Ruthe Farmer’s important big idea: The Last Mile Education Fund to increase diversity in STEM

I met Ruthe Farmer (Wikipedia page) when she represented the Girl Scouts in the early days of the NSF Broadening Participation in Computing (BPC) alliances. She played a significant role in NCWIT. I had many opportunities to interact with her in her roles at NCWIT and CSforAll. Ruthe organized the White House summit with ECEP in 2016 (see blog post) when she was with the Office of Science and Technology Policy in the Obama administration. Her latest project may be the one that’s closest to my heart.

Ruthe has founded and is CEO of the Last Mile Education Fund. Their mission is:

The Last Mile Education Fund offers a disruptive approach to increasing diversity in tech and engineering fields by addressing critical gaps in financial support for low-income underrepresented students within four semesters of graduation.

I was still at Georgia Tech when I heard about the completion microgrant program at Georgia State. Georgia State was (and still is) making headlines for their use of big data to boost retention and get students graduated. Georgia State is the kind of institution where over half of their students are classified as low-income. There is a huge social benefit when GSU can improve their retention statistics. The completion grant program was started in 2011 and focuses on students who could graduate (e.g., their grades were fine), but they had run out of money before they finished. The grant program gave no more than $2,500 per student (Inside Higher Education article). Today, we know that the average grant has actually been $900. That’s a shockingly low cost for getting students the rest of the way to their college degree. It’s a great idea, and deserves to be applied more broadly than one university.

The Last Mile Education Fund especially focuses on getting students from diverse backgrounds into STEM careers. These last gaps in funding are among the barriers that keep girls out from STEM careers (where Ruthe’s focus was in the Girl Scouts and NCWIT) but also low-income students and people of color.

I was reminded to write about the Last Mile Education Fund by Alfred Thompson’s blog (see post here). He’s got a lot more information about the Last Mile Education Fund there.

I am a first generation graduate. My parents and I had no idea how to even apply to college. I am forever grateful that Wayne State University found me in my high school, guided me to applying, and gave me a scholarship to attend. I’m a privileged white guy. Not everybody gets the opportunities I had. It’s critical to extend the opportunity of a higher education degree to a broader and more diverse audience.

The Last Mile Education Fund is important for closing the gap for students from diverse backgrounds. I’m a monthly supporter, and I encourage you to consider giving, too.

Come to the NAS Workshop on the Role of Authentic STEM Learning Experiences in Developing Interest and Competencies for Technology and Computing

Register here. And view the agenda here.

November 4, 2019

1:00 p.m.–6:00 p.m. (reception hour following)

Workshop
Role of Authentic STEM Learning Experiences in Developing Interest and Competencies for Technology and Computing

Keck Building, Room 100
500 5th St., NW
Washington, DC

#STEMforCompTech

The Board on Science Education of the National Academies of Sciences, Engineering, and Medicine will host a public workshop on November 4, 2019 to explore issues in STEM education. The workshop will illustrate the various ways in which stakeholders define and conceptualize authentic STEM learning opportunities for young people in grades K-12 in formal and informal settings, and what that means for the goals, design, and implementation of such experiences. Presenters will unpack the state of the evidence on the role of authentic STEM learning opportunities and promising approaches and strategies in the development of interest and competencies for technology and computing fields. A recurring theme throughout the workshop will be implications for increasing diversity and access to authentic STEM learning experiences among underserved young people.
 
Confirmed Speakers:

• Lisa Brahms, Monshire Museum of Science (virtual)
• Loretta Cheeks, Strong TIES
• Tamara Clegg, University of Maryland
• Jill Denner, ETR
• Ron Eglash, University of Michigan
• Sonia Koshy, Kapor Center
• Keliann LaConte, Space Science Institute (virtual)
• Amon Millner, Olin College
• Kylie Peppler, University of California, Irvine
• Jean Ryoo, University of California, Los Angeles
• Emmanuel Schanzer, Bootstrap
• Shirin Vossoughi, Northwestern University (virtual)
• David Weintrop, University of Maryland

Questions? Email us at STEMforCompTech@nas.edu

Come talk about the Role of Authentic STEM Learning Experiences in Developing Interest and Competencies for Technology and Computing #STEMforCompTech

I’m on a National Academies committee to write a report about the role of authentic STEM learning experiences in promoting interest and ability in computing.  We’re having an open meeting/workshop (I don’t really know what it’s about yet) in November in DC. Visit this link for more information.

It Matters a Lot Who Teaches Introductory Courses if We Want Students to Continue

Thanks to Gary Stager who sent this link to me. The results mesh with Pat Alexander’s Model of Domain Learning. A true novice to a field is not going to pursue studies because of interest in the field — a novice doesn’t know the field. The novice is going to pursue studies because of social pressures, e.g., it’s a requirement for a degree or a job, it’s expected by family or community, or the teacher is motivating.  As the novice becomes an intermediate, interest in the domain can drive further study.  These studies suggest that persistence is more likely to happen if the teacher is a committed, full-time teacher.

The first professor whom students encounter in a discipline, evidence suggests, plays a big role in whether they continue in it.

On many campuses, teaching introductory courses typically falls to less-experienced instructors. Sometimes the task is assigned to instructors whose very connection to the college is tenuous. A growing body of evidence suggests that this tension could have negative consequences for students.

Two papers presented at the American Educational Research Association’s annual meeting in New York on Sunday support this idea.

The first finds that community-college students who take a remedial or introductory course with an adjunct instructor are less likely to take the next course in the sequence.

The second finds negative associations between the proportion of a four-year college’s faculty members who are part-time or off the tenure track and outcomes for STEM majors.

Source: It Matters a Lot Who Teaches Introductory Courses. Here’s Why.

Teaching the students isn’t the same as changing the culture: Dear Microsoft: absolutely not. by Monica Byrne

A powerful blog post from Monica Byrne with an important point. I blogged a while back that teaching women computer science doesn’t change how the industry might treat them.  Monica is saying something similar, but with a sharper point. I know I’ve heard from CS teachers who are worried about attracting more women into computing.  Are we putting them into a unpleasant situation by encouraging them to go into the computing industry?

Then—gotcha!—they’re shown a statistic that only 6.7% of women graduate with STEM degrees. They look crushed. The tagline? “Change the world. Stay in STEM.”

Are you f***ing kidding me?

Microsoft, where’s your ad campaign telling adult male scientists not to rape their colleagues in the field? Where’s the campaign telling them not to steal or take credit for women’s work? Or not to serially sexually harass their students? Not to discriminate against them? Not to ignore, dismiss, or fail to promote them at the same rate as men? Not to publish their work at a statistically significant lower rate?

Source: Dear Microsoft: absolutely not. | monica byrne

Increasing the Roles and Significance of Teachers in Policymaking for K-12 Engineering Education

National Academies have released a report that relates to the idea of Engineering for All.

Engineering is a small but growing part of K–12 education. Curricula that use the principles and practices of engineering are providing opportunities for elementary, middle, and high school students to design solutions to problems of immediate practical and societal importance. Professional development programs are showing teachers how to use engineering to engage students, to improve their learning of science, technology, engineering, and mathematics (STEM), and to spark their interest in engineering careers. However, many of the policies and practices that shape K–12 engineering education have not been fully or, in some cases, even marginally informed by the knowledge of teacher leaders.

To address the lack of teacher leadership in engineering education policymaking and how it might be mitigated as engineering education becomes more widespread in K–12 education in the United States, the National Academies of Sciences, Engineering, and Medicine held a convocation on September 30–October 1, 2016. Participants explored how strategic connections both within and outside classrooms and schools might catalyze new avenues of teacher preparation and professional development, integrated curriculum development, and more comprehensive assessment of knowledge, skills, and attitudes about engineering in the K–12 curriculum. This publication summarizes the presentations and discussions from the event.

Source: Increasing the Roles and Significance of Teachers in Policymaking for K-12 Engineering Education: Proceedings of a Convocation | The National Academies Press

Profile of Ruthe Farmer: This Is How You Advocate For Girls In STEM

Nice piece on fierce CS education advocate, Ruthe Farmer.

Big change is at the forefront of her thinking. When asked what cause she most wants to advance, she has a prompt and specific reply: “I am interested in advancing women at all levels.  For women’s rights to education, autonomy, personal safety to be a topic of debate [still] is atrocious. Now is the time for women to lead. I’m particularly concerned about the safety of women on campus.  Sexual assault should not be an expected part of the college experience. I refuse to accept that as a norm.”

Source: This Is How You Advocate For Girls In STEM

Report on Addressing Unconscious Bias in CS Classrooms

New research report available at http://services.google.com/fh/files/misc/unconscious-bias-in-the-classroom-report.pdf from with Google and Thomas Dee of Stanford University and Seth Gershenson from American University.

In sum, Unconscious Bias (UB) is a nontrivial problem in education, especially in CS and STEM education, and it is not easily addressed via traditional educational policies and interventions. However, interventions that identify and alter the frequently unconscious psychological processes that harm individuals’ outcomes are currently being developed and piloted. Teacher-facing interventions, which can be administered to both pre- and in-service teachers, are particularly promising. In part, this is because by addressing UB among teachers, we can help shape the entire classroom context in supportive ways. Furthermore, teacher-facing interventions are potentially cost-effective and scalable, because infrastructure for teacher training is already in place.

Embedding and Tailoring Engineering Learning: A Vision for the Future of Engineering Education

In the last couple of months, I have had the opportunity to speak to groups of Engineering Education Researchers. That doesn’t happen often to me, and I feel very fortunate to get that chance.

I was asked to speak about my vision for the future of Engineering Education, from my perspective as a Computing Education Researcher. What I said wasn’t wholly unique–there are Engineering Education Researchers who are already working on some of the items I described. The response suggested that it was at least an interesting vision, so I’m telling the story here in blog form.

For readers of this blog who may not be familiar with Engineering Education Research, the Wikipedia page on EER is pretty good.  The most useful paper I read is Borrego and and Bernhard’s “The Emergence of Engineering Education Research as an Internationally Connected Field of Inquiry.”  I also recommend looking around the Purdue Engineering Education department website, which is the oldest Eng Ed department in the US.

Engineering has had a long relationship with computing. Engineers made computing part of their practice earlier and more pervasively than scientists or mathematicians. I love how this is described in the motion picture Hidden Figures where Octavia Spencer’s character is part of the effort to use computing as soon as possible in the American space program. Engineering educators have made computing part of the learning goals for all of today’s engineering students, again more pervasively than what I can see in science or mathematics programs.

Much of my work and my students’ work is about embedding computing education (e.g., Media Computation which embeds computing in the digital media context that students value, or Brian Dorn’s work embedding computing in a graphic design context) and tailoring computing education (e.g., high school CS teachers need something different from software developers). Computing education can be embedded in Engineering classes and tailored for Engineering students, of course. My vision is about embedding and tailoring engineering education.

There are three parts to the story below:

• Engineering Education for everyone K-16, especially for STEM learners.
• Reaching a diverse audience for engineering education.
• Recognizing the differences between Engineering Education research and teaching, and the need for more research on learning outside of the engineering classroom.

In January 2016, President Barack Obama launched the “CS for All” initiative. When he said that he wanted students to be “job-ready,” he wasn’t saying that everyone should be a software engineer. Rather, he was reflecting a modern reality. For every professional software developer, there are four-to-nine end-user-programmers (depending on the study and how you count). Most professionals will likely use some form of programming in the future. That’s an argument for “CS for All.”

We also need Engineering for All. Engineering skills like designing, planning, collaboration on diverse teams, and trouble-shooting are needed across STEM. When I look at bench science, I see the need for engineering — to design, plan, collaborate, debug, and test.

Engineering education researchers know a lot about how to teach those skills. I’d love to learn how to inculcate some engineering perspectives in my CS students. When I see Chemical Engineering students designing a plant, or Civil Engineering students designing a bridge, they predict that they made mistakes, and they look for those mistakes. There’s a humility about their process. CS students often run their program once and turn them in. If you write a hundred lines of code, odds are almost 100% that you made errors. How do we get CS students to think that way?

Engineering for All is different than what professional engineers do, in the same way that what a high school teacher needs is different than what a professional software developer needs. Both need a mental model of the notional machine. A high school teacher also needs to know how students get that wrong, and probably doesn’t need to know about Scrum or GitHub.

I believe that there is a tailored part of engineering education which should be embedded throughout K-16 STEM. The American Society of Engineering Education’s mission is focused on professional engineers, and my proposal does not diminish the importance of that goal. We need more professional engineers, and we need to educate them well. But engineering skills and practices are too important to teach only to the professionals.

Engineering should play a significant role in STEM education policy. Engineering education researchers should own that “E” in STEM. There are many research questions that we have to answer in order to achieve Engineering for All.

• What is the tailored subset of engineering that should be taught to everyone? To STEM learners?
• All technically literate US citizens should know far more about engineering than they do today. Here’s a hypothesis: If all US citizens understood what engineering is and what engineers do, we might have less crumbling infrastructure, because we citizens would know that infrastructure is critical and professional engineers design, build, and maintain infrastructure. How do we get there?
• All K-12 students should have the opportunity to fall in love with engineering. How?
• Are there limits to what we can teach about engineering in K-16? What learning and cognitive disabilities interfere with learning engineering, and what parts of engineering? I also wonder about the kinds of bias that prevent someone from succeeding in engineering, besides race and gender. For example, here in the South, there are a lot of students who don’t believe in evolution. I’m pretty sure that belief in evolution isn’t necessary for designing a bridge or a distillation column. But someone who believes in intelligent design is going to face a lot of barriers to getting through basic science to become an engineer. Is that how it should be?
• Engineering should aim to influence K-12 STEM education nationally, in every state.

The American University (particularly the Land Grant University, developed in the late 1800’s) was supposed to blend the German University focus on research and the British focus on undergraduate education. My favorite history of that story is Larry Cuban’s How Scholars Trumped Teachers, but Michael Crow also tells the story well in his book Designing the New American University. We believed that there were synergies between research and teaching. It’s not clear that that’s true.

Research and teaching have different measures of success and don’t feed directly into one another.

Teaching should be measured in terms of student success and at what cost. Cost is always a factor in education. We know from Bloom’s two-sigma 1984 study (and all the follow-ups and replications) that the best education is an individual human tutor for each subject who works with a student to mastery. But we as a society can’t afford that. Everything else we do is a trade-off — we are trying to optimize learning for the cost that we are willing to bear.

Research should be measured in terms of impact — on outcomes, on the research community, on society.

It’s quite likely that the education research on a given campus doesn’t influence teaching practice on the same campus.

I see that in my own work.

• The best of Media Computation is no longer at Georgia Tech. Beth Simon and Leo Porter at UC San Diego have done better studies and are inventing cool interventions like MediaComp art galleries. Cynthia Lee at Stanford has created MediaComp for multiple languages. Celine Latulipe built on Beth and Leo’s work to implement lightweight teams in her MediaComp course.
• Subgoal labeling totally works (see Lauren’s dissertation or Briana’s dissertation). Coursera uses it in some of their videos. Rob Miler at MIT has picked it up. But there are very few CS classes using it.

We can see the transition for education research idea to impact in teaching practice as an adoption curve. Boyer’s “Scholarship Reconsidered” helps to explain what’s going on and how to support the adoption. There is traditional Scholarship of Discovery, the research that figures out something new. There is Scholarship of Teaching that studies the practice of teaching and learning.

Then there’s Scholarship of Application, which takes results from Discovery into something that teachers can use. We can’t expect research to influence teaching without scholars of application. Someone has to take the good ideas and carry them into practice. Someone has to figure out what practitioners want and need and match it to existing research insights. Done well, scholarship of application should also inform researchers about the open research questions, the challenges yet to be faced.

High-quality teaching for engineering education should use the most effective evidence-based teaching methods.

Good teachers balance teaching for relevance and motivation with teaching for understanding. This is hard to do well. Students want authenticity. They want project-based learning and design. I was at the University of Michigan as project-based learning for science education was first being developed, and we knew that it very often didn’t work. It’s often too complex and leads to failure, in both the project and the learning. Direct instruction is much more efficient for learning, but misses out on the components that inspire, motivate, and engage students. We have to balance these out.

We have to teach for a diverse population of students, which means teaching differently to attract women and members of under-represented groups. In our ICER 2012 paper, we found that encouragement and self-perception of ability are equally important for white and Asian males in terms of intention to persist in computing, but for women and under-represented group students, encouragement matters more than ability in terms of how satisfied they are with computing and intention to persist. This result has been replicated by others. Encouragement of individual students is critical to reach a diverse audience.

An important goal for a first year Engineering program is to explain the relevance of the classes that they’re taking. Larry Cuban tells us that a piece of the British system that got lost by the early 1920’s in the American University was having faculty advisors who would explain how all the classes fit together for a goal. The research on common first year Engineering courses (e.g., merging Physics, Calculus, Engineering in a big 12 credit hour course) shows that they worked because they explained the relevance of courses like Calculus to Engineering students. I know from my work that relevance is critical for retention and transfer.

Do students see relevance of first year Engineering programs? Most first year programs emphasize design and team problem-solving. First year Engineering students don’t know what engineers do. When they’re told “This is Engineering” in their first year, do they believe it? Do they cognitively index it as “real Engineering”? Do they remember those experiences and that learning in their 3rd and 4th years when they are in the relevant classes? I hope so, but I don’t know of evidence that shows us that they do.

Engineering education research, like most discipline-based education research (DBER), is focused on education. I see the study of “education” as being about implementation in a formal system. Education is a design discipline, one of Simon’s Sciences of the Artificial. Robert Glaser referred to education as psychology engineering.

We need more research on Engineering Learning. How do students learn engineering skills and practices, even outside of Engineering classes? How do those practices develop, even if it’s STEM learners and teachers using them and not professional engineers? How should we best teach engineering even if it’s not currently feasible?

That last part is much of what drives my work these days. We’re learning a lot about how great Parsons Problems are for learning CS. Very few CS classes use them. There are reasons why they don’t (e.g., they’re emphasizing the project side of the education spectrum). I’m figuring out how to teach CS well, even if it’s not feasible in current practice. CS teaching practice will eventually hit a paradigm shift, and I’ll have evidence-based practices to offer.

To focus on engineering learning requires work outside the classroom, like Multi-Institutional, Multi-National (MIMN) studies that we use in computing education research, or even laboratory studies. A focus on Engineering Learning creates new opportunities for funding, for audience, and for impact. For example, I could imagine engineering education researchers seeking science education funding to figure out how to teach high school science teachers the engineering that they ought to teach their students — not to introduce engineering, but to make their students better in science.

My vision for engineering education has three parts:

1. K-16 STEM learners need Engineering for All. Engineering education has more to contribute than just for producing more professional Engineers. Engineering education ought to own the “E” in STEM education policy. Engineering skills and practices can be tailored to different audiences and embedded in STEM education.
2. Reaching a diverse audience is critical for both research and teaching. For me, that diversity includes the people who need engineering education who aren’t going to become professional engineers, but also people who look different or even have different beliefs.
3. Finally, research and teaching are different activities, with different measures of success. Teaching should be informed by evidence and be as efficient and effective as possible for a given cost. We need evidence for what we’re doing, and we should gather evidence if we don’t know if what we’re doing is working. Research should focus on what’s possible and on having impact, even if that impact isn’t in the on-campus classrooms. We shouldn’t expect research to impact teaching without explicit investment in adaptation to support adoption.

(Thanks to Barb Ericson, Beth Simon, Leo Porter, and Wendy Newstetter for advice on drafts of this piece.)

Highlighting NSF STEM Education Showcase Videos

Last month, NSF hosted a STEM Education video showcase.  I was surprised at how much I enjoyed and learned from these.  They’re only 3 minutes each, so it’s a brief investment in getting a sense of a project — and there are a lot of interesting projects here.  Here are some of my notes on what I found that was cool:

• You can find the CS education videos here, but there’s a lot more relevant stuff beyond that category, like the videos on integrating STEM and CS.
• Jill Denner’s video on the Digital NEST changed my mind about the role of informal education in broadening participation in computing.  I’ve worried that afterschool computer clubs and MakerSpaces are mostly for the privileged (as in this blog post).  Jill’s video was a compelling picture Hispanic/Latino/a youth in technology education.
• Learning scientists are increasingly exploring the role of embodiment in learning.  The project on integrating dance and CS was the first example that I’ve seen in how to do this in CS  — exciting work!
• I was pleased to see Sarah Wille’s work on providing computing education to students with learning disabilities.  It’s a really important area that we need for CS for All.  I have worked with Sarah on BASICS and didn’t know about this project.
• Celine Latulipe had a video on her lightweight teams that she uses in a Media Computation class (yay!) which is a short version of her SIGCSE 2016 paper.
• Sara Dunton did a great job organizing the ECEP video.

There are a lot more great videos, but I’ll stop there.  Highly recommended viewing!

Motivating STEM Engagement in Children, Families, and Communities

I’ve known Dan Hickey for many years, and got to spend some time with him at Indiana when I visited there a couple years ago.  He’s dealing with an issue in this blog post that is critical to CS Education.  If we want students to value computing, it has to be valued and promoted in their families and communities.  How do we get engagement at a beyond-school level in computing education?

These issues of trajectories and non-participation in STEM learning have personal relevance for me and my own family. I was quite pleased a few years ago when my son Lucas enrolled in a computer programming class in high school. I never learned to program myself and these days it I find it quite a handicap. While I bought an Apple II+ computer in 1982 (!) and taught myself BASIC, an instructional technology professor discouraged me from delving too deeply into technology or programming (because “it changes too often”). While I still want to learn how to code, my non-participation in programming clearly helped define my trajectory towards a Ph.D in Psychology and satisfying career as a Learning Scientist.Unfortunately, the curriculum in my son’s programming class was like the typical secondary computer science instruction that Mark Guzdial chronicles in his Computing Education blog. The coding worksheets seemed to have been haphazardly created to match various videos located on the web. My son wanted to use the much more professional videos and exercises that we were able to access via my university’s account at Lynda.com, but his teacher insisted that my son complete the worksheets as well (so teacher could grade them).

Source: re-mediating assessment: Motivating STEM Engagement in Children, Families, and Communities

Two weeks in Germany: Human-centered software development and STEM Ed PhD students and Risk

I’m leaving May 24 for a two week trip to Germany. Both one week parts are interesting and worth talking about here. I’ve been reflecting on my own thinking on the piece between, and how it relates to computing education themes, too.

I’m attending a seminar at Schloss Dagstuhl on Human-Centric Development of Software Tools (see seminar page here). Two of the seminar leaders are Shriram Krishnamurthi of Bootstrap fame who is a frequent visitor and even a guest blogger here (see post here) and Amy Ko whose seminal work with Michael Lee on Gidget has been mentioned here several times (for example here). I’ve only been to Dagstuhl once before at the live-coding seminar (see description here) which was fantastic and has influenced my thinking literally years later. The seminar next week has me in the relative-outsider role that I was at the live-coding seminar. Most of the researchers coming to this event are programming language and software engineering researchers. Only a handful of us are social scientists or education researchers.

The Dagstuhl seminar ends Thursday after lunch. Saturday night, I’m to meet up with a group in Oldenburg Germany and then head up Sunday to Stadland (near the North Sea) for a workshop where I will be advising STEM Education PhD students. I don’t have a web link to the workshop, but I do have a page about the program I’ll be participating in — see here. My only contact there is Ira Diethelm, whom I’ve met several times and saw most recently at WIPSCE 2014 in Berlin (see trip report here). I really don’t know what to expect. Through the ICER DC and WIPSCE, I’ve been impressed by the Computing Education PhD students I’ve met in Germany, so I look forward to an interesting time. I come back home on Friday June 5 from Bremen.

There’s a couple day gap between the two events, from Thursday noon to Saturday evening. I got a bunch of advice on what to do on holiday. Shriram gave me the excellent advice of taking a boat cruise partway north, stopping at cities along the way, and then finishing up with a train on Saturday. Others suggested that I go to Cologne, Bremen, Luxembourg, or even Brussels.

I’ve decided to take a taxi to Trier from Dagstuhl, tour around there for a couple days, then take a seven hour train ride north on Saturday. Trier looks really interesting (see Tripadvisor page), though probably not as cool as a boat ride.

Why did I take the safer route?

The science writer, Kayt Sukel, was a once student of mine at Georgia Tech — we even have a pub together. I am so pleased to see the attention she’s received for her book Dirty Minds/This is Your Brain on Sex. She has a new book coming out on risk, and that’s had me thinking more about the role of risk in computing education.

In my research group, we often refer to Eccles model of academic achievement and decision making (1983), pictured below. It describes how students’ academic decisions consider issues like gender roles and stereotypes (e.g., do people who are like me do this?), expectation for success (e.g., can I succeed at this?), and the utility function (e.g., will this academic choice be fun? useful? money-making?). It’s a powerful model for thinking about why women and under-represented minorities don’t take computer science.

Eccles’ model doesn’t say much about risk. What happens if I don’t succeed? What do I need to do to reduce risk? How will I manage if I fail?  How much am I willing to suffer/pay for reduced risk?

That’s certainly playing into my thinking about my in-between days in Germany. I don’t speak German. If I get into trouble in those in-between days, I know nobody I could call for help. I still have another week of a workshop with a keynote presentation after my couple days break. I’ve already booked a hotel in Trier. I plan on walking around and taking pictures, and then I will take a train (which I’ve already booked, with Shriram’s help) to Oldenburg on Saturday. A boat ride with hops into cities sounds terrific, but more difficult to plan with many more opportunities for error (e.g., lost luggage, pickpockets). That’s managing risk for me.

I hear issues of risk coming into students’ decision-making processes all the time, combined with the other factors included in Eccles’ model. My daughter is pursuing pre-med studies. She’s thinking like many other pre-med students, “What undergrad degree do I get now that will be useful even if I don’t get into med school?” She tried computer science for one semester, as Jeanette Wing recommended in her famous article on Computational Thinking: “One can major in computer science and go on to a career in medicine, law, business, politics, any type of science or engineering, and even the arts.” CS would clearly be a good fallback undergraduate degree. She was well-prepared for CS — she had passed the AP CS exam in high school, and was top of her engineering CS1 in MATLAB class.  After one semester in CS for CS majors, my daughter hated it, especially the intense focus on enforced software development practices (e.g., losing points on homework for indenting with tabs rather than spaces) and the arrogant undergraduate teaching assistants. (She used more descriptive language.) Her class was particularly unfriendly to women and members of under-represented groups (a story I told here). She now rejects the CS classroom culture, the “defensive climate” (re: Barker and Garvin-Doxas). She never wants to take another CS course. The value of a CS degree in reducing risks on a pre-med path does not outweigh the costs of CS classes for her. She’s now pursuing psychology, which has a different risk/benefit calculation (i.e., a psychology undergraduate degree is not as valuable in the marketplace as a CS undergraduate degree), but has reduced costs compared to CS or biology.

Risk is certainly a factor when students are considering computer science. Students have expectations about potential costs, potential benefits, and about what could go wrong. I read it in my students’ comments after the Media Computation course.  “The course was not what I expected! I was expecting it to be much harder.” “I took a light load this semester so that I’d be ready for this.”  Sometimes, I’m quite sure, the risk calculation comes out against us, and we never see those students.

The blog will keep going while I’m gone — we’re queued up for weeks. I may not be able to respond much to comments in the meantime, though.

Male- and female-dominated fields | Gas station without pumps

Interesting post on how STEM isn’t all male-dominant, but Engineering and CS are SO male dominant, it shifts the average.

Computer science is a particularly strange case, as it has seen more fluctuation both in raw numbers of students data not shown here and gender balance than any other field. Other fields have seen large shifts in gender balance, but they have generally been gradual and nearly monotonic—not reversing course in the early 1980s.  It seems to me that the biggest drops in the ratio of women in CS came at times when the overall number of students in CS was dropping like after the dot-com bubble burst in the 2000.  When CS grew, the number of women grew faster than the number of men.  When CS shrunk, the number of women shrunk faster than the men.  Perhaps if CS education had had a steady growth, rather than the boom-and-bust cycles that have plagued it since the late 1970s, it would not have had such a mysterious rise and fall in proportion of women in the field. The boom-and-bust cycles are not driven by the real need for CS degrees, but by media hype about relatively small shortages or excesses of personnel.  I believe that the demand for CS degrees has been stabler than the supply unlike most other fields, where the supply has been steady even as demand has fluctuated.

via Male- and female-dominated fields | Gas station without pumps.

Gesture interfaces can convey scale better than fixed diagrams

The title on the post linked below is wrong, “Can iPads help students learn science? Yes, study shows.”  It’s never whether a technology can help learning. It’s how it can help, and what it can help with.  The study described is a great example of this.

iPads can be used really badly (while also being quite expensive) in schools.  Philip Sadler’s new study shows that students can use the gesture-based interface of the iPad to understand issues of scale (just how far is the Moon from the Earth?) better than any diagram can convey.

They found that while the traditional approaches produced no evident gain in understanding, the iPad classrooms showed strong gains. Students similarly struggle with concepts of scale when learning ideas in biology, chemistry, physics, and geology, which suggests that iPad-based simulations also may be beneficial for teaching concepts in many other scientific fields beyond astronomy.

Moreover, student understanding improved with as little as 20 minutes of iPad use. Guided instruction could produce even more dramatic and rapid gains in student comprehension.

“While it may seem obvious that hands-on use of computer simulations that accurately portray scale would lead to better understanding,” says Philip Sadler, a co-author of the study, “we don’t generally teach that way.” All too often, instruction makes use of models and drawings that distort the scale of the universe, “and this leads to misconceptions.”

via Can iPads help students learn science? Yes, study shows.

Colleges Fight to Retain Interest of STEM Majors: Computing, too

This is our problem in computing, too.  If students have never seen a computer science course before coming to college, they won’t know what hits them when they walk in the door.

Experts estimate that less than 40 percent of students who enter college as STEM majors actually wind up earning a degree in science, technology, engineering or math.

Those who don’t make it to the finish line typically change course early on. Just ask Mallory Hytes Hagan, better known as Miss America 2013.

Hagan enrolled at Auburn University as a biomedical science major, but transferred to the Fashion Institute of Technology a year later to pursue a career in cosmetics and fragrance marketing.

“I found out I wasn’t as prepared as I should be,” Hagan said during a panel discussion today at the 2013 U.S. News STEM Solutions conference in Austin. “I hit that first chem lab and thought, ‘Whoa. What’s going on?'”

via Colleges Fight to Retain Interest of STEM Majors – US News and World Report.