Posts tagged ‘teaching’
Here’s a repository for videos that teach computer science. Unlike Khan, it’s open to anyone to contribute. Unlike YouTube, it’s only about teaching CS.
TeachingTree is an open platform that lets anybody organize educational content. Our goal is for students to quickly access the exact clips they need in order to learn individual concepts. Everyone is encouraged to help by adding videos or tagging concepts.
via Teaching Tree.
What a great idea! Everybody who goes to University takes a test like the ACT or SAT. Simply give it to them again as they’re graduating! Now you have a measure of impact — the change between the entrance test and exit test is the value added by a University.
Seems simple, but it doesn’t work. Students have a huge incentive to do well on the entrance exam, but zero incentive to do well on the exit exam. A new study published in Education Researcher shows that the motivation really matters, and it calls into question the value of the Academically Adrift study that claimed that Colleges aren’t teaching much. How do you know, if students don’t really have any incentive to do well on the post-intervention exams?
To test the impact of motivation, the researchers randomly assigned students to groups that received different consent forms. One group of students received a consent form that indicated that their scores could be linked to them and (in theory) help them. “[Y]our test scores may be released to faculty in your college or to potential employers to evaluate your academic ability.” The researchers referred to those in this group as having received the “personal condition.” After the students took the test, and a survey, they were debriefed and told the truth, which was that their scores would be shared only with the research team.
The study found that those with a personal motivation did “significantly and consistently” better than other students — and reported in surveys a much higher level of motivation to take the test seriously. Likewise, these student groups with a personal stake in the tests showed higher gains in the test — such that if their collective scores were being used to evaluate learning at their college, the institution would have looked like it was teaching more effectively.
I agree with the post below which suggests that MOOCs misunderstand what a good teacher does–that’s what my post earlier was about. I’m not convinced that I agree with the author’s definition of what a teacher does. Yes, a good teacher does all those things described in the second paragraph below, but a key part of what a teacher does is to motivate the student to learn. Learning results from what the student does and thinks. It’s the teacher’s job to cajole, motivate, engage, and even infuriate the student so that he or she thinks about things in a new way and learns. In the end, it’s always about the student, and the most important thing a teacher does is to get the student to do something.
But even if Tabarrok’s model makes good economic sense, it makes bad education sense and misrepresents what genuine teaching is and what the “best” teachers actually do. For starters, unlike TED speakers, they don’t simply deliver lectures and profess. They also work with students to help them become better thinkers, readers, and writers. How?
Through personal attention (such as tutorials) and classroom interaction (such as discussions and the guided close reading of texts). By constantly testing their students’ minds against theirs, forcing them to ask the hard questions and to explain them with significant answers. And by giving them appropriate personalized feedback.
Seb Schmoller had a nice response to my Friday post, where he asked what it will take for MOOCs to engage the student and lead to the learning that a good teacher can achieve. He included a wonderful quote from Herb Simon which really captures the key idea:
“Learning results from what the student does and thinks, and only from what the student does and thinks. The teacher can advance learning only by influencing what the student does to learn.” – Herb Simon.
During break (e.g., multi-hour long car rides), I gave a lot of thought to MOOCs and the changes that are coming to higher education. I realized that people can only believe that MOOCs can replace existing higher-education classes if they misunderstand what a teacher does.
MOOCs (for the most part, as they are defined in Udacity, Coursera, and edX, and as defined at Wikipedia) provide lecture-like material (typically through videos). These are broken into small pieces, and are presented with interspersed mini-quizzes. There is additional homework. Feedback is provided, either canned (the system knows what’s right and wrong) or through peer-evaluation. There is typically some kind of forum for questions and answers, and is a key part of the connectivist MOOC for “nurturing and maintaining connections.”
So why isn’t this the same as a face-to-face higher education class?
- The main activity of a higher-education teacher is not to lecture. The main activity of a teacher is to orchestrate learning opportunities, to get students to do and think. A teacher does this most effectively by responding to the individuals in the class. I just got my student feedback on the prototyping course I taught in the Fall. What the students liked best was that I led discussions based on their questions and comments on the readings, and that I had stories and anecdotes in response to their queries. A teacher responds to the students, provides scaffolding, and helps the students increase their knowledge.
- A teacher is an expert at teaching the topic, and the teaching is dependent on the domain. Teaching is not a generalized skill. The most effective teachers have a lot of pedagogical content knowledge — they know how to teach the domain. The same general course structure is not as effective as a course structure aimed at the domain.
- The job of the teacher is to educate, not filter, and that includes motivating students. What’s the difference between a book and a University? You can learn from a book. Most students can’t learn as effectively on-their-own with a book as they can with a good teacher. Many self-taught learners who have only studied books lack a general overview of the field, and haven’t read the books that challenge and contradict the books that they have read and loved. A good teacher motivates students to keep going, explains why the topics are important, challenges students, points out where their understanding is lacking, and makes sure that they see more than one perspective on a topic.
If the only educated people in our society were the ones who wanted to learn (at the start, from the beginning of a class), our society would collapse. We would have too few educated workers to create innovations and maintain the technology we have. Our society depends on teachers who motivate students to persevere and learn.
There is evidence that MOOCs do not teach. We know that MOOCs have a low completion rate. What most people don’t realize is that the majority of those who complete already knew the content. MOOCs offer a one-size-fits-few model, unchanging between content domains, that does not change for individual students (I know that they hope that it will one day, but it doesn’t now), that filters and certifies those who can learn on their own. The role of education in society is to teach everyone, not just those auto-didacts who can learn in a MOOC.
Absolutely, it’s worth exploring how to make educational technology (including MOOCs) that provides learning opportunities where no teacher is available. Alan Kay encouraged us to think that way here in this blog. However, replacing good teachers with MOOCs reflects a deep misunderstanding of what a teacher does.
Please note that I am not arguing that MOOCs are bad technologies, or that they can’t be used to create wonderful learning environments. I am explicitly critiquing the use of MOOCs as a replacement for existing courses (with a good teacher), not MOOCs as a textbook or augmentation of existing courses.
How did we get to this point, that people are seriously talking about shutting down schools in favor of MOOCs? Maybe it’s because we in Universities haven’t done enough to recognize, value, and publicize good teaching. We haven’t done enough to tell people what we do well. MOOCs do what the external world thinks that University teachers do.
I was pleased to see an essay in Inside HigherEd from a computing education researcher, Orit Hazzan. I’ll be interested to see what happens with her new program, that seeks to create more STEM teachers from former STEM graduates. Here’s the part that I wonder about: Will a graduate with a potentially high-paying STEM degree (say, in CS) stay in teaching when offered a better paying job in industry? We’ve had relatively little luck making that work in Georgia.
To this end, Views invites Technion graduates back to the Technion to study toward an additional bachelor’s degree in its department of education in technology and science, which awards a teaching certificate for high school STEM subjects. Technion graduates enrolled in the Views program receive full study scholarships from the Technion for two years and are not required to commit themselves to teach in the education system. Extending the program over two academic years enables the graduates to continue working as scientists and engineers in industry in parallel to their studies (one day or two half-days each week).
Technion graduates are not required to commit themselves to teach in the education system since the knowledge they gain in the Views program is useful also in businesses, where teaching and learning processes are crucial for coping with new knowledge and technological developments on a daily basis. Thus, even if they decide not to switch to education, they will still contribute to Israel’s prosperity, but in a different way.
In its current, first year of operation (2011-12), the program started with 60 Technion graduates. Sixty percent of them are males – a fact that indicates that the Views program indeed attracts populations that traditionally do not choose education as their first choice, and who at the same time are attracted to the program.
AngryMath’s blog post on Udacity Statistics 101 (linked below) is detailed, compelling, and damning. It’s certainly not the best statistics course anywhere. But I have to wonder: Is it worse than average? It’s hard to teach statistics well (I really did try this last summer). It’s hard to teach anything well, and there’s evidence that we need to improve our teaching in computer science. This doesn’t feel like an indictment of MOOC courses overall.
In brief, here is my overall assessment: the course is amazingly, shockingly awful. It is poorly structured; it evidences an almost complete lack of planning for the lectures; it routinely fails to properly define or use standard terms or notation; it necessitates occasional massive gaps where “magic” happens; and it results in nonstandard computations that would not be accepted in normal statistical work. In surveying the course, some nights I personally got seriously depressed at the notion that this might be standard fare for the college lectures encountered by most students during their academic careers.
There’s a Facebook meme making the rounds:
I am no expert on management or leadership. A management expert may look at the above chart and shake her head sadly about the misconceptions of the commonsense view of management. Nonetheless, the chart sets up an interesting dichotomy that is worth exploring, in relation to academia and then to teaching.
The abrupt firing of President Teresa Sullivan from the University of Virginia raises questions about academic leadership and its goals. The below quote from a Slate article on her ouster suggests that she fit under the “Leader” column above:
The first year of Sullivan’s tenure involved hiring her own staff, provost, and administrative vice president. In her second year she had her team and set about reforming and streamlining the budget system, a process that promised to save money and clarify how money flows from one part of the university to another. This was her top priority. It was also the Board of Visitor’s top priority—at least at the time she was hired. Sullivan was rare among university presidents in that she managed to get every segment of the diverse community and varied stakeholders to buy in to her vision and plan. Everyone bought in, that is, except for a handful of very, very rich people, some of whom happen to be political appointees to the Board of Visitors. (emphasis added)
I have known academic leaders like this. Jim Foley is famous at Georgia Tech for generating consensus on issues. My current school chair (ending his term this month) does a good job of engaging faculty in conversations and listening — he doesn’t always agree, but faculty opinions have swayed his choices. Eugene Wallingford has written a good bit about how to live on the right side of the chart.
I am sure that all of us in academics have also met one or more academic bullies who land more often in the left column:
The self-righteous bully is a person who cannot accept that they could possibly be in the wrong. They are totally devoid of self-awareness and neither know nor care about the impact of their behaviour on other people. They are always right and others are always wrong. R. Namie and G. Namie (2009) described bullies as individuals who falsely believed they had more power than others did…They tend to have little empathy for the problems of the other person in the victim/bully relationship.
The bosses vs. leaders chart at the top of this post is about leadership, but it’s also about teaching. The common view of the undergraduate teacher veers toward the “boss” and “bully” characterizations above. We are “authorities.” The education jobs in academia are often called “Lecturers” or “Professors.” We lecture or profess to students — we tell them, we don’t ask them. We “command” students to complete assignments. We strive to make our lectures “always right.”
The best teachers look more like the right side of the chart at the top. From what we know about learning and teaching, a good teacher does “build consensus.” We don’t want to just talk at students — we want students to believe us and buy into a new understanding. One of my favorite education papers is “Cognitive Apprenticeship” which explicitly talks about how an effective teacher “models/shows” a skill, and “develops” and “coaches” students. The biggest distinction between a “boss/bully” teacher and a “leader” teacher is listening to students. A good teacher “asks” them for students’ goals and interpretations. How People Learn emphasizes that we have to engage students’ prior understanding for effective learning. A good teacher sympathizes with the students’ perspectives, then responds not with a canned speech, but with a thoughtful response (perhaps in the form of an activity, not just a lecture) that develops student understanding.
I saw Eric Roberts receive the IEEE Computer Society Taylor L. Booth Education Award last week. I told him that I was eager to try a teleprompter for the first time. Eric said that he wouldn’t. He said that he would respond to the moment, the audience, and the speeches of the previous recipients. He would use the adrenalin of the moment to compose his talk on the fly. (Eric’s a terrific speaker, so he can pull that off better than me.) He told me that it was the same as in class — he listens and responds to the students.
At the end of this week, I’m heading off to Oxford where I’ll teach in our study abroad program there. It will be Georgia Tech students and Georgia Tech faculty, but physically, in Oxford. I’ll be teaching two classes: Introduction to Media Computation in Python (for my first time in seven years!) and Computational Freakonomics. I’ve taught at Oxford Study Abroad twice before, and loved it. Sure, Oxford is fabulous, but what I most enjoyed my past times (and what I most look forward to this time) is the teaching experience. I have 22 students registered in MediaComp (typically 150-300/semester at Georgia Tech, depending on the size of the lecture halls available), and 10 students in CompFreak. We will meet for 90 minutes a day (each class, so 3 hours a day for me), four days a week. It’s an immersive experience. We will have meals together. Last times, I had “office hours” at my kitchen table, and in impromptu meetings at a lab after dinner.
In enormous lecture halls with literally hundreds of students, it’s not always easy to be a “leader.” It’s easier in those settings to be the “boss” (even the “bully”), professing what’s right and ordering students to do their work. In a setting like Oxford with smaller classes and more contact, I will have more opportunity to listen to my students, and the opportunity to develop my skills as a leader/teacher.
“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.
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?
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.
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.
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.”
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.)
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.
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.