Posts tagged ‘STEM’
How CS differs from other STEM Disciplines: Varying effects of subgoal labeled expository text in programming, chemistry, and statistics
My colleagues Lauren Margulieux and Richard Catrambone (with Laura M. Schaeffer) have a new journal article out that I find fascinating. Lauren, you might recall, was a student of Richard’s who applied subgoal labeling to programming (see the post about her original ICER paper) and worked with Briana Morrison on several experiments that applied subgoal labeling to textual programming and Parson’s problems (see posts on Lauren’s defense and Briana’s).
In this new paper (see link here), they contrast subgoal labels across three different domains: Chemistry, statistics, and computer science (explicitly, programming). I’ve been writing lately about how learning programming differs from learning other STEM disciplines (see this post here, for example). So, I was intrigued to see this paper.
The paper contrasts subgoal labeled expository text (e.g., saying explicitly as a heading Compute Average Frequency) and subgoal labeled worked examples (e.g., saying Compute Average Frequency then showing the equation and the values and the computed result). I’ll jump to the punchline with the table that summarizes the result:
Programming has high complexity. Students learned best when they had both subgoal labeled text and subgoal labeled worked examples. Either one alone didn’t cut it. In Statistics, subgoal labeled examples are pretty important, but the subgoal labeled text doesn’t help much. In Chemistry, both the text and the worked examples improve performance, and there’s a benefit to having both. That’s an argument that Chemistry is more complex than Statistics, but less complex than Programming.
The result is fascinating, for two reasons. First, it gives us a way to empirically order the complexity of learning in these disciplines. Second, it gives us more reason for using subgoal labels in programming instruction — students just won’t learn as well without it.
Where the STEM Jobs Are (and Where They Aren’t): Ignoring health care and end-user programmers
The NY Times linked below attracted a lot of attention because it claims that CS is the only field where demand outstrips supply. There’s a big asterisk on the graph below — the claim that there are more life sciences graduates than jobs “does not include health care occupations.”
This report still underestimates the demand for CS in industry. Here at Georgia Tech (and at many other schools, as I read Generation CS), a huge part of our undergraduate course load comes from students who are not majoring in CS, but they expect to use CS in their non-software-development jobs.
“There is a huge divide between the computing technology roles and the traditional sciences,” said Andrew Chamberlain, Glassdoor’s chief economist. At LinkedIn, researchers identified the skills most in demand. The top 10 last year were all computer skills, including expertise in cloud computing, data mining and statistical analysis, and writing smartphone applications. In a recent analysis, Edward Lazowska, a professor of computer science at the University of Washington, focused on the Bureau of Labor Statistics employment forecasts in STEM categories. In the decade ending in 2024, 73 percent of STEM job growth will be in computer occupations, but only 3 percent will be in the physical sciences and 3 percent in the life sciences. A working grasp of the principles of science and math should be essential knowledge for all Americans, said Michael S. Teitelbaum, an expert on science education and policy. But he believes that STEM advocates, often executives and lobbyists for technology companies, do a disservice when they raise the alarm that America is facing a worrying shortfall of STEM workers, based on shortages in a relative handful of fast-growing fields like data analytics, artificial intelligence, cloud computing and computer security.
Study says multiple factors work together to drive women away from STEM
I wrote recently in a blog post that we don’t know enough why women aren’t going into computing, and I wrote in another blog post that CRA is finding that we lose women over the years of an undergraduate degree in CS. Here’s an interesting study offering explanations for why we are not getting and keeping women:
The study analyzed a large, private university on the East Coast, using data from 2009-16, broken down semester-by-semester to track students’ changes in grades and majors in as close to real time as possible. While other studies have suggested that women came out of high school less prepared, or that increasing female STEM faculty could help provide women mentors, the Georgetown study didn’t support those findings.
“Women faculty don’t seem to attract more women into a field, and that was sort of sad news for us,” Kugler said. “We were hoping we could make more of a difference.”
One of the reasons women might feel undue pressure in STEM fields might actually be because of how recruiting and mentoring is framed. Many times, those efforts actually end up reinforcing the idea that STEM is for men.“Society keeps telling us that STEM fields are masculine fields, that we need to increase the participation of women in STEM fields, but that kind of sends a signal that it’s not a field for women, and it kind of works against keeping women in these fields,” Kugler said.
And while many STEM majors are male-dominated, the framing of recruitment and mentorship efforts can sometimes paint inaccurate pictures for STEM fields that aren’t male-dominated, and contribute to an inaccurate picture for STEM as a whole, the paper says:
While men may not have a natural ability advantage in STEM fields, the numerous government and other policy initiatives designed to get women interested in STEM fields may have the unintended effect of signaling to women an inherent lack of fit.
While computer science, biophysics and physics tend to be male-dominated, Kugler said, neurobiology, environmental biology and biology of global health tend to be female-dominated.
Source: Study says multiple factors work together to drive women away from STEM
Growing Computer Science Education Into a STEM Education Discipline: November CACM
I manage the education column in CACM’s Viewpoints section, and this quarter, Briana Morrison and I wrote the piece. While CS is now officially “in STEM,” it’s not like mathematics and science classes. In the November issue, we look at what has to happen to make CS as available as mathematics or science education. ( BTW, Briana defends her dissertation today!)
Computing education is changing. At this year’s CRA Snowbird Conference, there was a plenary talk and three breakout sessions dedicated to CS education and enrollments. In one of the breakout sessions, Tracy Camp showed that much of the growth in CS classes is coming from non-CS majors, who have different goals and needs for computing education than CS majors.a U.S. President Obama in January 2016 announced the CS for All initiative with a goal of making computing education available to all students.
Last year, the U.S. Congress passed the STEM Education Act of 2015, which officially made computer science part of STEM (science, technology, engineering, and mathematics). The federal government offers incentives to grow participation in STEM, such as scholarships to STEM students and to prepare STEM teachers. Declaring CS part of STEM is an important step toward making computing education as available as mathematics or science education.
The declaration is just a first step. Mathematics and science classes are common in schools today. Growing computing education so it is just as common requires recognition that education in computer science is different in important ways from education in STEM. We have to learn to manage those differences.
White House Call to Action: Incorporating Active STEM Learning Strategies into K-12 and Higher Education
I’m so happy to see this! I’ve received significant pushback on adopting active learning among CS faculty. Maybe a White House call can convince CS higher education faculty to adopt active learning strategies?
Active learning strategies include experiences such as:
- Authentic scientific research or engineering or software design in the classroom to help students understand the practice of science, technology, and engineering and promote deep learning of the subject matter;
- Interactive computer activities to support students’ exposure to trial-and-error and promote deep learning;Discussions to encourage collaboration and idea exchange among students; and
- Writing to generate original ideas and solidify knowledge.
Today, the White House Office of Science and Technology Policy is issuing a call to action to educators in K-12 and higher education, professional development providers, non-profit organizations, Federal agencies, private industry, and members of the public to participate in a nationwide effort to meet the goals of STEM for All through the use of active learning at all grade levels and in higher education.
Bootstrap computer science in Physics, as well as Algebra
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.
STEM as the Goal. STEAM as a Pathway.
Dr. Gary May, Dean of the College of Engineering at Georgia Tech, is one of my role models. I’ve learned from him on how to broaden participation in computing, what academic leadership looks like, and how to make sure that education gets its due attention, even at a research-intensive university.
He wrote an essay (linked below) critical of the idea of “STEAM” (Science, Technology, the Arts, and Mathematics). I just recently wrote a blog post saying that STEAM was a good idea (see link here). I’m not convinced that I’m at odds with Gary’s point. I suspect that the single acronym, “STEM” or “STEAM,” has too many assumptions built into it. We probably agree on “STEM,” but may have different interpretations of “STEAM.”
The term “STEM” has come to represent an emphasis on science, technology, engineering, and mathematics education in schools. A recent Washington Post article critiques exactly that focus: Why America’s obsession with STEM education is dangerous.
From Gary’s essay, I think he reads “STEAM” to mean “We need to integrate Arts into STEM education.” Or maybe, “We need to emphasize Arts as well as STEM in our schools.” Or even, “All STEM majors must also study Art.” Gary argues that STEM is too important to risk diffusing by adding Art into the mix.
That’s not exactly what I mean when I see a value for STEAM. I agree that STEM is the goal. I see STEAM as a pathway.
Media Computation is a form of blending STEM plus Art. I’m teaching computer science by using the manipulation of media at different levels of abstraction (pixels and pictures, samples and sounds, characters and HTML, frames and video) as an inviting entryway into STEM. There are many possible and equally valid pathways into Computing, as one form of STEM. I am saying that my STEAM approach may bring people to STEM who might not otherwise consider it. I do have a lot of evidence that MediaComp has engaged and retained students who didn’t used to succeed in CS, and that part of that success has been because students see MediaComp as a “creative” form of computing (see my ICER 2013 paper).
I have heard arguments for STEAM as enhancing STEM. For example, design studio approaches can enhance engineering education (as in Chris Hundhausen’s work — see link here). In that sense of STEAM, Art offers ways of investigating and inventing that may enhance engineering design and problem-solving. That’s about using STEAM to enhance STEM, not to dilute or create new course requirements. Jessica Hodgins gave an inspiring opening keynote lecture at SIGCSE 2015 (mentioned here) where she talked about classes that combined art and engineering students in teams. Students learned from each other new perspectives that informed and improved their practice.
“STEM” and “STEAM” as acronyms don’t have enough content to say whether we’ve in favor or against them. There is a connotation for “STEM” about a goal: More kids need to know STEM subjects, and we should emphasize STEM subjects in school. For me, STEM is an important goal (meaning an emphasis on science, technology, engineering, and mathematics in schools), and STEAM is one pathway (meaning using art to engage STEM learning, or using art as a valuable perspective for STEM learners) to that goal.
No one — least of all me — is suggesting that STEM majors should not study the arts. The arts are a source of enlightenment and inspiration, and exposure to the arts broadens one’s perspective. Such a broad perspective is crucial to the creativity and critical thinking that is required for effective engineering design and innovation. The humanities fuel inquisitiveness and expansive thinking, providing the scientific mind with larger context and the potential to communicate better.
The clear value of the arts would seem to make adding A to STEM a no-brainer. But when taken too far, this leads to the generic idea of a well-rounded education, which dilutes the essential need and focus for STEM.
via Essay criticizes idea of adding the arts to push for STEM education @insidehighered.
Spatial Visualization Skills FAQs – Engage Engineering
A cool FAQ on the importance of spatial visualization skills in most STEM fields, and the research on how to improve them.
Research has demonstrated that training is an effective way to improve spatial visualization skills Contero et al., 2006; Ferguson, Ball, McDaniel, & Anderson, 2008; Hand, Uttal, Marulis, & Newcombe, 2008; Hsi et al., 1997; Martín-Dorta et al., 2008; Newcombe, 2006; Onyancha, Derov, & Kinsey, 2009; Onyancha, R., Towle, E., & Kinsey, B., 2007; Sorby, 2009; Sorby & Baartmans, 2000; Terlecki, Newcombe, & Little, 2008. In the area of mental rotation where the largest gender gap in performance exists, training has been effective as well Sorby & Baartmans, 2000; Sorby, Drummer, Hungwe, Parolini, & Molzan, 2006.In one study, students who failed the Purdue Spatial Visualization Test PSVT:R and enrolled in spatial skills training were able to improve their scores on the mental rotation test from approximately 50% to 77% or higher than students who failed the test and did not enroll in the course. These students also got better grades in 1st year STEM courses Sorby, 2009.
STEM is incredibly valuable, but STEAM makes it better
I am sympathetic to this argument for the value of STEAM (STEM+Art), rather than just STEM. I strongly believe in the value of creative expression in learning STEM subjects. That’s core to our goals for Media Computation. I believe that the STEAM perspective is why MediaComp has measurably improved motivation, engagement, and retention.
As a researcher, it’s challenging to measure the value of including art in learning STEM. I’m particularly concerned about the argument below. Singapore and Japan are less creative because they have less art in school? If we include more art in our schools, our students will be more innovative? If we’re already more innovative, and we have too little art classes, why should we believe that adding more art will increase our innovation?
But STEM leaves out a big part of the picture. “It misses the fact that having multiple perspectives are an invaluable aspect of how we learn to become agile, curious human beings,” Maeda said. “The STEM ‘bundle’ is suitable for building a Vulcan civilization, but misses wonderful irrationalities inherent to living life as a human being and in relation to other human beings.” A foundation in STEM education is exceptional at making us more efficient or increasing speed all within set processes, but it’s not so good at growing our curiosity or imagination. Its focus is poor at sparking our creativity. It doesn’t teach us empathy or what it means to relate to others on a deep emotional level. Singapore and Japan are two great examples. “[They] are looked to as exemplar STEM nations, but as nations they suffer the ability to be perceived as creative on a global scale.” Maeda said. Is the United States completely misinformed and heading down the wrong track? Not entirely. Science, technology, engineering and math are great things to teach and focus on, but they can’t do the job alone. In order to prepare our students to lead the world in innovation, we need to focus on the creative thought that gives individuals that innovative edge.
Half of STEM graduates in US went to community college at some point #CSEdWeek
Interesting claim from the American Association of Community Colleges — thanks from Cheryl Kiras for this: http://www.aacc.nche.edu/Publications/datapoints/Documents/ScienceCred_102814.pdf Here’s another reason why it’s important to care about all of the education pathways, and to look to community colleges for more (and more diverse) computing undergraduates.
Study finds increased STEM enrollment: Taking from education and business
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.
via Study finds increased STEM enrollment since the recession | Inside Higher Ed.
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.
via Wall Street’s collapse was computer science’s gain – Computerworld.
Shortage in the IT U.S. labor market? Or just a lack of graduates?
Is the shortage of STEM graduates a myth, as IEEE has been arguing recently? Is the case for IT different than the case for STEM overall?
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.
NSF Funding (NEW!): Improving Undergraduate STEM Education
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.
Marvel Girls in Stem Mentor Contest: The value and challenge of role models
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.”
September 2013 Special Issue of IEEE Computer on Computing Education
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.
Computing Ed Research - Guzdial's Take 
Recent Comments