May 2015 Vol. 27/No. 5
By Stuart Zweben and Betsy Bizot
By Lecia Barker (University of Texas at Austin), Tracy Camp (Colorado School of Mines), Ellen Walker (Hiram College), and Stu Zweben (Ohio State University)
We are in the throes of another undergraduate enrollment surge. The number of new CS/CE majors in bachelor’s programs at Taulbee departments this year has reached the peak levels seen at the end of the dot-com era. While this is better news than the opposite (declining enrollments), it is critical that the field take into account how policies and efforts to manage the enrollment surge will affect groups that are under-represented in computing. The Taulbee Survey shows a three-year increase of approximately 61 percent in undergraduate enrollment at U.S. CS departments between 2010-11 and 2013-14. We also note that the booming enrollments are not limited to doctoral granting universities. For the past two years, ACM has sponsored a survey similar to the Taulbee Survey, but which collects data from Non-doctoral granting Departments in Computing (NDC). The most recent study included data from 164 institutions representing 302 programs at the bachelor’s level. Between 2012-13 and 2013-14, these institutions saw more than a 16% increase in CS degree production and over 7% increase in total CS enrollment.
At the 2015 ACM SIGCSE conference in March, the authors held a discussion with about 150 computer science educators to understand how universities are dealing with increasing enrollments. Three general approaches were presented (which are not mutually exclusive), including managing staffing, class sizes and formats, and administrative policies.
Each of these approaches has implications for managing departments; e.g., teaching assistants require training and management and charging student fees requires approval beyond the department. In addition, some of the approaches may not be feasible. For example, although we are producing new Ph.D.s at record or near record numbers, about 60% are going to industry. Meanwhile, graduate enrollments have been stable the last few years, which suggests that there is limited capacity to handle growing undergraduate enrollments via the hiring of new doctoral graduates. Furthermore, some approaches may have especially negative consequences for diversity.
The U.S. computing community has put enormous effort into diversifying the field. Diversity is a social justice issue given the huge industry demand and high salaries associated with the demand, but also critical for innovation and problem solving (as shown by numerous studies). Programs like the National Science Foundation’s Broadening Participation in Computing and code.org have made significant inroads into formal and informal education. The students interested in computing are now more diverse than ever, yet the way the enrollment boom is managed could divert promising undergraduates into other majors.
Enrollment caps can help departments reduce the number of students who take courses or declare a major. Some course enrollment caps are simply based on a first-come, first-served approach or in randomization, so that students have a more or less equal chance to be admitted into classes or the major. Yet many departments go beyond FCFS, to give priority to students who are willing to declare the major. Students who take computer science in high school are more likely to declare the computer science major, are more likely to be a white or Asian male, and are more likely to be from a school large enough to have computer science classes. In contrast, underrepresented students and those from high schools without computer science courses are increasingly intrigued by computing and want to try it out for the first time as undergraduates. Enrollment policies influenced by pre-college course-taking limits access by women, under-represented minorities, and rural (under-resourced) areas.
Charging differential tuition or fees is another way that departments can accommodate increased teaching staff and lab expenses. However, research shows that differential costs are likely to more negatively impact students who are first in family to go to college or come from less affluent backgrounds.
Even when students can be accommodated, the need to scale course size may also negatively impact retention of under-represented groups in computing. Large lecture courses are less personal, with less faculty-student and student-peer interaction, two significant predictors of retention in computer science. Students can also have less information on which to judge their progress relative to their peers. In addition, when courses are large, it can be harder to establish ties with the peer networks that support learning and the development of identity as a person who belongs in the field. Women and under-represented minorities in computing also stand out as different and become isolated. Research shows that women leave computer science not because of their grades (which are typically higher than the men who stay), but because they are isolated, don’t understand their standing relative to peers, and feel the social climate is uncomfortable.
Some of the growth in interest in computer science appears to be tied to the availability of immediate, lucrative employment with a bachelor’s degree. For these students, the pipeline from undergraduate degree programs to graduate degree programs is likely to remain static. And, as mentioned, Taulbee data shows that graduate enrollments have been stable the last few years, with an increasing fraction of new graduate students from outside North America. Many attendees at our SIGCSE session, however, agreed that the current boom feels different than the dot.com boom. Specifically, SIGCSE panel attendees indicated that students taking computing classes during the dot.com boom seemed to mainly be interested in money, but now appear to be interested in computing. This interest is illustrated by the large increase in REU site applications seen by many universities, which indicates a graduate enrollment boom might be forthcoming.
Our field has faced booming enrollments twice in the past: in the mid-1980s and in the late 1990s. This one feels different to many of us. At the 2014 CRA Conference at Snowbird, we saw data from some universities that showed higher than ever demand for more advanced computing courses by students who were not computing majors. Since the previous surge, there has been a maturing of the computing disciplines of software engineering and information technology, and new areas such as security are on the rise. During the past decade, there has been an increase in the number of interdisciplinary programs that involve computing and demand for courses well beyond the introductory level. Students from all fields are much more aware of the power that computational abilities give to them within their chosen major. This is great news for the computing community. After the last boom, however, there was a considerable decline in gender diversity for both majority (e.g., white) and minority (e.g., Hispanic) populations. We need to be especially careful with our enrollment policies and practices right now, so that the computing community can benefit from the diversity that exists in the enrollment boom we currently face.
Mary Hall is a Professor in the School of Computing at the University of Utah, where she has been since 2008. She conducts research in programming language and compiler technology for parallel and high-performance computing architectures. Her current research focuses on automatic performance tuning of scientific and data analytics applications, which involves close collaboration with architects, computational scientists and domain scientists. She has previously served ACM through membership in awards and conference steering committees, leadership roles in conference organization, and most significantly, as member of the ACM History Committee for the past decade, and chair from 2009-2013. She has also served IEEE as a member of the Computer Society Award Committee, chair of the ACM/IEEE Kennedy Award Committee, and member of the Cray and Fernbach Award Committees. She has participated in several CRA-W mentoring workshops as both attendee and speaker, and this year's CRA Leadership in Science Policy Institute. She has co-authored numerous reports for government agencies, particularly NSF, DOE and DARPA, to establish the research agenda in compilers and high-performance computing. Professor Hall is an ACM Distinguished Scientist. She received an M.S. and Ph.D. in Computer Science from Rice University, in 1989 and 1991, respectively, and graduated Magna Cum Laude in 1985 with a B.A. in Computer Science and Mathematical Sciences also from Rice University. Prior to joining Utah, Professor Hall was jointly a research associate professor and project leader at University of Southern California, and previously held research positions at Caltech, Stanford and Rice.
The Education Committee of the Computing Research Association (CRA-E) is sponsoring workshops for faculty members interested in mentoring undergraduate research. The next two workshops are at ICRA (Seattle, Saturday May 30, 12-1:30 PM, lunch provided) and FCRC(Portland, Monday, June 15, 6-7:30 PM, appetizers provided). The workshops are free.
The objectives of these workshops are to provide faculty with resources and best practices for engaging undergraduates in their research, identifying funding sources for undergraduate research, and encouraging undergraduates to consider careers in research. To ensure a healthy pipeline of students motivated to continue on to graduate school, it is critically important that talented undergraduates obtain meaningful research experiences. Having faculty who are well-prepared to supervise undergraduate research can make a difference.
The Computing Community Consortium (CCC) is delighted to announce a new feature on our website!
Great Innovative Ideas are a way to showcase the exciting new research and ideas generated by the computing community. Once a month we will post an article highlighting new research going on in the field and ideas generated by our colleagues. This feature will replace the Highlight of the Week. All previously posted highlights of the week are archived here.
A few of the ideas showcased in Great Innovative Ideas will be from the CCC Blue Sky Ideas Conference Track, including our first Great Innovative Idea from Marian Petre (Open University) and Daniela Damian (University of Victoria, Canada) on Development Methodology.
By Jane Stout, CERP Director
In 2014, CERP asked 1,035 Ph.D. students (378 women; 657 men) to report their specialty area for their graduate research. Students were able to select more than one specialty area. Although there was considerable overlap in women and men’s specialty areas, there were also notable differences. In particular, women were more likely to specialize in human-oriented research areas such as Human-Computer Interaction, Biomedical Informatics and Social Computing/Informatics. This pattern is consistent with social science research indicating that, on average, women tend to be more interested in professions with clear social applications compared to men. CERP’s data suggest that one way to increase women’s participation in computing research is to promote women’s understanding of the social applicability of computing research early on. To accomplish this, academics and industry members could give research talks to K-12 and college students with emphasis on the real world implications of their research.
These data are brought to you by the CRA’s Center for Evaluating the Research Pipeline (CERP). CERP provides social science research and comparative evaluation for the computing community. To learn more about CERP, visit our website at http://cra.org/cerp/.
By Erwin Gianchandani & Gera Jochum, Directorate for Computer and Information Science and Engineering, National Science Foundation
In late March, NSF’s Directorate for Computer and Information Science and Engineering (CISE) sponsored a meeting, “Beyond Today’s Internet: Experiencing a Smarter Future,” which brought together researchers, educators, entrepreneurs, and civic leaders who are envisioning the future of the Internet through the Global Environment for Network Innovations, or GENI, Project and US Ignite Initiative. The joint session began with remarks by NSF Director Dr. France Córdova and White House Office of Science and Technology Policy Deputy Director for Technology and Innovation Tom Kalil, followed by demonstrations of what this future might entail, as detailed in a blog by Steve Lohr of the New York Times. NSF published a new special report with links to a press release, discovery stories, and videos that demonstrate the efforts of these communities, and CISE published a new perspective, which is reprinted below:
Beyond today’s Internet: Experiencing a smart and connected future
A perspective from Erwin Gianchandani, Deputy Division Director for Computer and Network Systems
Nearly 30 years ago, NSF initiated NSFNET, a general-purpose research network that sought to link scientists and engineers to the nation’s supercomputing facilities. Through additional public funding and private industry partnerships, NSFNET led to breakthrough discoveries in network architectures, protocols, and applications – that in turn ultimately developed into a major part of the backbone of today’s Internet.
Along with the Internet came essential and fundamental advances in networking and information technology that have transformed our world – from sensor networks to real-time data analytics to mobile and ubiquitous computing. Today, we all carry smartphones and tablets. We communicate with one another via emails transmitted over the Internet. And “Google” – which traces its origins back to NSF funding of a Stanford digital library project in the 1990s – is a verb and has grown into a multi-billion-dollar corporation.
Taken together, our fundamental research advances over the last several decades have accelerated the pace of discovery in nearly all fields – and they have enabled us to achieve national priorities and advance economic competitiveness.
But we haven’t stopped innovating the Internet despite these advances. NSF’s Directorate for Computer and Information Science and Engineering (CISE) has led long-term, significant investments in the Global Environment for Network Innovations, or GENI Project, and the US Ignite initiative. By investing in future networking architectures, protocols, and applications, and by helping to nurture and grow communities of researchers, experimenters, and developers, NSF continues to advance the capabilities and user experiences afforded by the Internet for generations to come.
A Global Environment for Network Innovations
Since its inception in 2007, NSF’s investments in GENI have allowed us to build an at-scale virtual laboratory for networking experimentation. Today, GENI spans over 60 university campuses throughout the U.S. as well as collaborators in over 30 countries around the world.
GENI has resulted in two key networking innovations:
1. First, it enables individual researchers to obtain access to their own secure “slice” of the network to conduct experiments.
2. And second, it allows for control of the network to be separate from the data flowing through it, enabling researchers and developers to customize experiments and applications, and to try radically new approaches for real-time, secure, enhanced, and personalized user experiences.
To date, more than 3,500 researchers around the globe have used GENI to conduct networking and other scientific experiments in ways that are simply not possible on today’s production Internet. And over 100,000 unique customizations have been created.
The innovations enabled by GENI – slicing and deep programmability – have also led to a new paradigm called Software-Defined Networking (SDN). Through partnerships with leading networking companies, SDN has become a multi-billion-dollar sector in just a matter of years – and it is anticipated to top $35 billion in market value by the year 2018.
Advancing Next-Generation Public-Sector Application Prototypes
To leverage our investments in GENI and take advantage of this programmable virtual laboratory, NSF, in collaboration with other federal, state, and local governments and industry partners, launched the US Ignite initiative in 2012.
US Ignite is connecting “islands” of broadband across the nation and demonstrating the potential of game-changing new applications that take advantage of ultra-high speed connections. These “apps” are offering new ways to provide never-before-imagined services that are in turn beginning to transform public safety, healthcare, education and learning, energy, transportation, manufacturing, and more.
Showcasing the potential of these next-generation applications, especially in addressing societal challenges, has proven that access to ultra-high-speed network connections is critically important for our future. It has also begun to demonstrate how a novel approach – a “user-inspired” model for advancing gigabit networks – is having an impact. For too long, there has been a fundamental deadlock: there has been insufficient investment in gigabit applications that can take advantage of advanced networking infrastructure because such infrastructure is rare and dispersed; and conversely, there has been a lack of broad availability of advanced broadband infrastructure for open experimentation and innovation because there are few advanced applications and services to justify it. We are breaking this deadlock by inspiring users themselves – through imagining, prototyping, and developing public-sector gigabit applications, and leveraging and extending a network testbed across U.S. campuses, cities, and regions.
In fact, since US Ignite’s launch three years ago, we have seen nearly 40 cities and regions across the nation deploy gigabit connections to homes and businesses – and over 100 concepts or prototypes of applications that use these advanced networks have emerged. One app has resulted in operational improvements in emergency response following disasters. Another has catalyzed a small business with a commercial product called FitNet that analyzes high-quality video of individuals’ exercise routines to provide personalized and real-time feedback to improve their health.
Toward a Smart and Connected Future
The result is that secure, programmable networks and next-generation apps are making their way into schools, libraries, hospitals and homes in communities across the nation. Through the hard work of researchers, educators, entrepreneurs, and civic leaders alike, these technologies are giving rise to transformational approaches for conducting science and engineering broadly – and they are fostering game-changing innovation throughout the entire Internet ecosystem.
NSF continues to facilitate the involvement of citizens and community organizations in building and experimenting with multiple advanced networking applications addressing national priorities. We are especially interested in fostering efforts that support mechanisms and processes to rapidly share and scale up innovations by transferring applications shown to be useful in once city/region to other cities/regions.
Ultimately, a key goal is to support mechanisms that will enable cities and regions to develop a smart and connected national ecosystem supporting applications of advanced networking.
Beginning July 1, the new members will each serve three-year terms. The CCC Council is comprised of 20 members who have expertise in diverse areas of computing. They are instrumental in leading CCC’s visioning programs, which help create and enable visions for future computing research. Members serve staggered three-year terms that rotate every July.
The CCC, CRA and NSF thank those Council members whose terms end on June 30 for their exceptional dedication and service to the CCC and to the broader computing research community:
The CCC encourages participation from all members of the computing research community. Each fall, the CCC issues a call for proposals for visioning activities. Each spring, the CCC issues a call for nominations for Council members effective the following July. For more information, please visit the CCC website or contact Dr. Ann W. Drobnis, CCC Director, at email@example.com.
Full Bios of New CCC Council Members
Cynthia Dwork is known for her research placing privacy-preserving data analysis on a mathematically rigorous foundation, including the co-invention of differential privacy, a strong privacy guarantee frequently permitting highly accurate data analysis. She was elected as a Fellow of the American Academy of Arts and Sciences (AAAS) in 2008, as a member of the National Academy of Engineering in 2008, and as a member of the National Academy of Sciences in 2014. She received the Dijkstra Prize in 2007 for her work on consensus problems together with Nancy Lynch and Larry Stockmeyer. Dwork received her B.S.E. from Princeton University in 1979, graduating Cum Laude, and receiving the Charles Ira Young Award for Excellence in Independent Research. Dwork received her Ph.D. from Cornell University in 1983. For additional information visit: http://research.microsoft.com/en-us/people/dwork/.
Kevin Fu is Associate Professor of Electrical Engineering and Computer Science at the University of Michigan where he directs the Archimedes Center for Medical Device Security and the Security and Privacy Research Group. His research investigates how to achieve trustworthy computing on embedded devices with application to health care, commerce, and communication. His participation in the provocative 2008 research paper analyzing the security of a pacemaker/defibrillator led to a watershed moment in cybersecurity for medical device manufacturing and regulatory science. Prof. Fu received his Ph.D. in EECS from MIT where his doctoral research pertained to secure storage and web authentication. Fu received a Sloan Research Fellowship, NSF CAREER award, Fed100 Award, and best paper awards from various academic silos of computing. The research is featured in critical articles by the NYT, WSJ, and NPR. Kevin was named MIT Technology Review TR35 Innovator of the Year for work on medical device security. Kevin has testified in Congress on health matters and has written commissioned work for the Institute of Medicine of the National Academies. He served as a visiting scientist at the Food & Drug Administration, the Beth Israel Deaconess Medical Center of Harvard Medical School, Microsoft Research, and MIT CSAIL. Previous employers include Bellcore, Cisco Systems, HP Labs, and Holland Community Hospital. He is a member of the ACM Committee on Computers and Public Policy and the NIST Information Security and Privacy Advisory Board. He is a principal investigator of Trustworthy Health & Wellness. Prior to joining Michigan, he served on the faculty at UMass Amherst. Kevin also holds a certificate of achievement in artisanal bread making from the French Culinary Institute. For more information visit: https://web.eecs.umich.edu/~kevinfu/.
Daniel P. Lopresti
Daniel Lopresti received his bachelor's degree from Dartmouth in 1982 and his Ph.D. in computer science from Princeton in 1987. After completing his doctorate, he joined the Department of Computer Science at Brown and taught courses ranging from VLSI design to computational aspects of molecular biology and conducted research in parallel computing and VLSI CAD. He went on to help found the Matsushita Information Technology Laboratory in Princeton, and later also served on the research staff at Bell Labs where his work turned to document analysis, handwriting recognition, and biometric security.
In 2003, Dr. Lopresti joined the Department of Computer Science and Engineering at Lehigh where his research examines fundamental algorithmic and systems-related questions in pattern recognition, bioinformatics, and security. Dr. Lopresti is director of the Lehigh Pattern Recognition Research (PatRec) Lab. On July 1, 2009, he became Chair of the Department of Computer Science and Engineering. Effective July 1, 2014, he assumed the role of Interim Dean of the P. C. Rossin College of Engineering and Applied Science at Lehigh. For additional information visit: http://www.cse.lehigh.edu/~lopresti/.
Shwetak N. Patel is the Washington Research Foundation Entrepreneurship Endowed Professor in Computer Science and Engineering and Electrical Engineering at the University of Washington, where he directs his research group, the Ubicomp Lab. His research interests are in the areas of Human-Computer Interaction, Ubiquitous Computing, Sensor-enabled Embedded Systems, and User Interface Software and Technology. He is particularly interested in developing new sensing technologies with a particular emphasis on energy monitoring and health applications for the home.
Dr. Patel was a founder of Zensi, Inc., a residential energy monitoring company, which was acquired by Belkin, Inc in 2010. He is also a co-founder of SNUPI Technologies, a low-power wireless sensor company. He received his Ph.D. in Computer Science from the Georgia Institute of Technology in 2008 and B.S. in Computer Science in 2003. Dr. Patel is a recipient of a MacArthur Fellowship (2011), Microsoft Research Faculty Fellowship (2011), Sloan Fellowship (2012), TR-35 Award (2009), World Economic Forum Young Global Scientist Award (2013), and an NSF Career Award (2013). He was also was named top innovator of the year by Seattle Business Magazine and Newsmaker of the year by Seattle Business Journal in 2011. His past work was also honored by the New York Times as a top technology of the year in 2005. For more information visit: http://abstract.cs.washington.edu/~shwetak/.
Katherine Yelick is a Professor of Electrical Engineering and Computer Sciences at the University of California at Berkeley and is also the Associate Laboratory Director for Computing Sciences at Lawrence Berkeley National Laboratory. She is the co-author of two books and more than 100 refereed technical papers on parallel languages, compilers, algorithms, libraries, architecture, and storage. She co-invented the UPC and Titanium languages and demonstrated their applicability across architectures through the use of novel runtime and compilation methods. She also co-developed techniques for self-tuning numerical libraries, including the first self-tuned library for sparse matrix kernels which automatically adapts the code to properties of the matrix structure and machine. Her work includes performance analysis and modeling as well as optimization techniques for memory hierarchies, multicore processors, communication libraries, and processor accelerators. She has worked with interdisciplinary teams on application scaling, and her own applications work includes parallelization of a model for blood flow in the heart. She earned her Ph.D. in Electrical Engineering and Computer Science from MIT and has been a professor of Electrical Engineering and Computer Sciences at UC Berkeley since 1991 with a joint research appointment at Berkeley Lab since 1996. She has received multiple research and teaching awards and is a member of the California Council on Science and Technology and a member of the National Academies committee on Sustaining Growth in Computing Performance. For more information visit: http://www.cs.berkeley.edu/~yelick/.
By Susanne Hambrusch, Purdue University and Mark Guzdial, Georgia Institute of Technology
The 2014 NSF CAREER competition in the Computer and Information Sciences and Engineering (CISE) directorate for the first time actively sought proposals in computing education research. The area of interest was closely aligned with the computing education research goals stated in its CE21 solicitation (NSF 12-609) which solicited proposals developing a research base for computing education: “Projects may conduct basic research on the teaching and learning of computational competencies in face-to-face or online settings; they may design, develop, test, validate, and refine materials, measurement tools, and methods for teaching in specific contexts; and/or they may implement promising small-scale interventions in order to study their efficacy with particular groups.” In March 2015 CISE announced two education research CAREER awardees, Kristy Boyer and R. Benjamin Shapiro. In the coming CAREER cycle, CISE is again inviting computing education research proposals. The topics of interest are highlighted in the STEM+C solicitation (NSF 15-537). Of special interest for CAREER proposals is the track focused on Computing Education Knowledge and Capacity Building.
This article briefly describes the proposed research in the two new CAREER awards. These two awards represent a new area of exploration for CISE. Computing education research offers new opportunities for computer science departments and schools, and we also describe some of them.
Kristy Elizabeth Boyer is an Assistant Professor of Computer Science at North Carolina State University. Her research focuses on how to support learning with natural language dialogue and intelligent systems. Her interest in computer science education research focuses on collaborative learning and on how machine learning can help us understand social, cognitive, and affective phenomena in human interactions. She received a Ph.D. in Computer Science from North Carolina State University in 2010. She holds an undergraduate degree in Mathematics and Computer Science from Valdosta State University and an M.S. in Applied Statistics from the Georgia Institute of Technology. Kristy was the recipient of a 2007 NSF Graduate Research Fellowship award.
Kristy Boyer’s CAREER project is titled “CS-CLIMATE: Collaborative Learning for Identity, Motivation, and Technology Engagement.” A rich body of evidence suggests that collaborative learning holds many benefits for computer science students, yet there is growing recognition that neither collaborative learning itself, nor the innovative curricula in which it may be situated, are “magic bullets” capable of single-handedly broadening the participation of students belonging to underrepresented groups. In contrast to being a one-size-fits-all solution, collaborative learning is highly dependent upon characteristics of the collaborators and on fine-grained interactions.
The proposed research will explore the fine-grained facets of collaborative dialogue known to be particularly effective for diverse computer science learners and build theoretically informed models that capture collaborative dialogue and problem solving phenomena associated with learning, identity development, motivation, and engagement. The project will leverage a learning environment built by the PI to support remote collaboration with textual natural language dialogue, synchronized code editing, and integrated repository control. It will implement and evaluate evidence-based pedagogical support for fostering effective collaborative dialogue by extracting a set of evidence-based pedagogical strategies for fostering effective collaborative dialogue tailored to student characteristics. Pedagogical support is expected to significantly improve learning, sense of identity, motivation, and continued engagement for students overall, and for women and African American students in particular. The research will draw upon collaborative learning data from computer science students at North Carolina State University, Meredith College, and Florida A&M University.
Benjamin Shapiro is the McDonnell Family Assistant Professor of Engineering Education and an Assistant Professor in the departments of Computer Science and Education at Tufts University. He received his Ph.D. in Learning Sciences from Northwestern University in 2009 and was a postdoctoral fellow at the University of Wisconsin-Madison. He holds an undergraduate degree in Independent Studies in Symbolic Systems (Computer Science & Cognitive Science) from the University of California, San Diego. His research focuses on the design of playful and constructionist learning environments. He studies how engineering computational systems can help learners to further their personal interests. To do so, he creates new technologies for learning and investigates how people, including students and teachers, use them to learn together.
Ben Shapiro’s CAREER project is titled “Constructing Modern and Inclusive Trajectories for Computer Science Learning.” His research will explore how youth building distributed cyber-physical systems offers possibilities of broadening participation and producing new theoretical and practical insights into the development of computational thinking.
Using data from middle and high school students solving problems by building networks of devices and mobile applications that communicate with each other, the project will develop new empirically-supported theories of the development of student thinking about distributed computing, as well as new tools to enable that development. Underrepresented minority youth will be partners in the co-design of the tools and supporting curriculum and the effects of their participation on interest, self-efficacy, and projective identity within computer science will be evaluated. A learning environment will be constructed to support youths' transitions from using beginner-specific programming environments (e.g., Scratch) into techniques and tools that are commonly found in university-level computer science education and in industry and open-source community practice. The research will describe and assess the development of student thinking in these transitions.
Caption: Benjamin Shapiro and Kristy Boyer at the Computing Education for the 21st Century NSF PI Meeting.
Why computing education research is important to computer science. Undergraduate enrollments are at a record high level. University administrators are unsure whether this is another high in the CS enrollment cycle to be followed by a steep drop or whether this is the new status quo. A time of burgeoning enrollments may not seem like an obvious time to focus on research in computing education, but the reality is that computer science students are changing and computing education practices are needed. Increased class sizes make many faculty re-evaluate how to teach and how to assess learning at scale. While MOOCS courses had significant promise three years ago, completion rates have been disappointing. But MOOCS demonstrated a new approach and model for a scalable teaching method that could make novel use of continuously collected data on learning.
Faculty are teaching freshmen with increasingly diverse computing backgrounds, both in-person and in-MOOCs. We see an increasing number of non-majors are taking computing courses. We do not always know how to engage, motivate, and retain a diverse student body. We know surprisingly little about how students understand foundational concepts in computer science. We know even less about effective methods for teaching parallel and distributed computing concepts. The field of computing education research draws on other disciplinary-based education research (DBER) areas, like science, mathematics, and engineering education. The history of DBER fields tell us computer science education is different, with unique challenges.
The percentage of students from underrepresented groups in computing has changed little in the last decade. While many departments have outreach and recruiting events that manage to attract more students from underrepresented groups, the retention of those students is often a challenge. To engage more diverse students, departmental outreach activities increasingly engage the entire K-12 range. However, little is known about validated practices for the earlier ages.
The computing community has recently seen a number of new activities at the high school level. A new AP course called CS Principles has been developed in an NSF-funded effort between computer scientists, higher education and high school educators, and the College Board. The CS Principles course is currently piloted in hundreds of schools across the country. The course will “introduce students to creative aspects of programming, using abstractions and algorithms, working with large data sets, understandings of the Internet and issues of cybersecurity, and impacts of computing that affect different populations.” The course was designed to be engaging and inspiring for all students. With only 19% of high school students currently taking a single CS course, the CS Principles course aims to attract a more diverse student to computing. The first AP Computer Science Principles Exam is taking place in May 2017.
Computer science has the unique position of teaching the medium that we can also use to teach. Can computing revolutionize how we teach and how students learn computer science? We can create specialized development environments tuned to the learning needs of our students. As we teach with MOOCs and other new media, we are challenged to explore the advantages of these platforms. Are there effective and scalable methods available to instructors for automated assessment of learning? Do we have validated data and evidence driven analysis tools for student learning? Many of these questions are at the heart of computing education research.
The research proposed by the two exceptional CS education researchers in their CAREER awards highlights a number of characteristics of computing education research. First, the field of computing education research is interdisciplinary. While grounded in computer science, the research area draws expertise and knowledge from learning sciences, education research, behavior and social scientists, psychology and sociology. We expect successful researchers to have a strong background in computer science as well as a clear understanding of the techniques and tools of education and learning science research. Many promising computing education research projects explore the application of the methods used in computer science research on itself. Common are methods in the areas of machine learning, big data/analytics, delivery of software as a service, human computer interaction. Computing education research has a number of similarities with HCI research. HCI research relies on the computing discipline to develop new methods and techniques and it also uses methods from the social sciences for assessment and validation.
Computing education research topics include understanding how students with different backgrounds learn computing, understanding how to effectively teach computing to audiences with different interests and backgrounds, and how to make use of personalized learning approaches and validated learning progressions. Research focuses on inventing, developing, assessing and validating ways to teach computing at all levels, from elementary school to a scientist. Computing education research aims to transform how learning happens in the traditional classroom as well as on-line. Based on new understandings on how learning happens, new systems and tools supporting teaching at scale are developed and assessed. Computing education research also includes effective teacher preparation and training, both as pre-service and in-service.
Numerous funding opportunities for computing education research exist. At NSF, the CISE and the EHR directorates both offer solicitations that can support work in computing education research. The most recent STEM + Computing Partnerships (STEM+C) solicitation is such an example. Other opportunities include Science of Learning (NSF 15-532), Cultivating Cultures for Ethical STEM (CCE STEM, NSF 15-528), and Cyberlearning and Future Learning Technologies (NSF 14-526). The Department of Education is also a source for computing education research funding. Funding opportunities from foundations include the MacArthur Foundation, Gates Foundation, and Sloan Foundation. Companies with a critical workforce computing needs including Microsoft Research, Google, Intel, IBM have various programs and opportunities for support.
In the long run, computing education research will strengthen our field and it has the potential to broaden participation of underrepresented groups. Understanding how students think about computing and how we can improve their learning will have impacts in how we design the interface between humans and computers. Teachers will have access to validated and established pedagogical instruments and assessment tools. The training of K-12 computer science teachers will follow established guidelines, principles, and methods. Departments with faculty interested in computing education research or interested in hiring in this area, will realize that a number of models for successful appointments and collaborations exist. Faculty often have joint appointments, especially in CS departments that are not in a College/School of Computing environment. Departments with computing education research as focus will train graduate students in the field of computing education research and will develop curricula. We expect graduates to get hired by CS/I/CE departments with active computing education research, Education departments, teaching focused institutions, providers of on-line and MOOCS courses, high schools, and organizations like Code.org, the Computer Science Teachers Association (CSTA), the National Center for Women in Information Technology (NCWIT), or Project Lead the Way (PLTW). This is an exciting time to get involved in computing education research, a research area shaped by the advances in our field which will help shape the future of our field.
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