Posts tagged ‘computing for everyone’
LaTiCE was announced to be in Saudi Arabia (see previous blog post), but it didn’t work out. I don’t know why. It will now be held in Hong Kong.
FIRST ANNOUNCEMENT AND CALL FOR PAPERS
Learning and Teaching in Computing and Engineering (LaTiCE 2017)
April 20-23, 2017
The Fifth International Conference on Learning and Teaching in Computing and Engineering (LaTiCE 2017) aims to create a platform towards sharing rigorous research and current practices being conducted in computing and engineering education. The previous four LaTiCE conferences have been successfully held in Macau (2013), Malaysia (2014), Taiwan (2015) and Mumbai (2016). The fifth LaTiCE conference will be held at the University of Hong Kong, from April 20th to 23rd, 2017.
LaTiCE 2017 is jointly organized by the University of Hong Kong, Hong Kong, and the Uppsala Computing Education Research Group (UpCERG), Uppsala University, Sweden. It is technically co-sponsored by the Special Technical Community for Education Research (STC Education), which is an IEEE Computer Society initiative to connect those interested in all forms of educational research and pedagogy in the field of computing and engineering.
The conference is preceded by a doctoral consortium on April 20th. The conference is a gathering for presentations of research papers, practice sharing papers, work-in-process papers, and display of posters and demos.
MAIN CONFERENCE THEMES
– Computer Science and Engineering Education research
– Secondary School Computer Science
– ICT in Education
– Computing and engineering education research, theories, and methodologies
– Cross-cultural aspects of computing and engineering education
– Educational technology, software, and tools
– Teaching innovations, best practices, experience sharing in computing and engineering education
– Course module design, proficiency assessment, and module cross-accreditation
– Improving student engagement in computing and engineering
– Collaborative learning in computing and engineering- team and project skills
– “Flipped” classrooms and active learning
– Work-integrated learning and project-based learning
Research papers (6-8 pages) present original, unpublished work relevant to the conference themes. Papers may be theoretical or based on empirical investigations. Papers are evaluated with respect to their theoretical contribution and the quality and relevance of the research.
Practice / Work-in-progress Papers
Practice / work-in-progress papers (3-5 pages) present original, unpublished practice sharing or work-in-progress work with a focus on innovative and valued practices within specific institutions. They can present preliminary results or raise issues of significance to the discipline.
Poster/demo (2 pages abstract) should present innovative ideas for work in the early stages related to research, teaching practice, or tools. Demonstration of tools should stress the methodology and can include some hands-on work for participants.
Papers should be submitted to the EasyChair review management system. All papers will undergo double-blind peer review.
Conference content will be submitted for inclusion into IEEE Xplore as well as other Abstracting and Indexing (A&I) databases. All papers should follow the IEEE Xplore Conference Publishing formatting guidelines.
Paper submission: January 15th, 2017
Notification of acceptance: February 15th, 2017
Camera-ready deadline: March 1st
Author registration deadline: March 1st
Doctoral consortium: April 20th
LaTiCE conference: April 21st-23rd
PROGRAMME COMMITTEE CO-CHAIRS
Roger Hadgraft, University of Technology, Sydney, Australia, Roger.Hadgraft@uts.edu.au
James Harland, RMIT University, Australia, email@example.com
Nick Black, brilliant GT alum and (now former) Google engineer, says it like he sees it. His critique of Google and their efforts to improving diversity extend to most of Silicon Valley. If you really want a diverse workforce, open offices where there’s diversity.
Nick’s analysis (and I encourage you to read the whole post below) talks about the density of middle class Black workers. He doesn’t consider where there are Black workers who know computing. Computing education is still pretty rare in the US. Let’s use AP CS exam-taking as a measure of where there is CS education. In Michigan last year, there were 19 Black AP CS exam-takers. 11 in Missouri. None in Mississippi. There are middle class Black families in these states. They may not be getting access to CS education.
Google talks endlessly about diversity, and spends millions of dollars on the cause. My NYC office lends its prodigiously expensive square feet to Black Girls Code. We attempt to hook the recruiting pipeline up to HBCUs. We tweet about social justice and blog about the very real problem of racial inequality in America. Noble endeavors, all. It’s too bad that they’re not taking place where black people actually, you know, live.
According to census.gov’s data as of 2016, Mountain View is 2% black. In 2010, the Bay Area Census Project recorded 1,468 blacks in MTV. I saw more black people than that crossing Peachtree Street today. census.gov reports, as of 2010, blacks making up 25.1% of NYC, 9.6% of Los Angeles, and 6.1% of famously liberal San Francisco. census.gov does not provide data for Dublin or Zürich, but we can make some reasonable assumptions about those other largest Google offices, n’est-ce pas?
And let’s be honest — I doubt much of that 25.1% of NYC is centered around Chelsea.
Atlanta’s a bit down from 67% in 1990, but 54% ain’t so bad.
At the ECEP Summit, I sat with the team from North Carolina as they were reviewing data that our evaluation team from Sagefox had assembled. It was fascinating to work with them as they reviewed their state data. I realized in a new way the difficult choices that a state has to make when deciding how to make progress towards the CS for All goal. In the discussion that follows, I don’t mean to critique North Carolina in any way — every state has similar strengths and weaknesses, and has to make difficult choices. I just spent time working with the North Carolina team, so I have their numbers at-hand.
North Carolina has 5,000 students taking CS in the state right now. That was higher than some of the other states in the room. I had been sitting with the Georgia state team, and knew that Georgia was unsure if we have even one full-time CS teacher in a public high school in the whole state. The North Carolina team knew for a fact that they had at least 10 full-time high school CS teachers.
Some of the other statistics that Sagefox had gathered:
- In 2015, the only 18% of Blacks in North Carolina who took the AP CS exam passed it. (It rose to 28% in 2016, but we didn’t have those results at the summit.) The overall pass rate for AP CS in North Carolina is over 40%.
- Only 68 teachers in the state took any kind of CS Professional Development (that Sagefox could track). There are 727 high schools in the state.
- Knowing that there are 727 high schools in the state, we can put the 5,000 high school students in CS in perspective. We know that there at 10 full-time CS teachers in North Carolina, each teaching six classes of 20 students each. That accounts for 1,200 of those 5,000. 3,800 students divided by 717 high schools, with class sizes typically at 20 students, suggests that not all high schools in North Carolina have any CS at all.
Given all of this, if you wanted to achieve CS for All, where would you make a strategic investment?
- Maybe you’d want to raise that Black student pass rate. North Carolina is 22% African-American. If you can improve quality for those students, you can make a huge impact on the state and make big steps towards broadening participation in computing.
- Maybe you’d want to work towards all high schools having a CS teacher. Each teacher is only going to reach at most 120 students (that’s full-time), but that would go a long way towards more equitable access to CS education in the state.
- Maybe you’d want to have more full-time CS teachers — not just one class, but more teachers who just teach CS for the maximum six courses a year. Then, you reach more students, and you create an incentive for more pre-service education and a pipeline for CS teachers, since then you’d have jobs for them.
The problem is that you can’t do all of these things. Each of these is expensive. You can really only go after one goal at a time. Which one first? It’s a hard choice, and we don’t have enough evidence to advise which is likely to pay off the most in the long run. And you can’t achieve all of the goal all at once — as I described in Blog@CACM, you take incremental steps. These are all tough choices.
Joan Ferrini-Mundy spoke at our White House Symposium on State Implementation of CS for All (pictured above). Joan is the Assistant Director at NSF for the Education and Human Resources Directorate. She speaks for Education Research. She phrased her remarks as three research areas for the CS for All initiative, but I think that they could be reasonably interpreted as three sets of warnings. These are the things that could go wrong, that we ought to be paying attention to.
1. Graduation Requirements: Joan noted that many states are making CS “count” towards high school graduation requirements. She mentioned that we ought to consider the comments of organizations such as NSTA (National Science Teachers Association) and NCTM (National Council of Teachers of Mathematics). She asked us to think about how we resolve these tensions, and to track what are the long term effects of these “counting” choices.
People in the room may not have been aware that NSTA had just (October 17) come out with a statement, “Computer Science Should Supplement, not Supplant Science Education.”
The NCTM’s statement (March 2015) is more friendly towards computer science, it’s still voiced as a concern:
Ensuring that students complete college- and career-readiness requirements in mathematics is essential. Although knowledge of computer science is also fundamental, a computer science course should be considered as a substitute for a mathematics course graduation requirement only if the substitution does not interfere with a student’s ability to complete core readiness requirements in mathematics. For example, in states requiring four years of mathematics courses for high school graduation, such a substitution would be unlikely to adversely affect readiness.
Both the NSTA and NCTM statements are really saying that you ought to have enough science and mathematics. If you only require a couple science or math courses, then you shouldn’t swap out CS for one of those. I think it’s a reasonable position, but Joan is suggesting that we ought to be checking. How much CS, science, and mathematics are high school students getting? Is it enough to be prepared for college and career? Do we need to re-think CS counting as science or mathematics?
2. Teacher Credentialing: Teacher credentials in computer science are a mishmash. Rarely is there a specific CS credential. Most often, teachers have a credential in business or other Career and Technical Education (CTE or CATE, depending on the state), and sometimes mathematics or science. Joan asked us, “How is that working?” Does the background matter? Which works best? It’s not an obvious choice. For example, some CS Ed researchers have pointed out that CTE teachers are often better at teaching diverse audiences than science or mathematics teachers, so CTE teachers might be better for broadening participation in computing. We ought to be checking.
3. The Mix of Curricular Issues: While STEM has a bunch of frameworks and standards to deal with, we know what they are. There’s NGSS (Next Generation Science Standards) and the National Research Council Framework. There’s Common Core. There are the NCTM recommendations.
In Computer Science, everything is new and just developing. We just had the K-12 CS Framework released. There are ISTE Standards, and CSTA Standards, and individual state standards like in Massachusetts. Unlike science and mathematics, CS has almost no assessments for these standards. Joan explicitly asked, “What works where?” Are our frameworks and standards good? Who’s going to develop the assessments? What’s working, and under what conditions?
I’d say Joan is being a critical friend. She wants to see CS for All succeed, but she doesn’t want that to cost achievement in other areas of STEM. She wants us to think about the quality of CS education with the same critical eye that we apply to mathematics and science education.
As usual, Barbara Ericson went heads-down, focused on the AP CS A data when the 2016 results were released. But now, I’m only one of many writing about it. Education Week is covering her analysis (see article here), and Hai Hong of Google did a much nicer summary than the one I usually put together. Barb’s work with Project Rise Up 4 CS and Sisters Rise Up have received funding from the Google Rise program, which Hai is part of. I’m including it here with his permission — thanks, Hai!
Every year, I’m super thankful that Barb Ericson at Georgia Tech grabs the AP CS A data from the College Board and puts it all into a couple of spreadsheets to share with the world. 🙂Here’s the 2016 data, downloadable as spreadsheets: Overall and By Race & Gender. For reference, you can find 2015 data here and here.Below is a round-up of the most salient findings, along with some comparison to last year’s. More detailed info is in the links above. Spoiler: Check out the 46% increase in Hispanic AP exam takers!
- Overall: Continued increases in test-taking, but a dip in pass rates.
- 54,379 test-takers in 2016. This reflects a 17.3% increase from 2015 — which, while impressive, is a slower increase than 24.2% in 2015 and 26.3% in 2014.
- Overall pass rate was 64% (same as last year; 61% in 2014)
- Female exam takers: 23% (upward trend from 22% in 2015, 20% in 2014)
- Female pass rate: 61% (same as last year; 57% in 2014)
- In 8 states fewer than 10 females took the exam: Alaska (9/60), Nebraska (8/88), North Dakota (6/35 ), Kansas (4/57), Wyoming (2/6 ), South Dakota (1/26 ), Mississippi (0/16), Montana(0/9). Two states had no females take the exam: Mississippi and Montana.
- Black exam takers: 2,027 (Increase of 13% from 1,784 in 2015; last year’s increase was 21% from 1,469 in 2014)
- Black pass rate: 33% (down from 38% in 2015, but close to 2014 pass rate of 33.4%).
- Twenty-four states had fewer than 10 African American students take the AP CS A exam. Nine states had no African American students take the AP CS A exam: Maine (0/165), Rhode Island (0/94), New Mexico (0/79), Vermont (0/70), Kansas (0/57), North Dakota (0/35), Mississippi (0/16), Montana (0/9), Wyoming (0/6)
- Hispanic exam takers: 6,256 (46% increase from 4,272 in 2015!)
- Hispanic pass rate: 41.5% (up from 40.5% in 2015)
- Fifteen states had fewer than 10 Hispanics take the exam: Delaware, Nebraska, Rhode Island, New Hampshire, Maine, Kansas, Idaho, West Virginia, Wyoming, Vermont, Mississippi, Alaska, North Dakota, Montana, and South Dakota. Three states had no Hispanics take the exam: North Dakota(0/35), Montana (0/9), South Dakota (0/26).And as a hat-tip to Barb Ericson (whose programs we’ve partnered with and helped grow through the RISE Awards these last 3 years) and the state of Georgia:
- 2,033 exam takers in 2016 (this represents something like a 410% increase in 12 years!)
- New record number of African Americans and females pass the exam in Georgia again this year!
- 47% increase (464 in 2016 vs. 315 in 2015) in girls taking the exam.
- Nationally, the African American pass rate dropped from 37% to 33%. In Georgia it increased from 32% to 34%.
- The pass rate for female students also increased in Georgia from 48% to 51%.
- Only one African American female scored a 5 on the AP CS A exam in Georgia in 2016 and she was in Sisters Rise Up 4 CS (RISE supported project).
Steps Teachers Can Take to Keep Girls and Minorities in Computer Science Education | Cynthia Lee in KQED News
So glad to see Cynthia Lee’s list (described in this blog post) get wider coverage.
Last summer, Cynthia Lee, a lecturer in the computer science department at Stanford University, created a widely-circulated document called, “What can I do today to create a more inclusive community in CS?” The list was developed during a summer workshop funded by the National Science Foundation for newly hired computer science faculty and was designed for busy educators. “I know the research behind these best practices,” said Lee, “but my passion comes from what I’ve experienced in tech spaces, and what students have told me about their experiences in computer science classrooms.”
Too often students from diverse backgrounds “feel that they simply aren’t wanted,” said Lee. “What I hear from students is that when they are working on their assignments, they love [computer science]. But when they look up and look around the classroom, they see that ‘there aren’t many people like me here.’ If anything is said or done to accentuate that, it can raise these doubts in their mind that cause them to questions their positive feelings about the subject matter.”
My ECEP colleagues at the University of Massachusetts Amherst, Rick Adrion and Renee Fall, led a successful NSF alliance called CAITE. One of CAITE’s most successful strategies to improve diversity at university-level CS was to make it easier for students to transfer from community colleges. Community colleges are much more diverse.
The latest reports from Google tell us more about the obstacles that CS students still face in moving from community colleges to bachelor’s degrees, and how to make it easier.
Our latest research shows that students who attend community colleges on the way to computer science (CS) bachelor’s degrees encounter many challenges and obstacles along the way. But there are many ways for community colleges and four-year colleges to work together and with industry to remove these obstacles and support students seeking to transfer into CS majors. Today, we are releasing two complementary research reports that explore the pathways that community college students follow to a bachelor’s degree in CS. The reports also examine the experiences of these students and the opportunities that exist or that might be created to ensure their successful career advancement. Longitudinal Analysis of Community College Pathways to Computer Science Bachelor’s Degrees investigates the national landscape of CS students at community colleges in order to better understand student behaviors and institutional characteristics that support or hinder community college students’ efforts to attain a CS bachelor’s degree. The companion report, Student Perspectives of Community College Pathways to Computer Science Bachelor’s Degrees, takes a complimentary in-depth and qualitative look at the experiences of students from underrepresented groups at community colleges in California, a state that enrolls one quarter of all community college students in the U.S.