Posts tagged ‘STEM’
First the good news: STEM enrollment is up. Then the surprising news: Humanities are not losing students to STEM. Rather, it’s the professional fields like education that are losing enrollment. That makes CS Ed (and other STEM discipline-based education research (DBER) fields) the odd winner-losers. Yay, there are more students, but there will be fewer STEM teachers in the future to teach them.
Policy makers regularly talk about the need to encourage more undergraduates to pursue science and technology fields. New data suggest that undergraduates at four-year institutions in fact have become much more likely to study those fields, especially engineering and biology.
And while much of the public discussion of STEM enrollments has suggested a STEM vs. liberal arts dichotomy (even though some STEM fields are in fact liberal arts disciplines), the new study suggests that this is not the dynamic truly at play. Rather, STEM enrollments are growing while professional field enrollments (especially business and education) are shrinking.
The ComputerWorldK agrees. They claim that the smart students were going into business, then Wall Street collapsed, and now they’re going into CS and that’s why we’re having sky-rocketing enrollments.
The number of computer science graduates will continue to increase. Computer science enrollments rose by nearly 30% in the 2011-12 academic year, and they increased 23% the year before that.
The trend of enrollment increases since 2010 bodes well for a “future increase in undergraduate computing production,” according to the report.
The recession that hit in 2008 sent IT unemployment soaring, but it may have done more damage to the finance sector, especially in terms of reputation. That prompted some educators at the time to predict that the recession might send math-inclined students from the world of hedge funds to computer science.
I found the analysis linked below interesting. Most IT workers do not have an IT-related degree. People with CS degrees are getting snapped up. The suggestion is that there’s not a shortage of IT workers, because IT workers are drawn from many disciplines. There may be a shortage of IT workers who have IT training.
IT workers, who make up 59 percent of the entire STEM workforce, are predominantly drawn from fields outside of computer science and mathematics, if they have a college degree at all. Among the IT workforce, 36 percent do not have a four-year college degree; of those who do, only 38 percent have a computer science or math degree, and more than a third (36 percent) do not have a science or technology degree of any kind. Overall, less than a quarter (24 percent) of the IT workforce has at least a bachelor’s degree in computer science or math. Of the total IT workforce, two-thirds to three-quarters do not have a technology degree of any type (only 11 percent have an associate degree in any field).4
Although computer science graduates are only one segment of the overall IT workforce, at 24 percent, they are the largest segment by degree (as shown in Figure F, they are 46 percent of college graduates entering the IT workforce, while nearly a third of graduates entering IT do not have a STEM degree). The trend in computer scientist supply is important as a source of trained graduates for IT employers, particularly for the higher-skilled positions and industries, but it is clear that the IT workforce actually draws from a pool of graduates with a broad range of degrees.
DUE funding is back! I wrote about TUES being closed down. This is the next iteration of a program in the NSF Division of Undergraduate Education to support STEM learning.
A well-prepared, innovative science, technology, engineering and mathematics (STEM) workforce is crucial to the Nation’s health and economy. Indeed, recent policy actions and reports have drawn attention to the opportunities and challenges inherent in increasing the number of highly qualified STEM graduates, including STEM teachers. Priorities include educating students to be leaders and innovators in emerging and rapidly changing STEM fields as well as educating a scientifically literate populace; both of these priorities depend on the nature and quality of the undergraduate education experience. In addressing these STEM challenges and priorities, the National Science Foundation invests in research-based and research-generating approaches to understanding STEM learning; to designing, testing, and studying curricular change; to wide dissemination and implementation of best practices; and to broadening participation of individuals and institutions in STEM fields. The goals of these investments include: increasing student retention in STEM, to prepare students well to participate in science for tomorrow, and to improve students’ STEM learning outcomes.
I’m glad to hear that Marvel wants to get involved in drawing more women into STEM. The involvement of Natalie Portman is interesting, but also challenging. There are these interesting studies showing that role models of women in STEM can trigger a kind of stereotype threat: “That can never be me, so I’d better not even try.” They’ll have to be careful in how they frame her involvement in science. Since I’ve been thinking about live coding, I’ve been wondering more about the importance of seeing embodiments of STEM workers that are otherwise invisible. Perhaps Marvel can provide that through this effort.
Marvel has announced the Ultimate Mentor Adventure, part mentor program, part contest, that gives American girls in grades 9-12 the resources to find and interview professional women in science, technology, engineering, and math, and then rewards them for doing it.
Natalie Portman has always been a consistent voice for greater screentime and opportunities behind the scenes for female characters and real women in the Marvel Cinematic Universe, so it doesn’t surprise me at all to learn that she’s the first face you see on the Ultimate Mentor Adventure’s explanatory video. Portman talks about her character Jane Foster, an astrophysicist, amid finished and behind the scenes clips of Jane in Thor: The Dark World, and, while the bombastic music of the trailers plays, she says, “the truth is, I really do love science. And the role gave me an amazing opportunity to explore science in all its possibilities.”
Betsy DiSalvo and I were guest editors for the September 2013 special issue of IEEE Computer on Computing Education. (The cover, copied above, is really nice!) The five articles in the issue did a great job of pushing computing education beyond our traditional image of CS education. Below I’m pasting our original introduction to the special issue — before copy-editing, but free for me to share, and it’s a reasonable overview of the issue.
Introduction to the Special Issue
Computing education is in the news regularly these days. England has just adopted a new computer science curriculum. Thousands of people are taking on-line courses in computer science. Code.org’s viral video had millions of people thinking about learning to code.
A common thread in all of this new computer science education is that it’s not how we normally think about computing education. Traditional computing education brings to mind undergraduates working late night in labs drinking highly-caffeinated beverages. “CS Class” brings to mind images of students gaining valuable vocational skills in classrooms. The new movement towards computing education is about computing education for everyone, from children to working adults. It’s about people learning about computing in places you wouldn’t expect, from your local elementary school to afterschool clubs. It’s about people making their own computing on things that only a few years ago were not computable at all, like your personal cellphone and even your clothing.
Computing has changed. In the 1950’s and 1960’s, computing moved from the laboratory into the business office. In the PC revolution, it moved into our homes. Now in the early 21st Century, it is ubiquitous. We use dozens of computers in our everyday life, often without even recognizing that the processors are there. Knowing about computing today is necessary for understanding the world we live in. Computer science is as valuable as biology, physics, or chemistry to our students. Consider a computer science concept: that all digitized information is represented in a computer, and the same information could be a picture or text or a virus. That is more relevant to a student today than the difference between meiosis and mitosis, or how to balance an equilibrium equation.
Computing also gives us the most powerful tool for creative expression humans have ever invented. The desktop user interface we use today was created at Xerox PARC in order to make the computer a creative device. Today, we can use computing to communicate, to inform, to delight, and to amaze. That is a powerful set of reasons for learning to control the computer with programming.
The papers in this special issue highlight how computing education has moved beyond the classroom. They highlight computing as porous education that crosses the boundaries of the classroom, and even boundaries of disciplines. These papers help us to understand the implications and the new needs of computing education today.
Maria Knobelsdorf and Jan Vahrenhold write on “Addressing the Full Range of Students: Challenges in K-12 Computer Science Education”. The issues change as computer science education moves down from higher education into primary and secondary education. What curricula should we use in schools? How do prepare enough teachers? Maria and Jan lay out the challenges, and use examples from Germany on how these challenges might be addressed.
“STEAM-Powered Computing Education using E-Textiles: Impacting Learning and Broadening Participation” by Kylie Peppler talks about integrating art into traditional STEM (Science, Technology, Engineering, and Mathematics) classrooms through use of new kinds of media. Kylie has students sewing computers into fabrics. Her students combine roles of engineers, designers, scientists and artists as they explore issues of fashion and design with electronic circuits and computer programming.
In “The Porous Classroom: Professional practices in the computing curriculum”, Sally Fincher and Daniel Knox consider how computer science students learn beyond the classroom. Learning in the classroom is typically scripted with careful attention to students activities that lead to learning outcomes. The wild and unconstrained world outside the classroom offers many more opportunities to learn, and Sally and Daniel look at how the opportunities outside the school walls influence students as they move between the classroom and the world beyond.
Karen Brennan’s paper “Learning Computing through Creating and Connecting” starts from the programming language, Scratch, which was created to introduce computing into afterschool computer clubhouses. Students using Scratch learned through creating wonderful digital stories and animations, then sharing them with others, and further learning by mixing and re-mixing what was shared. Karen then considers the porous education from the opposite direction — what does it take to take an informal learning tool, such as Scratch, into the traditional classroom?
The paper by Allison Elliott Tew and Brian Dorn, “The Case for Validated Tools in Computing Education Research”, describes how to measure the impacts of computing education, in terms of learning and attitudes. This work ties these themes together and back to the traditional classroom. Wherever the learning is occurring, we want to know that there is learning happening. We need good measurement tools to help us know what’s working and what’s not, and how to compare different kinds of contexts for different students. Allison and Brian tell us that “initial research and development investment can pay dividends for the community because validated instruments enable and enhance a host of activities in terms of both teaching and research that would not otherwise be feasible.” Tools such as these validated instruments may allow us to measure the impact of informal, maker-based, or practice-based approaches. Work in basic tools for measurement help us to ground and connect the work that goes on beyond our single classroom through the porous boundary to other disciplines and other contexts.
The story that this special issue tells is about computer science moving from subject to literacy. Students sometimes learn computer science because they are interested in computers. More often today, students learn computer science because of what they can do with computers. Computing is a form of expression and a tool for thinking. It is becoming a basic literacy, like reading, writing, and arithmetic. We use reading and writing in all subject areas. We see that students are increasingly using programming in the same way. The papers in this special issue offer a view into that new era of computing education.
An interesting study suggesting that role models and how they’re described (in terms of their achievements, or in terms of their struggles) has an interaction with students’ stereotypes about scientists and other professionals in STEM fields. So there are not just cognitive benefits to learning from failure, but there are affective dimensions to focusing on the struggle (including failures) and not just the success.
But when the researchers exposed middle-school girls to women who were feminine and successful in STEM fields, the experience actually diminished the girls’ interest in math, depressed their plans to study math, and reduced their expectations of future success. The women’s “combination of femininity and success seemed particularly unattainable to STEM-disidentified girls,” the authors conclude, adding that “gender-neutral STEM role models,” as well as feminine women who were successful in non-STEM fields, did not have this effect.
Does this mean that we have to give up our most illustrious role models? There is a way to gain inspiration from truly exceptional individuals: attend to their failures as well as their successes. This was demonstrated in a study by Huang-Yao Hong of National Chengchi University in Taiwan and Xiaodong Lin-Siegler of Columbia University.
The researchers gave a group of physics students information about the theories of Galileo Galilei, Issac Newton and Albert Einstein. A second group received readings praising the achievements of these scientists. And a third group was given a text that described the thinkers’ struggles. The students who learned about scientists’ struggles developed less-stereotyped images of scientists, became more interested in science, remembered the material better, and did better at complex open-ended problem-solving tasks related to the lesson—while the students who read the achievement-based text actually developed more stereotypical images of scientists.
I’m going to Michigan State University on Wednesday July 10 through Friday August 12. On the 10th, I’m visiting with colleagues whom I knew in Education at the University of Michigan (Bob Geier and Joe Krajcik) and giving a brownbag talk. I’m really looking forward to hanging out with Education folks for the day. I’ve just learned that Danny Caballero has moved to MSU, so I’m hoping to meet up with him, too. On Thursday and Friday, I’m attending a workshop on integrated engineering education. Since I used to do work like that, and haven’t done much in Engineering Education in years, I thought it would be fun and interesting — something I might want to get involved in again. Plus, it was a great chance to get back ‘home’ to Michigan.
The day after I get back, we are heading off to Boston and the CSTA Conference in Quincy, Massachusetts. We are holding an ECEP Day on Sunday July 14, to connect with CSTA Chapter Leaders and Leadership Cohort in the states where we’re working. On Monday, July 15, I’m just hanging out at the CSTA Conference, so if you’re there, I hope you will stop by the ECEP table and visit!