From July 17-19, the Computing Research Association (CRA) held its biennial conference at Snowbird, with more than 300 people in attendance. Every two years, the chairs of computing and information departments from across the country, as well as the leaders of government and industrial laboratories, gather in Snowbird, Utah, to network and discuss common issues concerning the future of the field.
Computing Research News
Published: August 2016, Issue: Vol. 28/No.7, Download as PDF
Archive of articles published in the August 2016, Vol. 28/No.7 issue.
In 2015, CERP asked 1,335 students enrolled in Ph.D. programs to report their interest in a variety of computing professions. The distribution of students’ year in their program was as follows: 22% first year, 21% second year, 13% third year, 12% fourth year, 10% fifth year, 10% sixth year or greater, and 12% unspecified. As seen in the graphic above, students were most interested in pursuing a computing research job in industry, followed by tenure track computing faculty at a research university, computing researcher in a government lab, and entrepreneurial work in computing. Students were least interested in becoming a middle or high school computing teacher.
On Tuesday, July 5, the CRA Government Affairs Office welcomed the 2016 class of Eben Tisdale Public Policy Fellows to the CRA Washington, D.C. office. These fellows, who are undergraduate students, spent the summer at high-tech companies, firms, or trade associations in Washington, learning the intricacies of technology policy. Additionally, they took two classes worth six credits at George Mason University, and attended briefings at institutions such as the U.S. Capitol, U.S. Department of State, World Bank, and Federal Reserve. The fellows visited the office to attend a presentation by Brian Mosley, policy analyst in the CRA Office of Government Affairs, that covered the policy concerns and issues the association works on and attempts to influence at the federal level.
CRA-WExpanding the Pipeline
The Latinas in Computing (LiC) community was established with the help of The Anita Borg Institute for Women in Technology (ABI) at the 2006 Grace Hopper Celebration of Women in Computing (GHC). Recognizing the status of Latinas as a double minority in North America, this community defines and implements strategies to improve the participation of the current and next generations of Latinas in technology. These dual strategies complement the work done by the Coalition to Diversify Computing (CDC) that focused on the recruitment and retention of minority students in computing-based fields in North America, and the work done by the Computing Research Association’s Committee on the Status of Women in Computing Research (CRA-W) to grow the research pipeline of women in computing. National Science Foundation (NSF) data shows Hispanic or Latino enrollment increased from 7.2% in 2002 to 9.9% in 2012, but the hiring of underrepresented minorities seems to be “stuck in neutral.”
July 1st starts a new term at CCC!
The new Computing Community Consortium (CCC) leadership, Elizabeth Mynatt and Mark Hill will assume their roles as Chair and Vice Chair respectively for two-years, while Greg Hager is stepping down after two years as Chair. The other members of the CCC Executive Committee include Jennifer Rexford, Princeton University, and Ben Zorn, Microsoft Research.
In addition to a new Exec Committee, four new CCC Council members will us join us for the start of their three-year terms, Sampath Kannan, University of Pennsylvania, Maja Matarić, University of Southern California, Nina Mishra, Amazon Research, and Holly Rushmeier, Yale University.
The Computing Community Consortium (CCC) will be sponsoring a visioning activity on Sociotechnical Cybersecurity. As a part of this effort, the workshop organizing committee has released a call for white papers in order to both assist us in organizing the workshop and in selecting attendees. Authors of informative and well-crafted white papers may be invited to the Sociotechnical Cybersecurity workshop.
Computing has become a powerful tool for productivity and connectivity. It powers companies, it fuels scientific research, and it delivers entertainment and social engagement for billions of people.
Could research-based innovations in computing also become a catalyst for addressing compelling societal problems?
To explore this question, the Computing Community Consortium (CCC) organized a two-day symposium titled Computing Research: Addressing National Priorities and Societal Needs. This meeting brought together more than 130 in-person participants and more than 1,000 online viewers to raise the visibility of work that connects innovative computing research to major societal needs. The seven panels, two plenaries, and an early-career poster session, all of which are now available on the CCC website, presented numerous ideas that could reshape our world.
On Monday, August 15, the National Academies of Sciences, Engineering, and Medicine will hold a public Workshop on the Growth of Computer Science Undergraduate Enrollments.
This workshop is being convened as an information-gathering session of the Academies’ Study on the Growth of Computer Science Undergraduate Enrollments sponsored by the National Science Foundation and co-chaired by Susanne Hambrusch, professor of computer science at Purdue University and CRA Board Vice-Chair, and Jared Cohon, president emeritus of Carnegie Mellon University.
Congratulations to David Patterson – 2016 Tapia Award Winner
Carnegie Corporation of New York Honors Farnam Jahanian
Aims and Scope
Special Issue on Signal Processing and Machine Learning for Education and Human Learning at Scale
Aims and Scope
The surge in popularity of Massive Open Online Courses (MOOCs) and other online and blended learning platforms has demonstrated the potential of the Internet for scaling education. While advances in technology have enabled content delivery to massive numbers of students, these platforms remain limited in their ability to provide an effective learning experience for each individual.
Recent advances in machine learning and signal processing offer promising avenues to move beyond this “one size fits all” educational approach. The key is that today’s learning technology platforms can capture big data about learners as they proceed through courses. Examples of learning data include performance on homeworks and exams, click actions made while watching lecture videos or interacting with simulations, the social learning networks formed among the students, and the content posted on discussion forums. Going even further, prototype platforms are being built that use cameras and other sensors to continuously monitor students’ affect and engagement. The large volumes of empirical learning data being collected present novel opportunities to study the process of student learning, to design systems that improve learning at scale by closing the learning feedback loop.