Posts tagged ‘teaching’
Carl Wieman on Effective Teaching
This is a really nice piece on a lecture by Carl Wieman, whom I have mentioned previously. In one page, the summary hits most of the key ideas in How People Learn.
“Memory is not talked about much in education, but it is critically important,” Wieman said, and the limited discussion that does occur focuses primarily on long-term memory while short-term working memory is ignored.
He compared the latter to a personal computer with limited RAM. “The more it is called upon to do, to remember, the harder it is to process. The average human brain [working memory] has a limit of five to six new items, it can’t handle anything more.”
A new item is anything that is not in the learner’s long-term memory, he continued. “Anything you can do to reduce unnecessary demands on working memory will improve learning.”
Among them is elimination of unnecessary jargon. Wieman asked: “That new jargon term that is so convenient to you, is it really worth using up 20% of the mental processing capacity of the students for that class period?” Demands of working memory can also be reduced by shifting some learning tasks, particularly transfer of simple information from the classroom to pre-reading assignments and homework.
Doubts of my students: Expert teaching is no better than good-enough teaching
Teaching is a great job. I particularly appreciate how teaching keeps me thinking and questioning, which is particularly important for an education researcher. I’m teaching two classes this semester. I’ve mentioned recently how my data structures class has me thinking about new kinds of practice activities.
I am also teaching a course on educational technology, where we’re reading How People Learn. Chapter 7 is a fascinating read with three detailed accounts of high-quality learning environments with expert teachers, one each in history, mathematics, and science. The chapter includes some strong claims about teaching:
The interplay between content knowledge and pedagogical content knowledge illustrated in this chapter contradicts a commonly held misconception about teaching–that effective teaching consists of a set of general teaching strategies that apply to all content areas. This notion is erroneous….These examples provide glimpses of outstanding teaching in the disci- pline of history. The examples do not come from “gifted teachers” who know how to teach anything: they demonstrate, instead, that expert teachers have a deep understanding of the structure and epistemologies of their disciplines, combined with knowledge of the kinds of teaching activities that will help students come to understand the discipline for themselves. As we previously noted, this point sharply contradicts one of the popular—and dangerous—myths about teaching: teaching is a generic skill and a good teacher can teach any subject.
We had a great discussion in class about this last night. HPL is claiming that an expert teacher has (1) discipline knowledge, (2) understanding about teaching and learning, (3) understanding of conceptual barriers that students face in the discipline, and (4) a set of effective strategies for addressing those conceptual barriers. (3) and (4) on that list is what we call pedagogical content knowledge, discipline-specific knowledge for how to teach that discipline. My students don’t argue that CS PCK (pedagogical content knowledge about teaching CS) doesn’t exist. They just argue that it’s not necessary to be “effective.”
It may be a “dangerous myth” but my students cling to it pretty stubbornly. “If you know the content, and you know about how people learn, then you can teach that content. You may not be as good as a teacher with years of experience, but you’re good enough.” That’s almost an exact quote from one of the students in my class last night. I tried to argue that, not only is it better to have CS PCK, but we can also teach CS PCK, so that a first year teacher can be much more effective than a brand new teacher who doesn’t know anything about student problems or teaching strategies. They pushed back. “How much more does PCK contribute to being a good teacher, beyond just knowledge of the discipline and knowledge of learning sciences?” Since I don’t know how to measure knowledge of CS well, nor how to measure CS PCK, I have two unknowns, so I can’t really answer the question.
One way of interpreting my students’ comments is sheer hubris. These are young, smart Georgia Tech undergrads (and a smattering of grad students). In their minds, they are intellectually invulnerable, able to tackle any academic challenge, and certainly better than any teacher from a school of education. Several of them mentioned Teach for America in their comments, an organization whose existence encourages them to think that teaching is not so hard. Maybe their comments also are the thoughts of expert learners — these students have had to teach themselves often, so they don’t see expert teaching as a necessity.
Another way of interpreting my students’ comments which is much more intellectually challenging is that the difference between an effective and expert teacher is hard to see. A recent NYTimes article speaks to the enormous value of expert teachers — over a student’s lifetime. Barbara has pointed out that, in her experience, the first year that a teacher teaches AP CS, none of his or her students will pass the AP CS (with a score of 3 or better). Even some veteran teachers have few test-passers, but all the teachers who get many test-passers are veterans with real teaching expertise. But how do you make those successes visible? As we’ve talked about here before: How do we measure good teaching?
As a teacher of education research, I wasn’t so successful yesterday. I failed at convincing my class (at least, a vocal group of students in my class) that there is some value in expert teaching, that it’s something to be developed and valued. What I worry is that these are not just the thoughts of a few undergraduates. How many more people think that it’s easy to learn to be a teacher? How many other adults, voting citizens, even members of school boards agree with my students — that expert teaching is not that much better than effective teaching, so hiring a bunch of young, smart kids to teach is good enough?
Quality of Homework matters, if quality matters
Students doing more homework isn’t as effective for student learning. Homework can influence learning, if it’s quality homework. But if quality of learning is not the outcome variable that we care about, then homework is not an issue. We can just have students watch videos instead.
The quantity of students’ homework is a lot less important than its quality. And evidence suggests that as of now, homework isn’t making the grade. Although surveys show that the amount of time our children spend on homework has risen over the last three decades, American students are mired in the middle of international academic rankings: 17th in reading, 23rd in science and 31st in math, according to results from the Program for International Student Assessment released last December.
In a 2008 survey, one-third of parents polled rated the quality of their children’s homework assignments as fair or poor, and 4 in 10 said they believed that some or a great deal of homework was busywork. A new study, coming in the Economics of Education Review, reports that homework in science, English and history has “little to no impact” on student test scores. (The authors did note a positive effect for math homework.) Enriching children’s classroom learning requires making homework not shorter or longer, but smarter.
Fortunately, research is available to help parents, teachers and school administrators do just that. In recent years, neuroscientists, cognitive scientists and educational psychologists have made a series of remarkable discoveries about how the human brain learns. They have founded a new discipline, known as Mind, Brain and Education, that is devoted to understanding and improving the ways in which children absorb, retain and apply knowledge.
Teaching-Oriented Faculty at Research Universities
Thanks to the team that put this together! I’m glad to see this finally get published — a discussion of the issues, challenges, and benefits of having teaching-track faculty at research-focused institutions.
Teaching-Oriented Faculty at Research Universities
Nine teacher-oriented faculty in computer science departments at research universities in the U.S. or Canada describe how their positions work, how they contribute to education, and how departmental policies can influence their success and satisfaction.
via Teaching-Oriented Faculty at Research Universities | November 2011 | Communications of the ACM.
Slow pace of higher-ed reform costs STEM majors: CS needs context
The argument being made here in this NYTimes piece suggests that the sluggish response to calls for higher-education reform has a real cost. We know how to make STEM classes more successful, in terms of motivation and learning, but higher-education institutions are not willing to change.
What does this mean for Computing Education? How do we avoid being “too narrow” and having a “sink or swim” mentality? We are encouraged to have CS education that has “passion” and includes “design projects for Freshmen.” Sounds to me that contextualized computing education, which includes efforts like Media Computation and robotics, is the kind of thing they’re encouraging.
No one doubts that students need a strong theoretical foundation. But what frustrates education experts is how long it has taken for most schools to make changes.
The National Science Board, a public advisory body, warned in the mid-1980s that students were losing sight of why they wanted to be scientists and engineers in the first place. Research confirmed in the 1990s that students learn more by grappling with open-ended problems, like creating a computer game or designing an alternative energy system, than listening to lectures. While the National Science Foundation went on to finance pilot courses that employed interactive projects, when the money dried up, so did most of the courses. Lecture classes are far cheaper to produce, and top professors are focused on bringing in research grants, not teaching undergraduates.
In 2005, the National Academy of Engineering concluded that “scattered interventions” had not resulted in widespread change. “Treating the freshman year as a ‘sink or swim’ experience and accepting attrition as inevitable,” it said, “is both unfair to students and wasteful of resources and faculty time.”
via Why Science Majors Change Their Minds (It’s Just So Darn Hard) – NYTimes.com.
Does economic inequality in a nation influence cheating in computing class?
I recently watched this TED talk, and it’s been influencing my thinking a lot over the last week. I don’t often follow links to TED talks, but I’m really glad that I did on this one. It’s by Richard Wilkinson on how income inequality in a country influences social good.
Wilkinson looks at a variety of social good variables, from number of prisoners per 100K citizens (above), to amount of trust in a society, to number of violent crimes. He finds no correlation between the gross domestic product per capita and these social goods — richer and poorer countries have these problems. But then, he creates a new index: a social inequality index. He takes the gross domestic product per capita in the top quintile of the country, and divides it by the GDP/capita in the bottom quintile.
The social good variables completely correlate with the inequality index, as you can see from the screen cap on prison populations. Watch the video. He suggests that what leads to social unrest is not the wealth, but the gap between the wealthiest and the poorest in a given society.
I wonder if this has any implications for we computing educators. I was particularly struck with the close correlation between trust and inequality. One of our rampant problems is cheating. I don’t know any multinational studies of cheating. Do students cheat less in countries where there is less inequality? Do you cheat more if you think that the system is stacked against you, and you need an edge to get ahead of the competition? Note that Wilkinson’s data does explain differences between US States and Canadian provinces. (I also note sadly that Atlanta was just judged by the US Census as being one of the most inequitable cities in the country.)
The university versus the faculty — who reaps invention’s rewards?
I’ve heard the argument that the Bayh-Doyle act was the downfall of undergraduate education in America. By allowing universities to keep the intellectual property rights to sponsored research, an enormous incentive was created for universities to push faculty into research, and away from education. A recent Supreme Court ruling may have placed a limit on the Bayh-Doyle Act, by ruling that an individual researcher’s rights supersede the university’s. The New York Times editorial linked below is disappointed by this ruling, predicting increased tension between universities and faculty.
Looking for a silver lining, I wonder if this ruling might not create the opportunity to get back to education. Rich DeMillo continues to point out in his blog how research is a losing proposition for universities. Could this ruling reduce the incentive for universities to push research, by raising the costs (and lowering the potential benefits) of faculty research? (Rich’s latest blog post on the point directly addresses the nay-sayers who say that research only makes money for universities — a recommended and compelling read.)
Although the decision is based on a literal reading of a poorly drafted initial agreement between Stanford and the researcher, it is likely to have a broader effect. It could change the culture of research universities by requiring them to be far more vigilant in obtaining ironclad assignments from faculty members and monitoring any contracts between researchers and private companies. Relationships between the university and its faculty are likely to become more legalistic and more mercantile. By stressing “the general rule that rights in an invention belong to the inventor,” the majority opinion of Chief Justice John Roberts Jr. romanticizes the role of the solo inventor. It fails to acknowledge the Bayh-Dole Act’s importance in fostering collaborative enterprises and its substantial benefit to the American economy.
Teaching and research can co-exist
An interesting study that’s going to fuel the claims that faculty don’t do enough work — 20% of UT-Austin’s faculty teach 57% of student credit hours. That’s understandable. Graduate classes are small, and first-year undergrad classes are huge. It’s pretty easy for a small number of faculty to rack up most of the credit hours.
It’s the later stats that I found more surprising — those teaching the most still brought in their fair share of research funding.
But the study suggests that research and teaching can easily coexist. It found that the 20 percent of faculty with the heaviest teaching loads generated 18 percent of UT’s research funding, meaning that they remained competitive in research even as they carried more than their share of teaching duties.
“This suggests that these faculty are not jeopardizing their status as researchers by assuming such a high level of teaching responsibility,” the study states.
The least productive 20 percent of faculty teach just 2 percent of all student credit hours at UT — meaning that students barely see them.
Research grants at UT go overwhelmingly to a small group of faculty. Two percent of faculty are responsible for 57 percent of research, and 20 percent are responsible for 99.8 percent.
via Study: One-fifth of faculty does most of the work – College, Inc. – The Washington Post.
Billion$ aren’t enough to improve schools
Money isn’t enough to improve schools. That’s probably obvious, though it’s interesting to see that somebody did the work to provide evidence. When I see what other countries do to improve their education quality, I realize how much of the education picture has to do with culture and respect, and money doesn’t help with that.
In the first-of-its-kind analysis of the billionaires’ efforts, NEWSWEEK and the Center for Public Integrity crunched the numbers on graduation rates and test scores in 10 major urban districts—from New York City to Oakland—which got windfalls from these four top philanthropists.
The results, though mixed, are dispiriting proof that money alone can’t repair the desperate state of urban education. For all the millions spent on reforms, nine of the 10 school districts studied substantially trailed their state’s proficiency and graduation rates—often by 10 points or more. That’s not to say that the urban districts didn’t make gains.
The good news is many did improve and at a rate faster than their states 60 percent of the time—proof that the billionaires made some solid bets. But those spikes up weren’t enough to erase the deep gulf between poor, inner-city schools, where the big givers focused, and their suburban and rural counterparts.
Student evaluations of teaching don’t correlate with learning gains
The best part of this post from Hake comes at the end, where he cites six published accounts of dramatic improvement in learning with dramatic decline in student teaching evaluations. Administrators rely heavily on student evaluations of teaching, but the reality is, they don’t correlate with good teaching. Students don’t necessarily “like” teaching that makes them think.
Unfortunately for my academic career, I gradually caught on to the fact that students’ conceptual understanding of physics was not substantively increased by traditional pedagogy. As described in Hake (1987, 1991, 1992, 2002c) and Tobias & Hake (1988), I converted to the “Arons Advocated Method” [Hake (2004c)] of “interactive engagement.” This resulted in average normalized gains on the “Mechanics Diagnostic” test or “Force Concept Inventory” that ranged from 0.54 to 0.65 [Hake (1998b), Table 1c] as compared to the gain of about 0.2 typically obtained in traditional introductory mechanics courses [Hake (1998a)].
But my EPA’s for “overall evaluation of professor,” sometimes dipped to as low as 1.67 (C-), and never returned to the 3.38 high that I had garnered by using traditional ineffective methods of introductory physics instruction. My department chair and his executive committee, convinced by the likes of Peter Cohen (1981, 1990) that SET’s are valid measures of the cognitive impact of introductory courses, took a very dim view of both my teaching and my educational activities.
It’s in Science: Interaction beats Lecture
AP, Washington Post, NYTimes, and NPR covered this story this week — Carl Weiman has an article in Science showing that two grad students with an interactive learner-engagement method beats out a highly-rated veteran lecturer in terms of student learning in a large class. This is a cool piece, and I buy it — that’s why I’m doing peer-interaction in my class. I still believe that lecture can work, the evidence is strong that learner-engagement beats lecture, especially in large STEM classes. I think that this result is particularly disconcerting for the open learning movement. If lectures aren’t worth much for most learners, what is it that iTunes-U and MIT Open Courseware are offering?
Who’s better at teaching difficult physics to a class of more than 250 college students: the highly rated veteran professor using time-tested lecturing, or the inexperienced graduate students interacting with kids via devices that look like TV remotes? The answer could rattle ivy on college walls.
A study by Nobel Prize winning physicist Carl Wieman at the university found that students learned better from inexperienced teachers using an interactive method _ including the clicker _ than a veteran professor giving a traditional lecture. Student answers to questions and quizzes are displayed instantly on the professor’s presentation.
He found that in nearly identical classes, Canadian college students learned a lot more from teaching assistants using interactive tools than they did from a veteran professor giving a traditional lecture. The students who had to engage interactively using the TV remote-like devices scored about twice as high on a test compared to those who heard the normal lecture, according to a study published Thursday in the journal Science.
Struggling to Create the Mobile Campus
An interesting article in The Chronicle of Higher Education on how well Universities are using mobile technologies. I read the article as highlighting two particular problems of using the mobile technologies on-campus:
- First, getting enough wireless to all the students for all the gadgets. One example they cite: Duke scaled back their mobile technologies program, and has instead focused over the last 3 years in just getting wireless coverage over at least 95% of campus. The quote below highlights how students love their phones (presumably with 3G access), but the iPad hasn’t taken off because Stanford can’t keep up with the WiFi demands of all those iPads.
- Second, we’re still trying to figure out how best to use these technologies and how to sustain them. An interesting story in the article: Stanford built a cool 3-D, interactive map of the brain for the iPad, but then the prof who wanted it stopped teaching that course, and nobody else wants to use the iPad, so nobody is using the cool gadget now.
Stanford University, birthplace of Google, Yahoo, and Cisco, is surely one of the most tech-savvy campuses in the world. A survey last year of 200 iPhone-owning Stanford students portrayed them as digitally obsessed, even addicted. Most slept next to their phones. A quarter said their phones were “dangerously alluring.”
But when Stanford’s School of Medicine lent iPads to all new students last August, a curious thing happened: Many didn’t like using them in class. Officials had hoped to stop printing an annual average of 3,700 pages of course materials per medical student, encouraging them to use digital materials instead. Some students rebelled, and Stanford was forced to resume offering printed notes to those who wanted them. In most classes, half the students had stopped using their iPads only a few weeks into the term.
via The Slow-Motion Mobile Campus – The Digital Campus – The Chronicle of Higher Education.
How other countries develop their teachers
Wow. This blog post from Linda Darling-Hammond really paints an amazing picture. Could you imagine doing this in the United States? Can you imagine how much higher-quality our education would be, if we developed and paid teachers like we do doctors (which is how I read the below)? Imagine telling future high school CS teachers that they have to get the equivalent of an undergraduate degree in CS to teach before starting their teaching preparation — but they’ll be paid as well as a CS undergraduate entering industry. That could make a difference! It’s certainly an issue for our Operation: Reboot teachers, to have the same skills that they had as IT workers, but now receiving a teacher’s salary.
The contrasts to the American attitude toward teachers and teaching could not have been more stark. Officials from countries like Finland and Singapore described how they have built a high-performing teaching profession by enabling all of their teachers to enter high-quality preparation programs, generally at the masters’ degree level, where they receive a salary while they prepare. There they learn research-based teaching strategies and train with experts in model schools attached to their universities. They enter a well-paid profession – in Singapore earning as much as beginning doctors — where they are supported by mentor teachers and have 15 or more hours a week to work and learn together – engaging in shared planning, action research, lesson study, and observations in each other’s classrooms. And they work in schools that are equitably funded and well-resourced with the latest technology and materials.
In Singapore, based on their talents and interests, many teachers are encouraged to pursue career ladders to become master teachers, curriculum specialists, and principals, expanding their opportunities and their earnings with still more training paid for by the government. Teacher union members in these countries talked about how they work closely with their governments to further enrich teachers’ and school leaders’ learning opportunities and to strengthen their skills.
Motivating cognitive work with Pink’s Drive
A recent NYTimes article tells us that the Silicon Valley hunt for programming talent has hit a new high. An example carrot offered to new recruits at a new start-up (in the below article, but not quoted below) are classes on how to create their own start-up. The high salaries may be an effective sales pitch to draw new students into CS. But I think that the other items are the ones that will really inspire and motivate new hires.
My colleague Bill Leahy recently sent me the link to an RSanimate video of a Daniel Pink talk about “Drive: The surprising truth about what motivates us.” Pink says that, when seeking to motivate cognitive tasks, more money can back-fire. The role of money is just to take money off the table — it has to be “enough.” From then on, more cognitive effort is inspired by offering “Autonomy, Mastery, and Purpose.” Starting one’s own start-up is autonomy and gives one a purpose.
I wonder if Pink’s story also helps to explain why it’s so hard to get faculty to change how they teach. Being a professor is filled with “Autonomy, Mastery, and Purpose” — it’s a great job where you have enormous autonomy, you get to work on research problems that you think are worthwhile (“purpose”), and you have the time to develop mastery in your chosen sub-sub-field. But being a good teacher is about responding to the students’ needs, even if it’s kind of boring for you. You surrender some autonomy. Becoming a master teacher is worthwhile purpose, but that’s not necessarily the “purpose” that a new PhD graduate finds inspiring.
Computer whiz kids have long been prize hires in Silicon Valley. But these days tech companies are dreaming up new perks and incentives as the industry wages its fiercest war for talent in more than a decade.
Free meals, shuttle buses and stock options are de rigueur. So the game maker Zynga dangles free haircuts and iPads to recruits, who are also told that they can bring their dogs to work. Path, a photo-sharing site, moved its offices so it could offer sweeping views of the San Francisco Bay. At Instagram, another photo-sharing start-up, workers take personal food and drink orders from employees, fill them at Costco and keep the supplies on hand for lunches and snacks.
Then there are salaries. Google is paying computer science majors just out of college $90,000 to $105,000, as much as $20,000 more than it was paying a few months ago. That is so far above the industry average of $80,000 that start-ups cannot match Google salaries. Google declined to comment.
When test scores seem too good to believe – USATODAY.com
I’m glad that it’s not just Atlanta, but it’s still depressing. I guess that this is an example of two quotes that Richard Hake recently included in a post:
Dukenfield’s Law <http://bit.ly/bsRokM>: “If a thing is worth winning, it’s worth cheating for.”
Campbell’s Law <http://bit.ly/hMsyUr>: “The more any quantitative social indicator is used for social decision making, the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor.”
Such anomalies surfaced in Washington, D.C., and each of the states — Arizona, California, Colorado, Florida, Michigan and Ohio — where USA TODAY analyzed test scores. For each state, the newspaper obtained three to seven years’ worth of scores. There were another 317 examples of equally large, year-to-year declines in an entire grade’s scores.
USA TODAY used a methodology widely recognized by mathematicians, psychometricians and testing companies. It compared year-to-year changes in test scores and singled out grades within schools for which gains were 3 standard deviations or more from the average statewide gain on that test. In layman’s language, that means the students in that grade showed greater improvement than 99.9% of their classmates statewide.
via When test scores seem too good to believe – USATODAY.com.
Computing Ed Research - Guzdial's Take 
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