Posts tagged ‘broadening participation in computing’
Sepehr Vakil appointed first Associate Director of Equity and Inclusion in STEM Education at U. Texas-Austin
I just met Sepehr at an ECEP planning meeting. Exciting to meet another CS Ed faculty in an Education school! He won the Yamashita Prize at Berkeley in 2015 for his STEM activism.
Dr. Vakil’s research revolves around the intersection of equity and the teaching and learning of STEM, particularly in computer science and technology. This focus has led Dr. Vakil to conduct participatory design research projects in several contexts. These efforts include founding and directing the Oakland Science and Mathematics Outreach (OSMO) program—an after school program serving youth of color in the city of Oakland. Dr. Vakil also has experience teaching and conducting research within public schools. During graduate school, he co-taught Introductory Computer Science Courses for 3 years in the Oakland Unified and Berkeley Unified School Districts. As part of a university-research collaboration between UC Berkeley and the Oakland Unified School District, he worked with students and teachers in the Computer Science and Technology Academy at Oakland Technical High School to design an after school racial justice organization named SPOCN (Supporting People of Color Now!) Dr. Vakil’s work at the intersection of equity, STEM, and urban education has also led to publications in prestigious journals such as Cognition & Instruction, Equity and Excellence in Education, and the Journal of the Learning Sciences.
There was interest in our slides from the 2017 SIGCSE Panel, “The Role of CS Departments in The US President’s “CS for All” Initiative.” They are linked above, and summarized below.
In January 2016, US President Barack Obama started an initiative to provide CS for All – with the goal that all school students should have access to computing education. Computing departments in higher education have a particularly important role to play in this initiative. It’s in our best interest to get involved, since the effort can potentially improve the quality of our incoming students. CS Departments have unique insights as subject-matter experts to inform the development of standards. We can provide leadership to inform and influence education policy. In this session, we will present a variety of ways in which departments and faculty can support CS for All and will answer audience questions about the initiative. Our goal is to provide concrete positive actions for faculty.
Barbara Ericson spoke on influencing our incoming students and using outreach to improve the number and diversity of students and to improve the number and quality of teachers.
Rick Adrion spoke on CS faculty providing subject-matter expertise to standards efforts. A key role for CS faculty is to help teachers, administrators, and public policy makers to understand what CS is.
Megean Garvin spoke on how CS faculty can provide a leadership role. Faculty have a particular privileged position to draw together diverse stakeholders to advance CS Education.
Barbara Ericson, with the help of Phil Sands at Purdue, has now finished tabulating the demographic data for AP Computer Science for 2015 — see link here. We don’t yet have the statistical tests that Kevin Karplus asked for (see post here), but Barbara did list the percentage of Hispanic exam takers with their proportion of the population.
Our blog posts on AP CS have been picked up by Audrey Watters in her 2015 Top Ed-Tech Trends summary, in a decidedly negative light.
I’ll look at the whole “learn-to-code” push in an upcoming post, but I will note here: “Nationally, 37,327 students took the AP CS A exam in 2014,” Mark Guzdial observed. “This was a big increase (26.29%) from the 29,555 students who took it in 2013.” “Barbara Ericson’s 2015 AP CS demographics analysis: Still No African-Americans Taking the AP CS Exam in 9 States.” And Code.org teamed up with the College Board: because everyone needs to learn to code and then hand over money to the College Board for an AP test on the subject. Boom.
We don’t analyze AP CS A in order to market for the College Board. We analyze AP CS A exam demographics because it’s the only operational definition we have found of the state of computing education across the United States. From our work in “Georgia Computes!” we know that AP CS A tracks closely all other computing education in Georgia. AP CS A is a dipstick to get a sense for who’s in the high school CS population.
Three and a half years, and 1000 blog posts ago, I wrote my 999th blog post about research questions in computing education (see post here). I just recently wrote a blog post offering my students’ take on research questions in computing education (see post here), which serves to update the previous post. In this blog post, I’m going to go more meta.
In my CS Education Research class (see description here), my students read a lot of work by me and my students, some work on EarSketch by Brian Magerko and Jason Freeman, and some by Betsy DiSalvo. There are other researchers doing work related to computing education in the College of Computing at Georgia Tech, notably John Stasko’s work on algorithm visualization, Jim Foley’s work on flipped classrooms (predating MOOCs by several years), and David Joyner and Ashok Goel’s work on knowledge-based AI in flipped and MOOC classrooms, and my students know some of this work. I posed the question to my students:
If you were going to characterize the Georgia Tech school of thought in computing education, how would you describe it?
We talked some about the contrasts. Work at CMU emphasizes cognitive science and cognitive tutoring technologies. Work at the MIT Media Lab is constructionist-based.
Below is my interpretation of what I wrote on the board as they called out comments.
- Contextualization. The Georgia Tech School of Computing education emphasizes learning computing in the context of an application domain or non-CS discipline.
- Beyond average, white male. We are less interested in supporting the current majority learner in CS.
- Targeted interventions. Georgia Tech computing education researchers create interventions with particular expectations or hypotheses. We want to attract this kind of learner. We aim to improve learning, or we aim to improve retention. We make public bets before we try something.
- Broader community. Our goal is to have a broaden participation in computing, to extend the reach of computer science.
- We are less interested in making good CS students better. To use an analogy, we are not about raising the ceiling. We’re about pushing back the walls and lowering the floors, and sometimes, creating whole new adjacent buildings.
- We draw on learning sciences theory, which includes cognitive science and educational psychology (e.g., cognitive load theory).
- We draw on social theories, especially distributed cognition, situated learning, social cognitive theory (e.g., expectancy-value theory, self-efficacy).
I might have spent hours coming up with a list like this, but in ten minutes, my students came up with a good characterization of what constitutes the Georgia Tech School of Thought in Computing Education.
Abstract: We share a vision of a society that is able to express problems and ideas computationally. Andrea diSessa called that computational literacy, and he invented the Boxer Programming Environment to explore the media of computational literacy. Education has the job of making citizens literate. Education systems around the world are exploring the question of what should all citizens know about computing and how do we provide that knowledge. The questions being asked are about public policy, but also about what does it mean to be expressive with computation and what should computing users know. The answers to these questions have implications for the future of human-centric computing.
I. Our Job: The first computer scientists set the goal to achieve a Computing-Literate Society.
II. Challenges to Achieving a Computing-Literate Society
Access and Diversity
Inverse Lake Wobegon Effect
Unanswered research questions of policymakers
III. Inventing New Kinds of Computing Education
Story #1: Contextualized Computing Education.
Story #2: Understanding the Needs of High School CS Teachers.
The new NSF STEM-C solicitation is out: See http://www.nsf.gov/pubs/2015/nsf15537/nsf15537.htm.
The introduction to the new solicitation is visionary and speaks of the power of computing in STEM and for all students. Here’s just the first paragraph:
The STEM + Computing (STEM+C) Partnerships program seeks to advance a 21st century conceptualization of education in science, technology, engineering and mathematics (STEM) that includes computing. The “+ Computing” notation emphasizes that computing is integral to the practice of all the other STEM disciplines. In this solicitation, computing refers to the whole set of fundamental concepts and skills that will allow students to creatively apply and adapt computation across a range of application domains, to “bend digital technology to one’s needs, purposes, and will.”
The focus of this solicitation is primarily on integration of computing with other STEM education disciplines, and secondarily, on computing education in K-12 (including teachers). The prioritization is pretty clear from the budget limits:
The maximum total budget for Track 1: Integration of Computing in STEM Education awards is $2.5 million for Design and Development awards, $1.25 million for Exploratory Integration awards, and $250,000 for Field-Building Conferences and Workshops. The maximum total budget for Track 2: Computing Education Knowledge and Capacity Building awards is $600,000 for Research on Education and Broadening Participation awards and $1.0 million for CS 10K awards.
You can get up to $1.25M USD to explore integration of computing in STEM ($2.5M to design and develop), but at most $1M to put computing into schools and at most $600K to do research on computing education and broadening participation. We might argue about the ratios, but in the end, both tracks and all the types of proposals have enough funding to do important work that needs to happen.
I recommend this talk by Ben Shapiro. He does a great job framing his work in computing education research, and shows some terrific examples of his latest work. I like how his work fits so well into both computing and education — he’s using education theory to help students learn important ideas in CS from distributed systems and parallelism (like latency and synchronization) that aren’t yet in the CS standards. This is using advanced knowledge in CS and advanced knowledge in Education to explore new ground.