Posts tagged ‘public policy’

Analyzing CS in Texas school districts: Maybe enough to take root and grow

My Blog@CACM for this month is about Code.org’s decision to shift gradually the burden of paying for CS professional development to the local regions — see link here.  It’s an important positive step that needs to happen to make CS sustainable with the other STEM disciplines in K-12 schools.

We’re at an interesting stage in CS education. 40-70% of high schools have CS, but the classes are pretty empty.  I use Indiana and Texas as examples because they’ve made a lot of their data available.  Let’s drill a bit into the Texas data to get a flavor of it, available here.  I’m only going to look at Area 1’s data, because even just that is deep and fascinating.

Brownsville Intermediate School District. 13,941 students. 102 in CS.

Computer_Science_Regional_Data___STEM_Center___The_University_of_Texas_at_Austin

Of the 10 high schools in Brownsville ISD, only two high schools have anyone in their CS classes.  Brownsville Early College High School has 102 students in CS Programming (no AP CS Level A, no AP CSP).  That probably means that one teacher has several sections of that course — that’s quite a bit.  The other high school, Porter Early College High School has fewer than five students in AP CS A.  My bet is that there is no CS teacher there, only five students doing an on-line class.  That means for 10 high schools and 13K students, there is really only one high school CS teacher.

Edinburg Consolidated Independent School District, over 10K students, 92 students in CS.

Computer_Science_Regional_Data___STEM_Center___The_University_of_Texas_at_Austin-3

This is a district that could grow CS if there was will.  There are 6 high schools, but two are special cases: One with less than 5 students, and the other in a juvenile detention center.  The other four high schools are huge, with over 2000 students each.  In Economedes, that are only 9 students in AP CS A — maybe just on-line?  Edinburg North and Robert R Vela high school each have two classes: AP CS A and CS1.  With 21 and 14, I’m guessing two sections.  The other has 43 and 6. That might be two sections of AP CS A and another of CS1, or two sections of AP CS A and 6 students in an on-line class.  In any case, this suggests two high school CS teachers (maybe three) in half of the high schools in the district.  Those teachers aren’t teaching only CS, but with increased demand and support from principals, the CS offerings could grow.

It’s fascinating to wander through the Texas data, to see what’s there and what’s not.  I could be wrong about what’s there, e.g., maybe there’s only one teacher in Edinburg and she’s moving from school-to-school.  Given these data, there’s unlikely to be a CS teacher in every high school, who just isn’t teaching any CS. These data are a great snapshot. There is CS in Texas high schools, and maybe there’s enough there to take root and grow.

 

October 19, 2018 at 7:00 am 2 comments

A high-level report on the state of computing education policy in US states: Access vs Participation

states-policyInteresting analysis from Code.org on the development of policies in US states that promote computing education — see report here, and linked below.  The map above is fascinating in that it shows how much computing education has become an issue in all but five states.

The graph below is the one I found confusing.

urm-access

I’ve been corrected: the first bar says that where the school’s population is 0-25% from under-represented minority groups, 41% of those schools teach CS.  Only 27% of mostly-minority schools (75%-100% URM, in the rightmost column) offer CS.  This is a measure of which schools offer computer science.

The graph above doesn’t mean that there are any under-represented minority students in any CS classes in any of those high schools.  My children’s public high school in Georgia was over 50% URM, but the AP CS class was 90% white and Asian kids.  From the data we’ve seen in Georgia (for example, see this blog post), few high schools offer more than one CS class. Even in a 75% URM high school, it’s pretty easy to find 30 white and Asian guys.  Of course, we know that there are increasing numbers of women and under-represented minority students in computer science classes, but that’s a completely different statistic from what schools offer CS.

I suspect that the actual participation of URM students in CS is markedly lower than the proportion in the school.  In other words, in a high school with 25% URM, I’ll bet that the students in the CS classes are less than 25% URM.  Even in a 75% URM high school, I’ll bet that CS participation is less than 75% URM.

Access ≠ participation.

Source: The United States for Computer Science – Code.org – Medium

October 12, 2018 at 7:00 am 10 comments

ECEP has a new home at The University of Texas at Austin: First meeting this week at CSforAll

I can’t tell you how exciting this press release is for me.  Rick Adrion, Renee Fall, Barbara Ericson, and I started the Expanding Computing Education Pathways Alliance (http://ecepalliance.org) in 2012 to provide states with support as they broadened participation in computing education.  Six years later, we had 16 states and Puerto Rico involved — but we were ready to be done.  We all four had worked on previous alliances (CAITE and Georgia Computes) and felt that the movement needed new leaders.  I am so very pleased that Carol Fletcher and her wonderful team decided to carry on ECEP, and NSF has agreed to continue funding ECEP as it expands to TWENTY-THREE states and US territories!

ECEP (now based out of UT-Austin) will have its first meeting this week, at Wayne State University in Detroit (where Barbara and I first met in 1983) as part of the CSforAll summit.

The National Science Foundation (NSF) has awarded the UT STEM Center a three-year $2.5 million grant to lead the Expanding Computing Education Pathways (ECEP) Alliance. ECEP is one of eight Broadening Participation in Computing Alliances (BPC) funded by the NSF to increase the number and diversity of students in K-16 pathways. ECEP works with state leadership teams to achieve this goal through education policy reform. First launched in 2012 through an NSF grant to Georgia Tech and the University of Massachusetts Amherst, ECEP has since grown through four phases from two states to sixteen and Puerto Rico. Building on the existing network of ECEP states noted in the map above, the ECEP leadership team is pleased to announce the fifth phase addition of six new states to the Alliance: Hawaii, Minnesota, Mississippi, Ohio, Oregon, and Washington.

Source: National Alliance for Expanding Computing Education Pathways has a new home at The University of Texas at Austin

October 8, 2018 at 7:00 am Leave a comment

South Carolina requires CS to fulfill high school requirement, and Keyboarding is no longer CS

Pat Yongpradit of Code.org shared some great news with me.  Well, it’s not really “new” — it happened back in March 2018. But it was something that both of us worked on, and it was great to finally see it happen.

South Carolina was one of the first ECEP (Expanding Computing Education Pathways) Alliance states. They had one of the first statewide summits on computing education (see blog post here). They were one of the first states to require computer science for all high school students.

The problem was that they didn’t actually require computer science. They allowed some 90 classes to count as CS, and only six actually contained CS content (like programming or algorithms). Even a course on “keyboarding” counted as “CS” under the South Carolina system. South Carolina resisted changing this requirement, as Tony Dillon of the state Department of Education argued (see this blog post). I’ve worried that other states that mandate CS would fall into a similar trap (see blog post here on that).

That changed March 28, 2018 with this memo. South Carolina has computer science standards. Keyboarding no longer counts.

It’s an interesting question how this happened.  I know that Pat and others at Code.org have been working a lot in South Carolina.  I know that our South Carolina ECEP collaborators, like Eileen Kraemer, Tiffany Barnes, and Mary Lou Maher, have been working tirelessly on the state. I also know that my involvement from Georgia had limited success.  As one Department of Education official said when I was working in Columbia, “No professor from Georgia Tech is going to tell me about AP CS.”

My suspicion is that this happened because there was significant internal and external pressure.  South Carolina wasn’t going to do much when it was just external pressure. But when it was both, there were changes made.

Pat has promised me that Code.org is going to be helping South Carolina fulfill their plans for new CS requirements.

 

September 10, 2018 at 7:00 am Leave a comment

The Story of MACOS: How getting curriculum development wrong cost the nation, and how we should do it better

Man: A Course of Study (MACOS) is one of the most ambitious US curriculum efforts I’ve ever heard about. The goal was to teach anthropology to 10 year olds. The effort was led by world-renowned educational psychologist Jerome Bruner, and included many developers, anthropologists, and educational psychologists (including Howard Gardner). It won awards from the American Education Research Association and from other education professional organization for its innovation and connection to research. At its height, MACOS was in thousands of schools, including whole school districts.

Today, MACOS isn’t taught anywhere. Funding for MACOS was debated in Congress in 1975, and the controversy led eventually to the de-funding of science education nationally.

Peter Dow’s 1991 book Schoolhouse Politics: Lessons from the Sputnik Era is a terrific book which should be required reading for everyone involved in computing education in K-12. Dow was the project manager for MACOS, and he’s candid in describing what they got wrong. It’s worthwhile understanding what happened so that we might avoid it in computing education. I just finished reading it, and here are some of the parts that I found particularly insightful.

First, Dow doesn’t dismiss the critics of MACOS. Rather, he recognizes that the tension is between learning objectives. What do we want for our children? What kind of society do we want to build?

I quickly learned that decisions about educational reform are driven far more by political considerations, such as the prevailing public mood, than they are by a systematic effort to improve instruction. Just as Soviet science supremacy had spawned a decade of curriculum reform led by some of our most creative research scientists during the late 1950s and 1960s, so now a new wave of political conservatism and religious fundamentalism in the early 1970s began to call into question the intrusion of university academics into the schools…Exposure to this debate caused me to recast the account to give more attention to educational politics. No discussion of school reform, it seems, can be separated from our vision of the society that the schools serve.

MACOS was based in the best of educational psychology at the time. Students engaged in inquiry with first-hand accounts, e.g., videos of Eskimos. The big mistake the developers made was they gave almost no thought to how it was going to get disseminated. Dow points out that MACOS was academic researchers intruding into K-12, without really understanding K-12. They didn’t plan for teacher professional development, and worse, didn’t build any mechanism for teachers to tell them how the materials should be changed to work in real classrooms. They were openly dismissive of the publishers who might get the materials into the world.

On teachers: There was ambivalence about teachers at ESI. On the one hand the Social Studies Program viewed its work as a panacea for teachers, a liberation from the drudgery of textbook materials and didactic lessons. On the other, professional educators were seen as dull-witted people who conversed in an incomprehensible “middle language” and were responsible for the uninspired state of American education.

On publishers: These two experienced and widely respected publishing executives listened politely while Bruner described our lofty education aspirations with characteristic eloquence, but the discussion soon turned to practical matters such as the procedures of state adoption committees, “tumbling test” requirements, per-pupil expenditures, readability formulas, and other restrictions that govern the basal textbook market. Spaulding and Kaplan tried valiantly to instruct us about the realities of the educational publishing world, but we dismissed their remarks as the musings of men who had been corrupted by commercialism. Did they not understand that our mission was to change education, not submit to the strictures that had made much of instruction so meaningless? Could not men so powerful in the publishing world commit some of their resources to support curriculum innovation? Had they no appreciation of the intellectual poverty of most social studies classrooms? I remember leaving that room depressed by the monumental conservatism of our visitors and more determined than ever to prove that there were ways to reach the schools with good materials. Our arrogance and naivete were not so easily cured.

By 1971, Dow realizes that the controversies around MACOS could easily have been avoided. They had made choices in their materials that highlighted the challenges of Eskimo life graphically, but the gory details weren’t really necessary to the learning objectives. They simply hadn’t thought enough about their users, which included the teachers, administrators, parents, and state education departments.

My favorite scene in the book is with Margaret Mead who tries to help Dow defend MACOS in Congress, but she’s frustrated by their arrogance and naivete.

Mead’s exasperation grew. “What do you tell the children that for?…I have been teaching anthropology for forty years,” she remarked, “and I have never had a controversy like this over what I have written.”

But Mead’s anger quickly returned. “No, no, you can’t tell the senators that! Don’t preach to them! You and I may believe that sort of thing, but that’s not what you say to these men. The trouble with you Cambridge intellectuals is that you have no political sense!”

Dow describes over two chapters the controversies around MACOS and the aftermath impacts on science education funding at NSF. But he also points out the problems with MACOS as a curriculum. Some of these are likely problems we’re facing in CS for All efforts.

For example, he talks about why MACOS was removed from Oregon schools, using the work of Lynda Falkenstein. (Read the below with an awareness of the Google-Gallup and EdWeek polls showing that administrators and principals are not supportive of CS in schools.)

She concluded that innovations that lacked the commitment of administrators able to provide long-term support and continuing teacher training beyond the initial implementation phase were bound to faster regardless of their quality. Even more than controversy, she found, the greatest barrier to successful innovation was the lack of continuity of support from the internal structure of the school system itself.

I highly recommend Schoolhouse Politics. It has me thinking about what it really takes to get any education reform to work and to scale. The book is light on evaluation evidence that MACOS worked. For example, I’m concerned that MACOS was so demanding that it may have been too much for underprepared students or teachers. I am totally convinced that it was innovative and brilliant. One of the best curriculum design efforts I’ve ever read about, in terms of building on theory and innovative design. I am also totally convinced that it wasn’t ready to scale — and the cost of that mistake was enormous. We need to avoid making those mistakes again.

June 18, 2018 at 7:00 am 6 comments

Are you talking to me? Interaction between teachers and researchers around evidence, truth, theory, and decision-making

In this blog, I’m talking about computing education research, but I’m not always sure and certainly not always clear about who I’m talking to. That’s a problem, but it’s not just my problem. It’s a general problem of research, and a particular problem of education research. What should we say when we’re talking to researchers, and what should we say when we’re talking to teachers, and where do we need to insert caveats or explain assumptions that may not be obvious to each audience?

From what I know of philosophy of science, I’m a post-positivist. I believe that there is an objective reality, and the best tools that we humans have to understand it are empirical evidence and the scientific method. Observations and experiments have errors and flaws, and our perspectives are biased. All theory should be questioned and may be revised. But that’s not how everyone sees the world, and what I might say in my blog may be perceived as a statement of truth, when the strongest statement I might make is a statement of evidence-supported theory.

It’s hard to bridge the gap between researchers and education. Lauren Margulieux shared on Twitter a recent Educational Researcher article that addresses the issue. It’s not about getting teachers access to journal articles, because those articles aren’t written to speak to nor address teachers’ concerns. There have to be efforts from both directions, to help teachers to grok researchers and researchers to speak to teachers.

I have three examples to concretize the problem.

Recursion and Iteration

I wrote a blog post earlier this month where I stated that iteration should be taught before recursion if one is trying to teach both. For me, this is a well-supported statement of theory. I have written about the work by Anderson and Wiedenbeck supporting this argument. I have also written about the terrific work by Pirolli exploring different ways to teach recursion, which fed into the work by Anderson.

In the discussion on the earlier post, Shriram correctly pointed out that there are more modern ways to teach recursion, which might make it better to teach before iteration. Other respondents to that post point out the newer forms of iteration which are much simpler. Anderson and Wiedenbeck’s work was in the 1980’s. That sounds great — I would hope that we can do better than what we did 30 years ago. I do not know of studies that show that the new ways work better or differently than the ways of the 1980’s, and I would love to see them.

By default, I do not assume that more modern ways are necessarily better. Lots of scientists do explore new directions that turn out to be cul-de-sacs in light of later evidence (e.g., there was a lot of research in learning styles before the weight of evidence suggested that they didn’t exist). I certainly hope and believe that we are coming up with better ways to teach and better theories to explain what’s going on. I have every reason to expect that the modern ways of teaching recursion are better, and that the FOR EACH loop in Python and Java works differently than the iteration forms that Anderson and Wiedenbeck studied.

The problem for me is how to talk about it.  I wrote that earlier blog post thinking about teachers.  If I’m talking to teachers, should I put in all these caveats and talk about the possibilities that haven’t yet been tested with evidence? Teachers aren’t researchers. In order to do their jobs, they don’t need to know the research methods and the probabilistic state of the evidence base. They want to know the best practices as supported by the evidence and theory. The best evidence-based recommendation I know is to teach iteration before recursion.

But had I thought about the fact that other researchers would be reading the blog, I would have inserted some caveats.  I mean to always be implicitly saying to the researchers, “I’m open to being proven wrong about this,” but maybe I need to be more explicit about making statements about falsifiability. Certainly, my statement would have been a bit less forceful about iteration before recursion if I’d thought about a broader audience.

Making Predictions before Live Coding

I’m not consistent about how much evidence I require before I make a recommendation. For a while now, I have been using predictions before live coding demonstrations in my classes. It’s based on some strong evidence from Eric Mazur that I wrote about in 2011 (see blog post here). I recommend the practice often in my keynotes (see the video of me talking about predictions at EPFL from March 2018).

I really don’t have strong evidence that this practice works in CS classes. It should be a pretty simple experiment to test the theory that predictions before seeing program execution demonstrations helps with learning.

  • Have a set of programs that you want students to learn from.
  • The control group sees the program, then sees the execution.
  • The experimental group sees the program, writes down a prediction about what the execution will be, then sees the execution.
  • Afterwards, ask both groups about the programs and their execution.

I don’t know that anybody has done this experiment. We know that predictions work well in physics education, but we know that lots of things from physics education do not work in CS education. (See Briana Morrison’s dissertation.)

Teachers have to do lots of things for which we have no evidence. We don’t have enough research in CS Ed to guide all of our teaching practice. Robert Glaser once defined education as “Psychology Engineering,” and like all engineers, teachers have to do things for which we don’t have enough science. We make our best guess and take action.

So, I’m recommending a practice for which I don’t have evidence in CS education. Sometimes when I give the talk on prediction, I point out that we don’t have evidence from CS. But not always. I probably should. Maybe it’s enough that we have good evidence from physics, and I don’t have to get into the subtle differences between PER and CER for teachers. Researchers should know that this is yet another example of a great question to be addressed. But there are too few Computing Education Researchers, and none that I know are bored and looking for new experiments to run.

Code.org and UTeach CSP

Another example of the complexity of talking to teachers about research is reflected in a series of blog posts (and other social media) that came out at the end of last year about the AP CS Principles results.

  • UTeach wrote a blog post in September about the excellent results that their students had on the AP CSP exam (see post here). They pointed out that their pass rate (83%) was much higher than the national average of 74%, and that advantage in pass rates was still there when the data were disaggregated by gender or ethnicity.
  • There followed a lot of discussion (in blog posts, on Facebook, and via email) about what those results said about the UTeach curriculum. Should schools adopt the UTeach CSP curriculum based on these results?
  • Hadi Partovi of Code.org responded with a blog post in October (see post here). He argued that exam scores were not a good basis for making curriculum decisions. Code.org’s pass rates were lower than UTeach’s (see their blog post on their scores), and that could likely be explained by Code.org’s focus on under-represented and low-SES student groups who might not perform as well on the AP CSP for a variety of reasons.
  • Michael Marder of UTeach responded with two blog posts. One conducted an analysis suggesting that UTeach’s teacher professional development, support, and curriculum explained their difference from the national average (see post here), i.e., it wasn’t due to what students were served by UTeach. A second post tried to respond to Hadi directly to show that UTeach did particularly well with underrepresented groups (see post here).

I don’t see that anybody’s wrong here. We should be concerned that teachers and other education decision-makers may misinterpret the research results to say more than they do.

  • The first result from UTeach says “UTeach’s CSP is very good.” More colloquially, UTeach doesn’t suck. There is snake oil out there. There are teaching methods that don’t actually work well for anyone (e.g., we could talk some more about learning styles) or only work for the most privileged students (e.g., lectures without active learning supports). How do you show that your curriculum (and PD and support) is providing value, across students in different demographic groups? Comparing to the national average (and disaggregated averages) is a reasonable way to do it.
  • There are no results saying that UTeach is better than Code.org for anyone, or vice-versa. I know of no studies comparing any of the CSP curricula. I know of no data that would allow us to make these comparisons. They’re hard to do in a way that’s convincing. You’d want to have a bunch of CSP students and randomly assign them to either UTeach and Code.org, trying to make sure that all relevant variables (like percent of women and underrepresented groups) is the same in each. There are likely not enough students taking CSP yet to be able to do these studies.
  • Code.org likely did well for their underrepresented students, and so did UTeach. It’s impossible to tell which did better. Marder is arguing that UTeach did well with underrepresented groups, and UTeach’s success was due to their interventions, not due to the students who took the test.  I believe that UTeach did well with underrepresented groups. Marder is using statistics on the existing data collected about their participants to make the argument about the intervention. He didn’t run any experiments. I don’t doubt his stats, but I’m not compelled either. In general, though, I’m not worried about that level of detail in the argument.

All of that said, teachers, principals, and school administrators have to make decisions. They’re engineers in the field. They don’t have enough science. They may use data like pass rates to make choices about which curricula to use. From my perspective, without a horse in the race or a dog in the fight, it’s not something I’m worried about. I’m much more concerned about the decision whether to offer CSP at all. I want schools to offer CS, and I want them to offer high-quality CS. Both UTeach and Code.org offer high-quality CS, so that choice isn’t really a problem. I worry about schools that choose to offer no CSP or no CS at all.

Researchers and teachers are solving different problems. There should be better communication. Researchers have to make explicit the things that teachers might be confused about, but they might not realize what the teachers are confused about. In computing education research and other interdisciplinary fields, researchers may have to explain to each other what assumptions they’re making, because their assumptions are different in different fields. Teachers may use research to make decisions because they have to make decisions. It’s better for them to use evidence than not to use evidence, but there’s a danger in using evidence to make invalid arguments — to say that the evidence implies more than it does.

I don’t have a solution to offer here. I can point out the problem and use my blog to explore the boundary.

June 15, 2018 at 1:00 am 5 comments

Some principals are getting interested in CS, but think pressure for CS is mostly coming from Tech companies

How do high school principals in small, medium and large districts view the Computer Science for All movement?

 

High school leaders in smaller districts are most enthusiastic about the trend, a new survey by the Education Week Research Center found. Overall, 30% of all principals say CS is not “on their radar,” and 32% say CS is an “occasional supplement or enrichment opportunity.”  I found the two graphs above interesting.  The majority of principals aren’t particularly excited by CS, and most principals think that it’s the Tech firms that are pushing CS onto schools, not parents.

Source: Principals Warm Up to Computer Science, Despite Obstacles

May 28, 2018 at 7:00 am 3 comments

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