Posts tagged ‘undergraduate’
The below note was posted by Jeff Forbes to the SIGCSE Members list. What an interesting idea — funding to change a whole department!
NSF has posted a new solicitation for proposals, IUSE/Professional Formation of Engineers: Revolutionizing Engineering Departments (RED).
RED focuses on efforts to effect significant, systemic departmental change that impacts undergraduate student success in their formation as computer scientists or engineers. This program is particularly interested in efforts that address the middle two years of the four year undergraduate experience, during which students receive the bulk of their formal technical preparation. RED proposals need to engage the entire department, and the effort must be led by the chair/head of the department.
See http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=505105 for more information.
Note: “Engineering departments” in the solicitation refers to both engineering and computer science departments, regardless of whether those departments are in a school of Engineering.
Letters of Intent are due October 28, 2014.
At our ECEP meeting after the NCWIT summit earlier this summer, Cheryl Kiras presented some data on community college enrollment that was really eye-opening for me.
This is from a fact sheet American Association of Community Colleges (available here). This is describing the percentage of all undergraduates in a group that are enrolled in community colleges. 56% of all Hispanic undergraduates were enrolled in community colleges in Fall 2012. 48% of all Black students, and 59% of all Native American students. Wow — that really supports the argument that if we want to broadening participation in University level computing, we need to improve the transfer and recruitment paths from Community Colleges into Universities. We can make it better at the University (and we should), but that’s only reaching half the students.
2nd Annual ACM NDC Study
Of Non-Doctoral Granting Departments in Computing
Please contact ACM Education Manager Yan Timanovsky (firstname.lastname@example.org) ASAP! Deadline is March 16 (extensions possible upon request).
• As an annual survey, NDC produces timely data on enrollment, degree production, student body composition, and faculty salaries/demographics that can benchmark your institution/program(s) and invite useful conversations with your faculty and administration.
• Those who qualify for and complete NDC in its entirety will be entered in a drawing to receive one of (3) unrestricted grants of $2,500 toward your department’s discretionary fund.
What would you accept as evidence in support of this claim? I don’t see it where I’m at, but I’m willing to believe that my experience is biased and limited. How could we test this claim?
The president of the Association of American Universities said on Monday that public research institutions were once again moving forward, thanks to a renewed focus on undergraduate education and a willingness to “be extremely aggressive” in taking advantage of new financing opportunities.
Hunter R. Rawlings III said that, for the first time in his career, senior faculty members were spending time and effort on teaching. “Our main job at universities is educating students,” he said during a panel discussion here at this week’s annual meeting of the Association of Public and Land-Grant Universities. “We forgot about that for a while. But now it has hit us with full force because tuition increases have caused the public to be angry, or skeptical at least, about the quality and the value proposition that they’re getting.”
It’s great to hold this woman up as a role model, but isn’t it a shame that she is so unusual. Only girl in AP CS? One of only five women in CS at Iowa State?
Cassidy Williams was the only girl in her AP computer science class at Downers Grove South High School.
Now, she is one of only five women majoring in computer science, along with 57 men, in the 2014 graduating class at Iowa State University.
It’s a trend the 21-year-old Downers Grove native hopes to help change for future girls studying computer science.
“If we don’t have women in computer science, we’re only seeing half the picture,” Cassidy said. “We need to have women in the computing workforce to bring their diverse perspectives to a development team, thus creating the best products.”
The first ACM study of non-doctoral computing (NDC) departments has just released its report (to contrast with the Taulbee Survey which is focused on doctoral-granting department). Below is the coverage in the Huffington Post.
The study shows that enrollment in undergraduate computer science (CS) programs within these departments increased 11 percent between 2011-12 and 2012-13. Computer science bachelor’s degree production in these departments is expected to increase nearly 14 percent during this period. Other areas of computing, such as software engineering and information technology, also are experiencing growth according to the report. Only in the information systems area is there no real evidence of growth. Master’s degree production in the NDC departments also generally is increasing, adding to the skilled employment base in these key technology areas.
Once upon a time, all computer scientists understood how floating point numbers were represented in binary. Numerical methods was an important part of every computing curriculum. I know few undergraduate programs that require numerical methods today.
Results like the below make me think about what else we teach that will one day become passé, irrelevant, or automatized. The second result is particularly striking. If descriptions from programming competitions can lead to automatic program generation, what does that imply about what we’re testing in programming competitions — and why?
The researchers’ recent papers demonstrate both approaches. In work presented in June at the annual Conference of the North American Chapter of the Association for Computational Linguistics, Barzilay and graduate student Nate Kushman used examples harvested from the Web to train a computer system to convert natural-language descriptions into so-called “regular expressions”: combinations of symbols that enable file searches that are far more flexible than the standard search functions available in desktop software.
In a paper being presented at the Association for Computational Linguistics’ annual conference in August, Barzilay and another of her graduate students, Tao Lei, team up with professor of electrical engineering and computer science Martin Rinard and his graduate student Fan Long to describe a system that automatically learned how to handle data stored in different file formats, based on specifications prepared for a popular programming competition.
Hot topic these days, like the debate in the UK. Workshop to be held in conjunction with ASEE in Atlanta June 26-28.
A primary objective of undergraduate computing and engineering programs is to prepare graduates for professional practice. New graduates often find themselves working on large, complex systems that require dozens (or hundreds) of people and months (or years) to complete. Unfortunately, graduates often feel ill-prepared to work on systems of such size and complexity. Educators find it extremely difficult to provide a realistic experience with such systems in an academic environment.
Engineering and computing curricula primarily rely on a senior design course (one or two semesters in length) to teach professional practice. Students are typically organized in project teams to develop a realistic product or service, in which the students engage in various professional practices: such as project management, requirements analysis and modeling, highlevel and detailed design, implementation or simulation, quality assurance, project reporting, and use of appropriate engineering tools and methods.
Relates to the issue of when an employee needs college, and when they don’t. For Cybersecurity, they do. Relates to the growing needs in cybersecurity in the UK and in the US.
Too many (current) educational programs stress only the technology — and many others include significant technology training components — because of pressure by outside entities, rather than a full spectrum of education and skills. We have a real shortage of people who have any significant insight into the scope of application of policy, management, law, economics, psychology and the like to cybersecurity, although arguably, those are some of the problems most obvious to those who have the long view. (BTW, that is why CERIAS was founded 15 years including faculty in nearly 20 academic departments: “cybersecurity” is not solely a technology issue; this has been recognized by several other universities that are treating it more holistically.) These other skill areas often require deeper education and repetition of exercises involving abstract thought. It seems that not as many people are naturally capable of mastering these skills. The primary means we use to designate mastery is through postsecondary degrees, although their exact meaning does vary based on the granting institution.
Shared by Leigh Ann Sudol-DeLyser (Visiting Scholar, New York University) with the SIGCSE list.
I would like to announce the First Workshop on AI-Supported Education for Computer Science to be held at the Artificial Intelligence in Education conference this summer in Memphis and invite the submission of papers from the SIGCSE community. Please see the website at: https://sites.google.com/site/aiedcs2013/ Submissions are due by April 12, 2013.
Designing and deploying AI techniques within computer science learning environments presents numerous important challenges. First, computer science focuses largely on problem solving skills in a domain with an infinitely large problem space. Modeling the possible problem solving strategies of experts and novices requires techniques that represent a large and complex solution space and address many types of unique but correct solutions to problems. Additionally, with current approaches to intelligent learning environments for computer science, problems that are provided by AI-supported educational tools are often difficult to generalize to new contexts. The need is great for advances that address these challenging research problems. Finally, there is growing need to support affective and motivational aspects of computer science learning, to address widespread attrition of students from the discipline. Addressing these problems as a research community, AIED researchers are poised to make great strides in building intelligent, highly effective AI-supported learning environments and educational tools for computer science and information technology.
Topics of Interest:
- Student modeling for computer science learning
- Adaptation and personalization within computer science learning environments
- AI-supported tools that support teachers or instructors of computer science
- Intelligent support for pair programming or collaborative computer science problem solving
- Automatic question generation or programming problem generation techniques
- Affective and motivational concerns related to computer science learning
- Automatic computational artifact analysis or goal/plan recognition to support adaptive feedback or automated assessment
- Discourse and dialogue research related to classroom, online, collaborative, or one-on-one learning of computer science
- Online or distributed learning environments for computer science
At the ACM Education Council meeting this last weekend, I heard about changes in the accreditation criteria being considered for computing disciplines (e.g., Computer Science, Information Systems, Information Technology). The committee has asked for feedback on several issues that they’re considering, e.g., how much mathematics do students really need in computing?
That question, in particular, is one that I’m reading about in The Computer Boys Take Over by Nathan Ensmenger. Ensmenger tells the story of how mathematics got associated with preparation of programmers (not computer scientists). Mathematics showed up on the early aptitude tests that industry created as a way of figuring out who might be a good programmer. But Ensmenger points out that mathematic ability only correlated with performance in academic courses, and did not correlated with performance as a programmer. It’s not really clear how much math is really useful (let alone necessary) for being a programming. Mathematics got associated with programming decades ago, and it remains there today.
The Committee is inviting feedback on this and other issues that they’re considering:
This survey was developed by a joint committee from CSAB and the ABET Computing Accreditation Commission, and is designed to obtain feedback on potential changes on the ABET Computing Accreditation Criteria. We are looking for opinions about some of the existing ideas under discussion for change, as well as other input regarding opportunities to improve the existing criteria.
Respondents to the survey may be computing education stakeholders in any computing sub discipline, including computer science, information systems, information technology, and many others. Stakeholders may include professionals in the discipline, educators, and/or employers of graduates from computing degree programs.
The survey may be completed online: https://www.surveymonkey.com/s/caccriteria2013.
Please send inquiries to email@example.com.
Thank you for your participation.
MUST READ: Hacking at Education: TED, Technology Entrepreneurship, Uncollege, and the Hole in the Wall
Audrey Watters has an insightful essay that show how the “Hack Education” and TED movements misunderstand school. Public school is not better than learning on your own. Public school is about making sure that everyone has the opportunity to learn. I believe that the issues are the same for MOOCs, which tend to draw a well-educated, majority-class, and male audience. I highly recommend reading her entire essay linked below.
“I’m the first MacCaw not to go to Cambridge,” says one of the informant. This and a myriad of other utterances are rather mind-boggling markers of privilege, markers that Hacking Your Education fails to examine and that the book seems extraordinarily unaware of.
One hack it offers for the young uncollege-er: “take people out for coffee” — budget $150 a month to do so. Another hack: “go to conferences.” Sneak in. “Hardly anyone will notice.” Another hack: “buy an airplane ticket.” “You can go anywhere in the world for $1500.” “Collect frequent flyer points.” Too bad if you’re big or black or brown or a non-native English speaker or the working poor or a single mom. Just practice your posture and your grammar and your email introductions, and you’re golden.
A nice upbeat piece! I hadn’t talked about the Code.org video here — I recommend checking it out. (I will point out that Chris Bosh who “coded in college” according to the video, was at Georgia Tech for his one year in college.)
America’s elite institutions came out in full force for computer science education. First, the House of Representatives voted to update its traditional students arts competition to include a nationwide mobile apps competition. Then, to top off the day, the nation’s leading geeks, from Mark Zuckerberg to Bill Gates, helped launch a national nonprofit to encourage young programmers.
Posted by Mehran Sahami. There are several sessions for feedback on the draft and to provide exemplars for the curriculum section.
Just in time for SIGCSE, we are happy to announce the availability of the
ACM/IEEE-CS Computer Science Curricula 2013 (CS2013) – Ironman v1.0 draft.
The draft is available at the CS2013 website (http://cs2013.org) or directly
The Ironman v1.0 draft contains a revision of the CS2013 Body of Knowledge,
based on comments from the previously released CS2013 Strawman and Ironman
v0.8 drafts. The Ironman v1.0 draft also includes additional new chapters
as well as over 50 course exemplars, showing how the CS2013 Body of
Knowledge may be covered in a variety of actual fielded courses.
** SIGCSE-13 SPECIAL SESSION: CS2013: Reviewing the Ironman Report **
A special session, entitled “ACM/IEEE-CS Computer Science Curriculum 2013:
Reviewing the Ironman Report,” will be held at SIGCSE-13. This session will
give you an overview of the current state of the CS2013 curricular
guidelines and provide opportunities for discussion and feedback from the
community. The special session will be held on Thursday, March 7, 2013 from
10:45am to 12:00pm in Ballroom E.
** SIGCSE-13 SPECIAL SESSION: CS2013 EXEMPLAR-FEST **
Another SIGCSE-13 special session is the “CS 2013: Exemplar-Fest”. This
session will showcase submitted samples of CS2013 course/curriculum
exemplars and provide the opportunity to engage the community in the
development of additional course/curricular exemplars for CS2013. The
special session will be held on Friday, March 8, 2013 from 10:45am to
12:00pm in Ballroom F.
COMMENTING ON CS2013 IRONMAN v1.0 DRAFT
The Ironman v1.0 draft is the penultimate draft of the CS2013 curricular
guidelines. The final version of the CS2013 guidelines will be published in
Fall 2013. We welcome additional comments on the CS2013 Ironman draft from
the computing community. Information on how to comment on the draft is
available at the CS2013 website. Comments on the Ironman draft will be
addressed in the final released version of CS2013.
CALL FOR EXEMPLARS
The CS2013 Curriculum Steering Committee is continuing to seek exemplars of
courses and curricula from the broader community. This open process will
better connect the CS2013 Body of Knowledge to real, existing approaches
representing diverse and innovative ways to teach computer science. In
Computer Science terms, the topics and learning outcomes in the Body of
Knowledge represent a “specification”, whereas a curriculum is an
“implementation” and a course is part of a curriculum. Information on how
to contribute course/curriculum exemplars is available at the CS2013 website
(http://cs2013.org) or directly at:
Mehran Sahami and Steve Roach
Co-Chairs, CS2013 Steering Committee
CS2013 Steering Committee
Mehran Sahami, Chair (Stanford University)
Andrea Danyluk (Williams College)
Sally Fincher (University of Kent)
Kathleen Fisher (Tufts University)
Dan Grossman (University of Washington)
Beth Hawthorne (Union County College)
Randy Katz (UC Berkeley)
Rich LeBlanc (Seattle University)
Dave Reed (Creighton University)
Steve Roach, Chair (Univ. of Texas, El Paso)
Ernesto Cuadros-Vargas (Univ. Catolica San Pablo, Peru)
Ronald Dodge (US Military Academy)
Robert France (Colorado State University)
Amruth Kumar (Ramapo Coll. of New Jersey)
Brian Robinson (ABB Corporation)
Remzi Seker (Embry-Riddle Aeronautical Univ.)
Alfred Thompson (Microsoft)
The latest issue of Computing Research News has a report from CRA-E (their Education subcommittee) on where CS PhD’s come from. Research universities, institutions that stop at Masters degrees, four year colleges, or top liberal arts institutions? Turns out the answer is that the vast majority of CS PhD’s get their undergraduate degrees from research universities, but the sum of the PhD’s who get their undergraduate degrees from the top 25 liberal arts institutions is greater than any single research institution. There’s also evidence that the research universities produce better graduate students, using NSF fellowships as the quality metric. That was quite unexpected — I would have guessed that the four years and the liberal arts institutions would have played a much greater role.
In 2010, 1665 Ph.D.’s were awarded in computer science of which 714 went to domestic students. Approximately 71% of the domestic Ph.D.’s received their undergraduate degrees from research universities, 15% from master’s institutions, 11% from four-year colleges, and 4% from other colleges. These proportions have remained essentially unchanged since 2000 with all four types seeing similar increases since 2005.