Posts tagged ‘BPC’
SIGCSE Preview: Project Rise Up 4 CS: Increasing the Number of Black Students who Pass AP CS A — by paying them
I’m guessing that Barbara’s paper on Friday 1:45-3 (in Hanover FG – whole program here) is going to be controversial. She’s working on a problem we’ve had in GaComputes for years. Besides Betsy DiSalvo’s work on Glitch, we’ve made little progress in increasing numbers of Black students taking AP CS A and even less progress in getting more of them to pass the test.
She’s had significant progress this last year using an approach that NMSI used successfully in Texas and elsewhere. She’s offering $100 to Black students who attend extra sessions to help them pass the exam and who do pass the exam. She’s expanding the program now with a Google RISE grant. Her approach is informed by Betsy’s work – it’s about going beyond interests to values and giving students help in navigating past their motivations to not-learn. She does have aspects of the project in place to counteract the disincentives of cash payments for academic achievement. In the final interviews, students didn’t talk about the money. It may be that the money wasn’t an incentive as much as a face-saving strategy. (Barb’s preview talk was also recorded as part of a GVU Brown Bag.)
This paper describes Project Rise Up 4 CS, an attempt to increase the number of Black students in Georgia that pass the Advanced Placement (AP) Computer Science (CS) A exam. In 2012 Black students had the lowest pass rates on the AP CS A exam both in Georgia and nationally. Project Rise Up 4 CS provided Black students with role models, hands-on learning, competitions, a financial incentive, and webinars on AP CS A content. The first cohort started in January of 2013 and finished in May 2013. Of the 27 students who enrolled in the first cohort, 14 met all of the completion requirements, and 9 (69%) of the 13 who took the exam passed. For comparison, in 2012 only 22 (16%) of 137 Black students passed the exam in Georgia. In 2013, 28 (22%) of 129 Black students passed the exam in Georgia. This was the highest number of Black students to pass the AP CS A exam ever in Georgia and a 27% increase from 2012. In addition, students who met the completion requirements for Project Rise Up 4 CS exhibited statistically significant changes in attitudes towards computing and also demonstrated significant learning gains. This paper discusses the motivation for the project, provides project details, presents the evaluation results, and future plans.
SIGCSE2014 Preview: Engaging Underrepresented Groups in High School Introductory Computing through Computational Remixing with EarSketch
EarSketch is an interesting environment that I got to demo for Jason Freeman and Brian Magerko at the Dagstuhl Livecoding conference. It’s Python programming that creates complex, layered music. The current version of EarSketch isn’t really livecoding (e.g., there’s a “compilation” step from program into digital audio workstation), but I got to see a demo of their new Web-based version which might be usable for live coding .
I got to see the preview talk and was blown away. The paper is about use in a 10 week programming unit in a high school course, with significant under-represented minority and female involvement. The evaluation results are stunning. The authenticity angle here is particularly interesting. In the preview talk, Jason talked about “authentic STEAM.” They have audio loops from real musicians, and involve hip-hop artists in the classroom. Students talk about how they value making music that sounds professional, with tools that professional musicians use.
In this paper, we describe a pilot study of EarSketch, a computational remixing approach to introductory computer science, in a formal academic computing course at the high school level. EarSketch, an integrated curriculum, Python API, digital audio workstation (DAW), audio loop library, and social sharing site, seeks to broaden participation in computing, particularly by traditionally underrepresented groups, through a thickly authentic learning environment that has personal and industry relevance in both computational and artistic domains. The pilot results show statistically significant gains in computing attitudes across multiple constructs, with particularly strong results for female and minority participants.
I’ve been excited to see this paper get published since Betsy first told me about the work. The paper described below (by Betsy DiSalvo, Cecili Reid, and Parisa Khanipour Roshan) looks at the terms that families commonly use to find on-line resources to help their children learn about computer science. They didn’t find Alice or Scratch or Blockly — none of the things that would be our first choices for CS education opportunities on-line. Betsy and her students show how we accidentally hide our resources from the uneducated and under-privileged, by presuming that the searchers are well-educated and privileged. They point out that this is one way that open education resources actually actually increase the socioeconomic gap, by not being easily discoverable by those without privilege. I got to see a preview of this talk, and the results are surprising — a video of the preview talk will be available here. Friday March 7, 3:45-5, in Room Hanover DE.
They Can’t Find Us: The Search for Informal CS Education
In this study we found that search terms that would likely be used by parents to find out-of-school computer science (CS) learning opportunities for their children yielded remarkably unproductive results. This is important to the field of CS education because, to date, there is no empirical evidence that demonstrates how a lack of CS vocabulary is a barrier to accessing informal CS learning opportunities. This study focuses on the experience of parents who do not have the privilege of education and technical experience when searching for learning opportunities for their children. The findings presented will demonstrate that issues of access to CS education go beyond technical means, and include ability to conduct suitable searches and identify appropriate computational learning tools. Out-of-school learning is an important factor in who is motivated and prepared to study computer science in college. It is likely that without early access to informal CS learning, fewer students are motivated to explore CS in formal classrooms.
Check out the headline “Can early computer science education boost number of women in tech?” Then read the part (quoted below) where they show what works at Harvey Mudd. I don’t read anything there about early CS education. I do believe that we need CS in high schools to improve diversity in computing, but I’m not sure that much earlier than high school helps much. I worry about higher education giving up on issues of diversity, by changing the discussion to K12.
I wish that Mercury News would have really said what they found: University Computing Programs, you have the power to improve your diversity! You can change your classes and your culture! Don’t just pass the buck to K12 schools!
“The difference is, females in general are much more interested in what you can do with the technology, than with just the technology itself,” says Harvey Mudd President Maria Klawe, a computer scientist herself.
So administrators created an introductory course specifically for students without programming experience. They emphasized coding’s connection to other disciplines. They paid for freshman women to attend the annual Grace Hopper Celebration of Women in Computing, a chance to meet programming role models in diverse fields. And they provided early research opportunities for women students to inspire them to stick with the field.
The result? The percentage of female computer science majors at Harvey Mudd increased from about 10 percent before the initiatives to 43 percent today.
Here’s a great answer to the under-representation on the AP CS — the College Board (with funding from Google) will offer grants to help start AP programs, including AP CS (see details for AP CS for STEM Access).
AP STEM Access Program: In fall 2013, the College Board implemented the AP STEM Access program in 335 public high schools across the country. With the support of a $5 million Google Global Impact Award to DonorsChoose.org, these schools started offering new AP math and science courses with the goal of enabling underrepresented minority and female students who have demonstrated strong academic potential to enroll in and explore these areas of study and related careers. Over the next three years, the AP STEM Access program will give an estimated 36,000 students the opportunity to study college-level STEM course work in these newly offered AP classes.
An important and interesting position, that I first learned about from the work of Caroline Simard. There is significant evidence that Silicon Vally is not a meritocracy, but there is significant advantage to the people in power there to maintain the myth.
But if the tech scene is really a meritocracy, why are so many of its key players, from Mark Zuckerberg to Steve Jobs, white men? If entrepreneurs are born, not made, why are there so many programs attempting to create entrepreneurs? If tech is truly game-changing, why are old-fashioned capitalism and the commodification of personal information never truly questioned?
The myths of meritocracy and entrepreneurialism reinforce ideals of the tech scene that shore up its power structures and privileges.
The myths of authenticity, meritocracy, and entrepreneurialism do have some basis in fact. But they are powerful because they reinforce ideals of the tech scene that shore up its power structures and privileges. Believing that the tech scene is a meritocracy implies that those who obtain great wealth deserve it, and that those who don’t succeed do not. The undue emphasis placed on entrepreneurship, combined with a limited view of who “counts” as an entrepreneur, function to exclude entire categories of people from ascending to the upper echelon of the industry. And the ideal of authenticity privileges a particular type of self-presentation that encourages people to strategically apply business logics to the way they see themselves and others.
California community colleges’ experiment with accelerated remediation: Maybe there’s more learning going on
Remedial courses in higher-education are important to get right, for lots of reasons. Certainly, that’s one of the big stumbling blocks in MOOCs — many people who start a MOOC aren’t prepared for that level material (or maybe, the MOOCs presume too much knowledge to start). The CAITE alliance was able to improve diversity in Massachusetts’ universities, by improving the transfer from community college, but that path sometimes requires remedial courses. If we could get remediation right, we might improve diversity, make distance learning more successful, and (as suggested below) improve graduation rates.
The story below is unusual: Make remediation better, by making it shorter. A simple time-on-task model would suggest that there’s less being learned. I hypothesize that it might be working (i.e., resulting in more learning), by looking at it from a different model.
At the Future Computer Science Research Summit in Orlando in early January, Nobel laureate Carl Wieman gave a talk where he referenced the famous Richard Hake 6000 subject study. One of the results of that study is that traditional lecture only results in students learning about 30-40 percent of what was being taught, but with student engagement pedagogies, 60-80 percent is learned.
Note the word: engagement. We can engage by using techniques like peer instruction. I wonder if we can also engage by saying, “This required course will be made shorter. You still need it to move on to something you want, but now, it’s less painful.” Could that result in more learning? Maybe that 30-40% becomes 50-60%? So a reduction of a few weeks in time may actually result in equal or more learning?
Remedial courses are widely seen as one of the biggest stumbling blocks to improving college graduation rates, as few students who place into remediation ever earn a degree.
The problem is particularly severe for black and Hispanic students, who account for almost half of the California community college system’s total enrollment of 2.4 million.
More than 50 percent of black and Hispanic community college students place three or more levels below college mathematics, said Myra Snell, a math professor at Los Medanos College. And only 6 percent of those remedial students will complete a credit-bearing math course within three years of starting the first remedial course.
A key reason for abysmal pass rates is the length of remedial sequences, argue Snell and Katie Hern, an English instructor at Chabot College, which, like Los Medanos, is a two-year institution located in California.
“The lower down you start, the fewer students complete,” Hern said.
The two instructors decided to do something about the problem. In 2010 they founded the California Acceleration Project. Armed with research from the Carnegie Foundation for the Advanced of Teaching and the Community College Research Center at Columbia University’s Teachers College, they encouraged their peers to offer shorter remedial sequences in math and English.
The chart below (above, here in the blog) shows the ratio of boy to girl test-takers across AP exam subjects. In subjects whose bars do not reach the orange line, girls outnumber boys. In subjects where the bar extends past the orange line, boys outnumber girls.
Shuchi Grover nails the problem in her EdSurge article linked below. If you read the Slashdot responses to Barbara Ericson’s AP CS statistics (not on a full stomach, of course), you will see a lot of comments along the lines of “The PC BS has to stop at some point. There are some professions and things that men prefer more than women and others that women prefer more than men.” But all the evidence that we have suggests that there is a false hidden assumption in that statement: most students (male and female) don’t pick computer science simply because they have no idea what it is. If students never have access to computer science, never see computer science, never see programming or a programmer or any code, then it’s not a choice.
Here’s news for all: Even today, most children between the ages of 11 and 18 either have no idea about CS or overwhelmingly associate a computer scientist with “building,” “fixing,” “improving” or “studying” computers. While some add ‘programming’ to this list, most don’t see even that within the ambit of computer science.
Research also reports that students finishing high school have a difficult time seeing themselves as computer scientists since they do not have a clear understanding of what computer science is and what a computer scientist does. This is rather unfortunate in light Hazel Markus and Paula Nurius’ powerful study on the idea of “possible selves,” the type of self-knowledge that pertains to how individuals think about their potential and their future.
Congratulations to Maureen!
The Center of Excellence for Women in Technology (CEWiT) at Indiana University officially launched this month. TechTober, the month-long launch of CEWiT during October, culminates on Monday, October 28, with a keynote address by NPR’s Moira Gunn, followed by a special reception at the IU Auditorium.
CEWiT falls under the Office of the Provost umbrella and is dedicated to promoting success, retention, increased engagement, and promotion of IU women faculty, staff and students from multiple disciplines and career intentions who engage with computation and technology. Alliances have formed for each of these three advocacy groups. The focus hits very close to home for the School of Informatics and Computing (SoIC), given that the School has been named a Pacesetter by the National Center for Women in Information & Technology, which works to increase women’s participation in IT.
The connection between SoIC and the program is strengthened by SoIC’s Assistant Dean for Diversity and Education Maureen Bigger’s role as director of CEWiT. She has made a career out of promoting student retention, leadership, teams, diversity, and broadening participation in computing. Biggers came to the School in 2008 from Georgia Tech. During her tenure, undergraduate female enrollment has more than doubled.
A slightly different pattern for me: Check out the quote first, and I’ll add comments after.
Let us consider the conundrum facing the computer field in higher education first. It is experiencing an exponentially increasing demand for its product with an inelastic labor supply. How has it reacted? NSF has made a survey of the responses of engineering departments, including computer science departments in schools of engineering, to the increasing demand for undergraduate education in engineering. There is a consistent pattern in their responses and the results can be applied without exception to the computer field whether the departments are located in engineering schools or elsewhere. 80% of the universities are responding by increasing teaching loads, 50% by decreasing course offerings and concentrating their available faculty on larger but fewer courses, and 66% are using more graduate-student teaching assistants or part-time faculty. 35% report reduced research opportunities for faculty as a result. In brief, they are using a combination of rational management measures to adjust as well as they can to the severe manpower constraints under which they must operate. However, these measures make the universities’ environments less attractive for employment and are exactly counterproductive to their need to maintain and expand their labor supply. They are also counterproductive to producing more new faculty since the image graduate students get of academic careers is one of harassment, frustration, and too few rewards. The universities are truly being choked by demand for their own product and have a formidable people-flow problem, analogous to but much more difficult to address than the cash-flow problem which often afflicts rapidly growing businesses. There are no manpower banks which can provide credit.
This quote was presented by Eric Roberts in his keynote earlier this month at the NSF-sponsored Future Computing Education Research Summit (well organized by Steve Cooper). The highlight is my addition, because I was struck by the specificity of the description. I find the description believable, and it captures the problems of CS higher-education today, especially in the face of rising enrollments in CS classes (discussed by Eric Roberts here and by Ed Lazowka and Dave Patterson here).
What makes this analysis scarier is that the paper quoted was published in 1982. Back in the 1980′s, the state Universities had the mandate and the budget to grow to meet the demand. They didn’t always have the CS PhD graduates that they needed, so some Math and EE PhDs became CS faculty. Today, though, the state Universities are under severe budget constraints. How will we meet the demand in enrollment? In the 1980′s, some CS programs met the demand by raising the bar for entering the CS major, which ended up make CS more white and male (because only the more privileged students were able to stay above the bar). Will our solutions lead to less diversity in CS? Will we lose more faculty to industry, and replace them with MOOCs?
Barb does her analysis of AP CS data every year, but for some reason, her 2013 analysis has really taken off with the media. I’m going to use this post to track the ones I’ve found.
- The EdWeek piece is interesting because it includes a response from the College Board: http://blogs.edweek.org/edweek/curriculum/2014/01/girls_african_americans_and_hi.html?cmp=SOC-SHR-TW
- The Atlantic did an interview with Barb that worked out quite well: http://www.theatlantic.com/education/archive/2014/01/techs-gender-and-race-gap-starts-in-high-school/282966/
- Just learned about the Slate article this morning. http://www.slate.com/blogs/future_tense/2014/01/13/no_women_took_the_ap_computer_science_exam_in_mississippi_montana_and_wyoming.html
- Yes, it’s on Slashdot. That’s not always a pleasant thing. I realized it was there when I suddenly had 500 readers in my blog on a Sunday (about five times a normal load).
If you find others, please send them my way and I’ll update here. If anyone’s interested, our more SIGCSE 2014 paper with more detailed analysis (e.g., controlling for state population, doing a six year historical view of six states, and using regression analysis to explore the relationship of wealth to exam-taking) can be found here: http://bit.ly/SIGCSE14-APCS
Thanks to @NCWIT for the link to this article. I’m not sure that I buy the validity of a crowd-sourced data set, but agree that the Bureau of Labor Statistics’ (BLS) sampled dataset may be missing the overall picture, too. Maybe we have to use multiple measures to triangulate for better accuracy.
The data she’s been collecting for about a month now can be viewed via a Google spreadsheet. Taking a look at them, there are already some interesting findings. Based on data reported for 107 companies, 438 of 3,594 engineers (12%) are females, well below the BLS’s 22% finding, backing up Chou’s theory that the numbers may be inflated.
Here are how the some of the more well known companies in Chou’s data rank:
Khan Academy: 6 of 24 engineers, 25%
Medium: 5 of 21, 24%
GoodReads: 5 of 25, 20%
Snapchat: 2 of 13, 15%
Hootsuite: 6 of 41, 15%
Reddit: 2 of 14, 14%
The Girls Who Code program is growing into more cities, including Boston, Miami, and Seattle in addition to NY and Bay Area programs. They are now recruiting for summer: Summer Immersion Program Interest Form. (Thanks to Leigh Ann Sudol-DeLyser for the pointer.)
Launched in Spring 2012, Girls Who Code is a national nonprofit organization working to close the gender gap in the technology and engineering sectors. With support from public and private partners, Girls Who Code works to educate, inspire, and equip high school girls with the skills and resources to pursue opportunities in computing fields.
via Girls Who Code.
Guest post from Barbara Ericson:
I have finished compiling the data for 2013 for AP CS A. You can download the spreadsheet from http://home.cc.gatech.edu/ice-gt/556 The spreadsheet has 3 sheets with detailed data by race and gender. The first sheet is from 2006 to 2013 for selected states. The second sheet is the race and gender information for every state for 2013. The third sheet is the race and gender information for every state for 2012.
Here are some interesting findings from this data:
- No females took the exam in Mississippi, Montana, and Wyoming.
- For states that had some females take the exam the percentage female ranged from 3.88% in Utah to 29% in Tennessee.
- 11 states had no Black students take the exam: Alaska, Idaho, Kansas, Maine, Mississippi, Montana, Nebraska, New Mexico, North Dakota, Utah, and Wyoming.
- The following states had the most Black students taking the exam: 1) Maryland with 170, 2) Texas with 132, 3) Georgia with 129, 4) Florida with 83, 5) Virginia with 78, 6) California with 74, 7) New York with 68, 8) New Jersey with 34 9) Mass with 34 and 10) North Carolina with 28. The pass rates for Black student in these states: Maryland 27.06%, Texas 48.48%, Georgia 21.7%, Florida 19.28%, Virginia 28.21%, California 56.76%, New York 33.82%, New Jersey 47.06%, Mass 38.24%, and North Carolina 21.43%.
- The pass rate for Black students in states that had at least 5 Black students take the exam ranged from 19% (Florida) to 75% (Alabama) with 6 of 8 passing.
- 8 states had no Hispanic students take the exam: Alaska, Idaho, Kansas, Mississippi, Montana, Nebraska, North Dakota, and Wyoming.
- The following states had the most Hispanic students taking the exam: 1) Texas with 751, 2) California with 392, 3) Florida with 269 , 4) New York with 150, 5) Illinois with 142, 6) New Jersey with 96, 7) Virginia with 90, 8) Maryland with 88, 9) Georgia with 71, and 10) Mass with 56. In report the Hispanic numbers I cam combining the College Board categories of Mexican American, Other Hispanic, and Puerto Rican. The pass rate for Hispanic students in these states: Texas 44.47%, California 47.45%, Florida 44.61%, New York 35.33%, Illinois 39.44%, New Jersey 52.08%, Virginia 46.67%, Maryland 44.32%, Georgia 40.85%, and Mass 39.29%
You can also see historical data for all states for AP CS A at http://home.cc.gatech.edu/ice-gt/321
Director, Computing Outreach
College of Computing