In early 2015, CRA created a committee to investigate increasing enrollments. As part of this effort, an institutional subgroup of this committee developed and distributed a CRA Enrollment Survey to better understand enrollment trends and their impact. A report Generation CS: CS Undergraduate Enrollments Surge Since 2006 presents and analyzes the data collected. The report will be available from the CRA website soon, and comments will be supported for those interested in discussing the report and its implications.
Computing Research News
Published: February 2017, Issue: Vol. 29/No.2, Download as PDF
Archive of articles published in the Current Issue issue.
The Education Committee of the Computing Research Association (CRA-E) is proud to announce three winners of the CRA-E Undergraduate Research Faculty Mentoring Award. Congratulations to the 2017 award recipients: Margaret Burnett from Oregon State University, Nayda Santiago from the University of Puerto Rico, Mayaguez Campus, and Margo Seltzer from Harvard University.
The Computing Research Association’s Education Committee (CRA-E) is pleased to announce the “Undergraduate Research Listing Service.” This free service is now available for faculty and other researchers to advertise undergraduate research opportunities and for undergraduates to find such opportunities. The site can be found here: http://conquer.cra.org/research-opportunities.
This site can be used to advertise individual summer positions, research programs, and any other opportunities for undergraduates to engage in research in the computing field. If you have a research opportunity available, please post it here: http://conquer.cra.org/post-a-research-opportunity.
CRA-WExpanding the Pipeline
Several years ago, after devoting many years to the study of the gender gap in STEM fields using nationwide data on first-year college students, it became clear to me that the study of STEM in the “aggregate” was no longer a realistic or useful way to examine women’s progress in these fields. Not only does women’s representation in undergraduate STEM vary dramatically by field (constituting as many as 58% of bachelor’s degree earners in the biological sciences and only 18% of degree earners in computer science and engineering [NCES, 2015]), but STEM fields are distinct from each other in many other ways, including curriculum, career paths, and the types of students they attract.
My research revolves around tracking and understanding users’ emotional states and leveraging that information as additional context for the design of emotionally sentient systems. Some of the systems we have built have been designed for a user’s own personal reflection. Our first application, AffectAura, provided users with their own behavior patterns over time, such as what they were doing, where they were, who they were with and how they felt. This information could be used to make personal decisions about behavior change—if certain activities usually result in your feeling good or bad, perhaps you want to increase or decrease those behaviors.
Since I started graduate school in 1997, I have considered myself a member of the programming languages research community — and I continue to attend and publish in the annual conferences of this vibrant computing subfield. But over the last 5-10 years, I have also found myself increasingly passionate about opportunities for computing researchers to focus on ways to influence computing education beyond, for those of us who are academics, our own classrooms and independent studies. Let me share some of the projects I have enjoyed (seriously!) and others I wish I had more time to pursue.
CERP recently extracted Web data to observe the career progression of women who had participated in the CRA-W’s 2008 or 2009 Career Mentoring Workshops (CMWs) compared to a sample of women who had never participated in CMWs. We obtained the comparison sample from a population of women who earned their Ph.D.s in computer science during the same time period as the participants. We collected current career information including job titles (e.g., associate professor) and job setting (e.g., academia vs. industry/labs) for both groups. We then categorized job titles as entry level (e.g., assistant professor, software engineer), mid level (e.g., associate professor, senior engineer), and senior level (e.g., professor, principal program manager), collapsed across job setting. To test for a systematic difference in job rankings between workshop participants and the comparison group, we ran a 2 (Group) x 3 (Job Title Rank) Chi-squared test and found a statistically significant difference in rankings across the two groups, χ2 (2, N = 181) = 8.46, p < 0.05. Specifically, CMW participants were less likely than non-participants to be in an entry level position, p < .05, and more likely to be in a senior level position than non-participants, p < .05.
CRA wishes to thank the computing departments who distributed CERP’s Data Buddies survey during the fall of 2016! The collective effort of these departments provides data for CERP’s research on students’ experiences and successes in computing degree programs.
In 2009, the CCC published a report, A Roadmap for US Robotics, From Internet to Robotics (a.k.a. the Robotics Roadmap), which explored the capacity of robotics to act as a key economic enabler, specifically in the areas of manufacturing, healthcare, and the service industry, 5, 10, and 15 years into the future.
An updated version of the Robotics Roadmap was released in November 2016; it expands on the topics discussed in the 2009 roadmap and addresses the areas of public safety, earth science, and workforce development. It also emphasizes robotics as a validated STEM education and career recruitment tool and calls for additional research in this promising area. This direction is particularly important as it not only aids in training the 21st century workforce, but also helps to address concerns about job loss to automation.
The past year has seen an incredible amount of ink spilled on a singular topic: what does the future of AI portend for the nation and the world? Will AI technologies enhance productivity and quality of life, or will it disrupt labor markets and accelerate growth in income disparity and wealth concentration? Will AI research be used for the common good, or will it be “bought up” by the private sector and exploited for commercial gain? Is this another AI research bubble, or are we truly on the verge of a paradigm shift that could change the nature of computing itself?