computer science is not that difficult but wanting to learn it is.
Maybe that goes for “hard science,” too. SpaceX is a great reason to want to learn a lot of “hard science.”
Postscript: I told my daughters about this blog post. One daughter said, “We’ve both been to Space Camp (in Huntsville). Space Camp would be great except for that one annoying guy who always thinks he knows everything and wants to tell everyone all about it.” The other daughter agreed. Context is important, but we have to get the social stuff right, too.
Here’s an interesting project that could really get at generalizable “computational thinking” skills:
Wilkerson-Jerde’s research project will explore how young people think and learn about data visualization from the perspective of a conceptual toolkit. Her goals for “DataSketch: Exploring Computational Data Visualization in the Middle Grades” are to understand the knowledge and skills students bring together to make sense of novel data visualizations, and to design tools and activities that support students’ development of critical, flexible data visualization competence.
“Usually when we think of data visualization in school, we think of histograms or line graphs. But in contemporary science and media, people rely on novel, interactive visualizations that tell unique stories using data,” she explains.
Carl Weiman has accepted a position at Stanford to focus on science teaching. It’s a great place for him, and I expect that we’ll hear more interesting things from him in the future. One aspect of the story that I find particular interesting is Weiman’s dislike of MOOCs, and how that conflicts with the perspective of some of the MOOC advocates at Stanford.
Mr. Wieman left the White House last summer, after receiving a diagnosis of multiple myeloma and after spending two years searching for ways to force universities to adopt teaching methods shown through scientific analysis to be more effective than traditional approaches.
His health has improved, Mr. Wieman said in an interview last week. But rather than try again through the political process to prod universities to accept what research tells them would be better ways of teaching and retaining students in the sciences, he now hopes at Stanford to work on making those methods even better.