Posts tagged ‘teachers’
Last month, I wrote about the new NSF program Improving Undergraduate Stem Education (see NSF page on IUSE here). I talked to Jane Prey about this program a couple weeks ago, and she was concerned. She said that lots of people are expressing doubt about applying for a program that only has a single page description–not the standard multi-page solicitation.
That’s exactly why this is the time to apply! IUSE doesn’t have a solicitation this year, but most likely will in future years. That means that anything goes this year! If you have any idea that you want to get funded, THIS is the year to apply.
The program description is wonderfully broad:
- Want to work on broadening participation in computing? It’s there: “broadening participation of individuals and institutions in STEM fields.”
- Want to work on after school programs, service learning, new ways of structuring your department, formal education research, new ways of measuring learning? It’s all there: “experiential learning, assessment/metrics of learning and practice, scholarships, foundational education research, professional development/institutional change, formal and informal learning environments.”
Want to work on teacher professional development, or even adult learners? It’s there: “educating a STEM-literate populace, improving K-12 STEM education, encouraging life-long learning, and building capacity in higher education.”
In short, the lack of a formal solicitation means that there are few barriers. You should go for it.
From here on, this is my advice based on talking with NSF program managers and having written (rejected mostly, but a bunch accepted) proposals. This is not coming from NSF:
- You need to demonstrate that your proposal has intellectual merit and broader impacts. That’s part of any NSF proposal.
- No, there’s nothing there that says you must have evaluation, but if you read phrases like “empirically validated teaching practices,” you have to believe that funded proposals will have good evaluation. You can probably be competitive without an external evaluator if you come up with a good evaluation plan in the proposal body itself. If you don’t know how to do this, bring in an external evaluator.
- The really tough part of applying to a program without a solicitation is deciding how much to budget. Here’s me just gazing into a crystal ball: Smaller but realistic budgets have the greatest chance of getting funded. If you can do your project in $100-200K/year for two to three years, you increase your odds of getting funded. I think there’s a psychological barrier for review committees at a $1M proposal, so stay below that or make your really proposal great.
The big message is: Apply on February 4, 2014. Take this rare opportunity to get your wildest and most exciting ideas on the table at NSF.
Computing is included as one of the priorities in England’s offer of special funding to attract more teachers. Scholarships up to 25K pounds are pretty impressive. Texas is offering loan forgiveness. I don’t know if there’s anyone else in the US trying this approach.
Schools Minister David Laws said more scholarships and bursaries would be available to help recruit the most talented graduates with the potential to be brilliant teachers in key subjects. This would help raise standards in schools and ensure all children were given a good education.
Scholarships, awarded by respected subject organisations, will be available to the most talented maths, physics, chemistry and computing trainees. Bursaries will be available to top graduates in maths, physics, chemistry, computing, and languages, in primary and in priority subjects at secondary school (English, history, biology, geography, music, and design and technology).
One reason we have so much engineering and so little computer science taught at US high schools. | ACM Inroads
Joe Kmoch wrote an interesting follow-on to my blog post about why we have so little CS ed in the US. Why is that engineering is succeeding so much more than CS in high schools in the US? He suggests that (in part) it’s because engineering is getting the PD right.
I think the reason is that groups like Project Lead the Way (PLTW) offer an “off the shelf” high quality program, vetted by engineers. The attractiveness of this is that the school and students get access to a number of well-written up-to-date courses and they also get access to intensive professional development for teachers who want to teach a particular PLTW course. Teachers must not only take but also pass the two-week intensive summer course before being allowed to teach a particular course. There is regular monitoring of schools in terms of offering a minimal 3-course sequence of engineering courses and evaluating how well these courses are being taught.
In computer science we have really never had such a program available. The AP is not such a program. If a school wants to teach a computer science course, they have to find a teacher who is willing to put together a course syllabus, and then teach that course. (For AP, the course must be audited for fidelity). There really isn’t any professional development required to teach any kind of computer science course in most states.
Try out the tutorials for the Hour of Code for CSEd Week 2013.
Choose a tutorial for your students
Check out the tutorials and pick one for your class. Note: we have not yet received the Hour of Code submissions from Scratch or KhanAcademy, so check back for those. Also, more international/multilingual support is on its way.
Go through the tutorial yourself so you can help students during the Hour of Code.
Test tutorials on student computers or devices. Make sure they work properly (with sound and video).
Preview the congrats page to see what students will see when they finish.
If the tutorial you choose works best with sound, provide headphones for your class, or ask students to bring their own.
Excellent post and interesting discussion at Neil Brown’s blog, on the question of the role of types for professional software developers and for students. I agree with his points — I see why professional software developers find types valuable, but I see little value for novice programmers nor for end-user programmers. I have yet to use a typing system that I found useful, that wasn’t just making me specify details (int vs Integer vs Double vs Float) that were far lower level than I cared about nor wanted to care about.
This paper is getting a lot of discussion here at Georgia Tech:
In preliminary research, professors at Harvey Mudd College haven’t found that students learn more or more easily in so-called flipped courses than in traditional classes, USA Today reports. In flipped courses, students watch professors’ lectures online before coming to class, then spend the class period in discussions or activities that reinforce and advance the lecture material.
Earlier this year, the National Science Foundation gave four professors at the college in Claremont, Calif., a three-year grant for $199,544 to study flipped classrooms. That research isn’t complete yet, but the professors already tried flipping their own classes last year and found “no statistical difference” in student outcomes.
The reason why it’s generating a lot of discussion is because we know that it can make a difference to flip a classroom. Jason Day and Jim Foley here at Georgia Tech did a careful and rigorous evaluation of a flipped classroom seven years ago (see IEEE paper on their study). We all know this study and take pride in it — it was really well done. It can work. The Harvey Mudd study also shows that it can be done in a way that it doesn’t work.
That’s really the story for all educational technology. It can work, but it’s not guaranteed to work. It’s always possible to implement any educational technology (or any educational intervention at all) in such a way that it doesn’t work.
I just received this via email:
We would like to inform you that we have added recently many new resources to the Computer Science Open Educational Resources Portal (CS OER Portal) (http://iiscs.wssu.edu/drupal/csoer ). For those of you who have not visited it, the Portal hosts a rich collection of links to open teaching/learning materials targeted specifically the area of Computer Science. It provides multiple ways for locating resources, including search with filtering the results by CS categories, material type, level, media format, etc., as well as browsing by institutional (OpenCourseWare) collections, by CS categories, or by topics as recommended by the ACM/IEEE Computer Science Curriculum. The browsing functionality is supplemented with recommendations for similar courses/resources.
My first thought was, “Is this competition for Ensemble, the big NSF-sponsored digital library of CS curricular materials?”
If we’re specifically thinking just about computing in schools (K-12 in the US), we should also consider the CSTA Source Web Repository and the Resources section of the Computing at Schools website (which is pretty big and growing almost daily).
Specifically for a particular tool or approach, there’s the Greenfoot Greenroom, ScratchEd for Scratch Teachers and other Educators, the Alice teacher’s site, the TeaParty site (for the Alice + MediaComp website), and of course, the Media Computation site. I’m sure that there are many others — for particular books (like this one introducing Python with Objects), for particular curricular approaches (like Exploring Computer Science and CSUnplugged), and even for particular methods (I reference the Kinesthetic Learning Activities site in my TA preparation class).
It’s really great that there are so many repositories, so many resources to help CS teachers, and so many people developing and sharing resources. I get concerned when I’m in a meeting where we’re talking about how to help CS teachers, and someone suggests (and it really happens in many of the meetings I attend), “If we only had a repository where teachers could find resources to help them…” No, I really don’t think that more repositories is going to solve any problems at this point.
I have a CS Ed PhD depth exam meeting later this morning. One of the committee members can’t make it, because she’s a UK faculty member who is going on strike today. (BBC coverage here.)
The concerns of the strikers (press release linked below) seem pretty similar to the issues that we have in the United States: No pay raises for faculty (University System of Georgia faculty haven’t had a pay raise since 2008), big salaries for upper administration, and increasing middle management bloat. Interesting to see if this picks up on this side of the Atlantic.
UCU, UNISON and Unite trade unions announced today that their members working in higher education will walk out on Thursday 31 October in an increasingly bitter row over pay.
Staff have been offered a pay rise of just 1% this year, which means they have suffered a pay cut of 13% in real terms since October 2008. Will Hutton this weekend highlighted that as one the most sustained cut in wages since the Second World War.
The squeeze on staff pay comes at a time when pay and benefits for university leaders increased, on average, by more than £5,000 in 2011-12, with the average pay and pensions package for vice-chancellors hitting almost £250,000.
I have a theory that predicts when (if?) we will see more computing education research students in the US. I think that it might also help understand when computer science education (e.g., an AP course in CS) might reach the majority of US high schools.
Why are there so few CS Ed research students in the US?
Recently, I hosted a visit from Dr. Nick Falkner (Associate Dean (IT), Faculty of Engineering, Mathematical and Computer Sciences) and Dr. Katrina Falkner (Deputy Head and Director of Teaching, School of Computer Science) from the University of Adelaide. We got to talking about the lack of CS education research (CER) graduate students in the United States. There are lots of PhD students studying CER in Australasia, Europe, and Israel. To offer a comparison point, when we visited Melbourne in 2011, they had just held a doctoral consortium in CS Ed with 20 students attending, all from just the Melbourne area. The ICER doctoral consortium at UCSD in August had 14 students, and not all 14 were from the US. The Australasian Computing Education will have its own DC, and they’re capping enrollment at 10, but there are far more CER PhD students than that in the region. I get invitations regularly to serve on review committees for dissertations from Australia and Europe, but rarely from the US.
Why is CER so much more popular among graduate students outside of the US? I’ve wondered if it’s an issue of funding for research, or how graduate students are recruited. Then it occurred to us.
Check out the Falkners’ titles: Associate Dean, Deputy Head (Katrina will be Head of School next year), Director. I remarked on that, and Nick and Katrina started naming other CS education research faculty who were Chairs, full Professors, and Deans and Directors in Australia. We went on naming other CS education researchers in high positions in New Zealand (e.g., Tim Bell, Professor and Deputy Head of Department), England (e.g., the great Computing Education Group at Kent), Denmark (e.g., Michael Caspersen as Director of the Center for Science Education), Sweden (e.g., CS Education Research at Uppsala), Finland, Germany, and Israel.
Then I was challenged to name:
- US CS Education researchers who are full Professors at research intensive universities;
- US CS Education researchers who are Chairs of their departments or schools;
- US CS Education researchers who are Deans or Center Directors.
I’m sure that there would be some quibbling if I tried to name US researchers in these categories. I don’t think anyone would disagree that none of these categories requires more than one hand to count — and I don’t think anyone needs more than a couple fingers for that last category.
We have great computing education researchers in the United States. Few are in these kinds of positions of visible prestige and authority. Many in the ICER community are at teaching institutions. Many who are at research intensive universities are in teaching track positions.
Computing Education Research is not as respected in US universities as it is in other countries. In these other countries, a graduate student could pursue computing education research, and might still be able to achieve tenure, promotion, and even an administrative position in prestigious institutions. That’s really rare in the United States.
There are many reasons why there isn’t more CER in research-intensive universities. Maybe there’s not enough funding in CER (which is an outcome of lack of respect/value). Most people don’t buy into computing for all in the US. Unless there’s more CER in schools, maybe we don’t need much CER in Universities. I’m actually not addressing why CER gets less respect in the US than in other countries — I’m hypothesizing a relationship between two variables because of that lack of respect.
The status of CER is definitely on the mind of students when they are considering CER as a research area. I’ve lost students to other areas of research when they realize that CER is a difficult academic path in the US. My first CS advisor at U-Michigan (before Elliot Soloway moved there) was strongly against my plans for a joint degree with education. “No CS department will hire you, and if they do, they won’t tenure you.” I succeeded into that first category (there was luck and great mentors involved). It’s hard for me to say if my personal path could ever reach categories 2 or 3, and if barriers I meet are due more to my research area than my personal strengths and weaknesses. All I can really say for sure is that, if you look around, there aren’t many CER people in those categories, which means that there is no obvious evidence to a graduate student that they can reach those kinds of success.
So, here’s my hypothesis:
Hypothesis: We will see more computing education research graduate students in the US when CER is a reasonable path to tenure, promotion, and advancement in research-intensive US universities.
Why is there so little computing education in US high schools?
Other countries have a lot more computing education in their high schools than we do in the United States. Israel, New Zealand, Denmark, and England all have national curricula that include significant computer science. In Israel, you can even pursue a software engineering track in high school. They all have an advantage over the US, since we have no national curricula at all. However, Germany, which has a similarly distributed education model, still has much more advanced computing education curricula (the state of Bavaria has a computing curriculum for grades 6-12) and CS teacher professional development. What’s different?
I suspect that there are similar factors at work in schools as in Universities. Computing education is not highly valued in US society. That gets reflected in decisions at both the University and school systems. I don’t know much about influence relationships between the University and the K-12 system. I have suggested that we will not have a stable high school CS education program in the United States without getting the Schools of Education engaged in teacher pre-service education. I don’t know how changes in one influence the other.
However, I see a strong correlation, caused by an external social factor — maybe some of those I mentioned earlier (not enough funding for CER, don’t need more CER, etc.). Professors and University administrators are not separate from their societies and cultures. The same values and influences are present in the University as in the society at large. What the society values has an influence on what the University values. If a change occurs in the values in the society, then the University values will likely change. I don’t know if it works in the other way.
So here’s where I go further out on a limb:
Second Hypothesis: We will see the majority of US high schools offering computer science education (e.g., AP CS) when CER is a reasonable path to tenure, promotion, and advancement in research-intensive US universities.
Here are two examples to support the hypothesis:
- Consider Physics. No one doubts the value of physics. Within society, we’re willing to spend billions to find a Higgs Boson, because we value physics. Similarly, we strive to offer physics education to every high school student. Similarly, physics faculty can aspire to become Deans and even University Presidents. Physics is valued by society and the University.
- Consider Engineering Education Research. Twenty years ago, engineering education research was uncommon, and it had little presence in K-12 schools. Today, there are several Engineering Education academic units in the US — at Purdue, Clemson, and Virginia Tech. (There’s quite a list here.) Engineering education researchers can get tenured, promoted, and even become head of an engineering education research academic unit. And, Engineering is now taught in K-12 schools. Recently, I’ve been involved in an effort to directly interview kids in schools that offer AP CS. We can hardly find any! Several of the schools in the Atlanta area that used to offer AP CS now offer Engineering classes instead. (Maybe the belief is that engineers will take care of our CS/IT needs in the US?) Engineering has a significant presence in K-12 education today.
I don’t think that this hypothesis works as a prescriptive model. I’m not saying, “If we just create some computing education research units, we’ll get CS into high schools!” I don’t know that there is much more CS Ed in schools in Australia, Sweden, or Finland than in the US, where CER is a path to advancement. I hypothesize a correlation. If we see changes at the Universities, we’ll be seeing changes in schools. I expect that the reverse will also be true — if we ever see the majority of US high schools with CS, the Universities will support the effort. But I thnk that the major influencer on both of these is the perception of CER in the larger society. I’m hypothesizing that both will change if the major influence changes.
(Thanks to Briana Morrison, Barbara Ericson, Amy Bruckman, and Betsy DiSalvo on an earlier draft of this post.)
This is from Jennie Kay, who was one of the organizers of the SIGCSE Robot Rodeo a few years ago, and is a leader in the use of robotics in CS education in the SIGCSE community.
Educational Robots for Absolute Beginners:
A Free On-Line Course that teaches the basics of LEGO NXT Robot Programming
Got a LEGO NXT robot kit but don’t know where to begin? Come learn the basics of LEGO NXT Robot Programming and discover a new way to bring math, science, and computer science content to your students both in and out of the classroom. By the end of this class, you (YES YOU!) will have built your own robot and programmed it to dance around the room.
This course, developed by the Rowan University Laboratory for Educational Robotics and supported by a generous grant from Google CS4HS, is specifically designed for K-12 teachers, but is free and open to anyone who is interested in learning about LEGO NXT robotics. The course will be starting at the end of October. Preregister now and we’ll send you an email when we open up the course. To preregister, as well as to see our video “trailer” and get the answers to frequently asked questions please visit: http://cs4hsrobots.appspot.com/
The first of these “lies” is the one that that the students in my TA Prep (Teaching Assistant Preparation course, for PhD students learning to be teaching assistants) courses most often say back to me. The third lie (where “___” is “computer programming”) is a pernicious one among CS teachers.
When I was in middle school and high school, teachers loved to impart various tidbits of wisdom about the way students learn during lectures, always couched in such a way as to indicate these were scientifically accepted facts. You know everyone learns differently. Do you think you learn better through words or pictures? Did you know you learn different subjects with different sides of the brain?
Welp, they were wrong. Many of the theories of “brain-based” education, a method of instruction supposedly based on neuroscience, have been largely debunked by rigorous science. Brain-based education studies are usually poorly designed and badly controlled. Nevertheless, myths about how we learn persist in the popular imagination, and, most importantly, in educational materials and references for teachers.
1. We Learn Best When Teaching Is Tailored To Our Learning Style
2. Some People Are Left-Brained, Some People Are Right-Brained
3. __ Will Make You Smarter
My colleague Mary Jean Harrold lost her battle with cancer last week. Mary Jean worked hard for women in computing, and was always a strong supporter of efforts to improve and broaden computing education. The classes I’m now teaching in TA preparation were originally proposed by Mary Jean and a committee she chaired — she thought it was important that we produce PhD’s who know something about teaching and communicating ideas. She will be missed.
Harrold also was a fierce advocate for women and minorities in computing fields. At Georgia Tech, she was the NSF ADVANCE Professor in the School of Computer Science for 10 years, from 2001 to 2011; she also was a member of the Leadership Team and Director of the Georgia Tech Hub for the National Center for Women and Information Technology (NCWIT). Outside Georgia Tech, Harrold served many years (several as co-chair) on the CRA’s Committee on the Status of Women in Computing Research (CRA-W), whose goal is to increase the number of women in computer science research and education. She was instrumental in establishing the biennial Software Engineering Educators’ Symposium (SEES), which aims to forge ties between faculty at minority-serving colleges and software engineering researchers.
Karen Head has finished her series on how well the freshman-composition course fared (quoted and linked below), published in The Chronicle. The stats were disappointing — only about 238 of the approximately 15K students who did the first homework finished the course. That’s even less than the ~10% we saw completing other MOOCs.
Georgia Tech also received funding from the Gates Foundation to trial a MOOC approach to a first year of college physics course. I met with Mike Schatz last Friday to talk about his course. The results were pretty similar: 20K students signed up, 3K students completed the first assignment, and only 170 finished. Mike had an advantage that Karen didn’t — there are standardized tests for measuring the physics knowledge he was testing, and he used those tests pre-post. Mike said the completers fell into three categories: those who came in with a lot of physics knowledge and who ended with relatively little gain, those who came in with very little knowledge and made almost no progress, and a group of students who really did learn alot. They don’t know why nor the relative percentages yet.
The researchers also say, perhaps unsurprisingly, that what mattered most was how hard students worked. “Measures of student effort trump all other variables tested for their relationships to student success,” they write, “including demographic descriptions of the students, course subject matter, and student use of support services.”
It’s not surprising, but it is relevant. Students need to make effort to learn. New college students, especially first generation college students (i.e., whose parents have never gone to college), may not know how much effort is needed. Who will be most effective at communicating that message about effort and motivating that effort — a video of a professor, or an in-person professor who might even learn your name?
As Gary May, our Dean of Engineering, recently wrote in an op-ed essay published in Inside Higher Ed, “The prospect of MOOCs replacing the physical college campus for undergraduates is dubious at best. Other target audiences are likely better-suited for MOOCs.”
On the freshman-composition MOOC, Karen Head writes:
No, the course was not a success. Of course, the data are problematic: Many people have observed that MOOCs often have terrible retention rates, but is retention an accurate measure of success? We had 21,934 students enrolled, 14,771 of whom were active in the course. Our 26 lecture videos were viewed 95,631 times. Students submitted work for evaluation 2,942 times and completed 19,571 peer assessments (the means by which their writing was evaluated). However, only 238 students received a completion certificate—meaning that they completed all assignments and received satisfactory scores.
Our team is now investigating why so few students completed the course, but we have some hypotheses. For one thing, students who did not complete all three major assignments could not pass the course. Many struggled with technology, especially in the final assignment, in which they were asked to create a video presentation based on a personal philosophy or belief. Some students, for privacy and cultural reasons, chose not to complete that assignment, even when we changed the guidelines to require only an audio presentation with visual elements. There were other students who joined the course after the second week; we cautioned them that they would not be able to pass it because there was no mechanism for doing peer review after an assignment’s due date had passed.
I’m teaching a TA preparation course at Georgia Tech this semester. My students are PhD students who are learning how to be teaching assistants. In a session on dealing with classroom behavior and FERPA, I introduced peer instruction — I put scenarios up on the screen with four or five choices of responses, and the students used clickers to choose what they thought was the appropriate response. One of the scenarios was:
In a class discussion, a student starts yelling at another student: “You moron! C# is a terrible language for that! You should use C++!” What do you do?
I had a distractor that collected a surprising number of votes: “Just let it go – that’s the way CS students are.” And after the discussion period — that one still got some votes. The expectation that “That’s just the way CS students are” is surprisingly pervasive. Computer science teachers need to stand up to it, to demand change in culture and expectations.
Later in my class, the students are reading chapters of Diana Franklin’s new book.
So, you see, I was all too familiar with what my daughter was going through, but I was unprepared for the harassment to start in high school, in her programming class.I consulted with friends — female developers — and talked to my daughter about how to handle the situation in class. I suggested that she talk to you. I offered to talk to you. I offered to come talk to the class. I offered to send one of my male friends, perhaps a well-known local programmer, to go talk to the class. Finally, my daughter decided to plow through, finish the class, and avoid all her classmates. I hate to think what less-confident girls would have done in the same situation.My daughter has no interest in taking another programming class, and really, who can blame her.
The Washington Post series on “The Tuition is Too Damn High” has been fascinating, filled with interesting data, useful insights, and economic theory that I hadn’t met previously. The article linked below is about “Baumol’s cost disease” which suggests an explanation for why wages might increase when productivity does not. It’s an explanation that some have used to explain the rise in tuition, which Post blogger Dylan Matthews rejects based on the data (in short: faculty salaries aren’t really rising — the increase in tuition is due to other factors).
But I actually had a concern about an earlier stage in his argument. It’s absolutely true that our labor intensive methods do not lead to an increase in productivity in terms of number of students, while MOOCs and similar other methods can. However, we can gain productivity in terms of quality of learning and retention. We absolutely have teaching methods, well-supported with research, that lead to better learning and more retention — we can get students to complete more classes with better understanding. In the end, isn’t THAT what we should be measuring as productivity of an educational enterprise, not “millions of customers served” (even if they don’t complete and don’t learn)?
Performing a string quartet will always require two violinists, a violist and a cellist. You can’t magically produce the same piece with just two people. Higher education, for at least the past few millennia, has seemed to fall in this category as well. “What just happened in my classroom is not very different from what happened in Plato’s academy,” quips Archibald. We’ve gotten better at auditorium-building, perhaps, but lecturers generally haven’t gotten more productive.