Tag Archives: learning

Speaking of the inverted classroom

On Wednesday, I gave a talk at Indiana University – Purdue Universty – Indianapolis (IUPUI, for short) to the teaching seminar for math graduate students on the inverted classroom. It was sort of a generalization of the talk I gave on the inverted linear algebra classroom back at the Joint Mathematics Meetings in January. Carl Cowen was in attendance at that talk and invited me to make the 20-minute drive from my house to IUPUI to do something like it, and I was happy to oblige.

Since putting the talk up on Slideshare yesterday morning, it’s gotten over 200 views, 2 favorites, a handful of retweets/Facebook likes, and is currently being highlighted on Slideshare’s Education page. So I thought I would share it here as well. Enjoy and ask questions!

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Filed under Calculus, Camtasia, Clickers, Education, Inverted classroom, Linear algebra, Math, Screencasts, Teaching

Technology making a distinction but not a difference?

This article is the second one that I’ve done for Education Debate at Online Schools. It first appeared there on Tuesday this week, and now that it’s fermented a little I’m crossposting it here.

The University of South Florida‘s mathematics department has begun a pilot project to redesign its lower-level mathematics courses, like College Algebra, around a large-scale infusion of technology. This “new way of teaching college math” (to use the article’s language) involves clickers, lecture capture, software-based practice tools, and online homework systems. It’s an ambitious attempt to “teach [students] how to teach themselves”, in the words of professor and project participant Fran Hopf.

It’s a pilot project, so it remains to be seen if this approach makes a difference in improving the pass rates for students in lower-level math courses like College Algebra, which have been at around 60 percent. It’s a good idea. But there’s something unsettling about the description of the algebra class from the article:

Hopf stands in front of an auditorium full of students. Several straggle in 10 to 15 minutes late.

She asks a question involving an equation with x’s, h’s and k’s.

Silence. A few murmurs. After a while, a small voice answers from the back.

“What was that?” Hopf asks. “I think I heard the answer.”

Every now and then, Hopf asks the students to answer with their “clickers,” devices they can use to log responses to multiple-choice questions. A bar graph projected onto a screen at the front of the room shows most students are keeping up, though not all.

[…]

As Hopf walks up and down the aisles, she jots equations on a hand-held digital pad that projects whatever she writes on the screen. It allows her to keep an eye on students and talk to them face-to-face throughout the lesson.

Students start drifting out of the 75-minute class about 15 minutes before it ends. But afterward, Hopf is exuberant that a few students were bold enough to raise their hands and call out answers.

To be fair: This is a very tough audience, and the profs involved have their work cut out for them. The USF faculty are trying with the best of intentions to teach students something that almost assuredly none of them really want to learn, and this is exceedingly hard and often unrewarding work. I used to teach remedial algebra (well short of “college algebra”) at a two-year institution, and I know what this is like. I also know that the technology being employed here can, if used properly, make a real difference.

But if there’s one main criticism to make here, it’s that underneath the technology, what I’m seeing — at least in the snapshot in the article — is a class that is really not that different than that of ten or twenty years ago. Sure, there’s technology present, but all it seems to be doing is supporting the kinds of pedagogy that were already being employed before the technology, and yielded 60% pass rates. The professor is using handheld sketching devices — to write on the board, in a 250-student, 75-minute long lecture. The professor is using clickers to get student responses — but also still casting questions out to the crowd and receiving the de rigeur painful silence following the questions, and the clickers are not being used in support of learner-centered pedagogies like peer instruction. The students have the lectures on video — but they also still have to attend the lectures, and class time is still significantly instructor-centered. (Although apparently there’s no penalty for arriving 15 minutes late and leaving 15 minutes early. That behavior in particular should tell USF something about what really needs to change here.)

What USF seems not to have fully apprehended is that something about their remedial math system is fundamentally broken, and technology is neither the culprit nor the panacea. Moving from an instructor-centered model of learning without technology to an instructor-centered model of learning with technology is not going to solve this problem. USF should instead be using this technology to create disruptive change in how it delivers these courses by refocusing to a student-centered model of learning. There are baby steps here — the inclusion of self-paced lab activities is promising — but having 75-minute lectures (on college algebra, no less) with 225 students signals a reluctance to change that USF’s students cannot afford to keep.

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Filed under Clickers, Education, Educational technology, Higher ed, Inverted classroom, Math, Peer instruction, Student culture, Teaching, Technology

The inverted classroom and student self-image

picture of an e-learning classroom

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This week I’ve been immersed in the inverted classroom idea. First, I gave this talk about an inverted linear algebra classroom at the Joint Meetings in New Orleans and had a number of really good conversations afterwards about it. Then, this really nice writeup of an interview I gave for MIT News came out, highlighting the relationship between my MATLAB course and the MIT OpenCourseware Project. And this week, I’ve been planning out the second iteration of that MATLAB course that’s starting in a few weeks, hopefully with the benefit of a year’s worth of experience and reflection on using the inverted classroom to teach technical computing to novices.

One thing that I didn’t talk much about at the Joint Meetings or in the MIT interview was perhaps the most prominent thing about using the inverted classroom model on a day-to-day basis: how students react to it and change as a result of it. I was actually quite surprised that nobody at my Joint Meetings talk asked me a question about this, because honestly, the inverted classroom sounds great on paper, but when you start to imagine the average college student walking in on the first day of class and having this method of instruction described to him, it becomes clear that a significant amount of work is going to have to be done in order to get students — who are already resistant to any change from their accustomed modes of instruction — on board with the plan.

Students do tend to resist the inverted classroom at first. Some forms of resistance are more benign than others. On the benign end of the spectrum there are students with little experience with the course material or its prerequisites who get bogged down on the basic podcast viewing (which takes the place of in-class lectures in this model) or the accompanying guided practice, and instead of actively seeking a resolution to their question will wait for the instructor to clear it up — in class. On the other end is the student who simply doesn’t believe I’m serious when I say there won’t be any lecturing, who then doesn’t do the work, assuming I’ll bail him out somehow — in class. But in the inverted model, students are held responsible for acquiring basic competencies before class so that the hard stuff — what we refer to as assimilation — is the primary focus of the class time.

I break this distinction down for students, but not everybody buys into it. Those who don’t will have to undergo a learning process that usually looks like shock — shock that I won’t reteach them the material they were supposed to have viewed and worked on, while the lab assignment based on that material is going on. This can get very ugly in ways I probably don’t need to describe. Let’s just say that you had better not use the inverted classroom model if you aren’t prepared to put out a constant P.R. effort to convince students of the positive benefits of the model and constantly to assuage student concerns.

I’ve often wondered why students sometimes react so negatively to the inverted classroom model. I’ve come to believe it’s the result of a invasive, false belief that can arise in students about their ability to learn things independently of others — namely, that they simply cannot do so. I have had students tell me this to my face — “I can’t learn [insert topic] unless you lecture to me about it in class first.” Clearly this is not true. Toddlers learn their native language without formal instruction, just by assimilating (there’s that word again) the language going on naturally in their background. We all learn things every day without sitting in a classroom; we may seek out training data first through printed instructions, worked-out examples, YouTube videos, etc., but it’s almost never in a classroom setting. Learning new things on our own initiative and without formal instruction in a classroom setting is as natural to humans as breathing. Indeed you could say that it’s the capacity to learn in this way that makes us human. But somehow many students think otherwise.

Where does this belief come from? I think that it comes from its own instance of assimilation, namely the assimilation of a culture of programmed classroom instruction that takes place from roughly the first grade through the twelfth grade in this country. Students have so few experiences where they pursue and construct their own knowledge that they simply come to believe that they are incapable of doing so. And this belief is propagated most rapidly in mathematics. I’ve been reading in Seymour Papert‘s book Mindstorms: Children, Computers, and Powerful Ideas, and this quote hits this issue right on the head:

Difficulty with school math is often the first step of an invasive intellectual process that leads us all to define ourselves as bundles of aptitudes and ineptitudes, as being “mathematical” or “not mathematical”, “artistic” or “not artistic”, “musical” or “not musical”, “profound” or “superficial”, “intelligent” or “dumb”. Thus deficiency becomes identity and learning is transformed from the early child’s free exploration of the world to a chore beset by insecurities and self-imposed restrictions.

That last sentence (emphasis added) sums it up, doesn’t it? Deficiency becomes identity. Eventually, if a student is robbed of experiences of self-motivated learning, the student eventually adopts a self-image in which she is incapable of self-motivated learning. It is a false self-image that is ultimately dehumanizing.

Which is why I put such stock in the inverted classroom model. I think this method of teaching, along with other learner-centered modes of instruction like problem-based learning, is on the front lines in reversing students’ negative ways of thinking about how they learn. Students may (will?) chafe at the inversion at first. But in the MATLAB course at least, something really cool happened at the end of the semester. I made up a slideshow for students called “Five myths about how you think you learn that CMP 150 has busted”. Among the myths were “I can’t learn unless a professor lectures to me” and “I can’t learn on my own initiative”, and I gave concrete examples of work that the students had done in the class that contradicted these messages. In the end I showed them that through this inverted classroom process they had taken majors strides toward being confident, independent, skill learners and problem-solvers rather than just people who can play the classroom game well. And even the most skeptical students were nodding in agreement. And I think that makes it all worthwhile for everyone.

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Filed under Critical thinking, Education, Inverted classroom, Liberal arts, Linear algebra, Math, MATLAB, Screencasts, Student culture, Teaching, Technology

Misunderstanding mathematics

Plots of quadratic equations with discriminant...

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Robert Lewis, a professor at Fordham University, has published this essay entitled “Mathematics: The Most Misunderstood Subject”. The source of the general public’s misunderstandings of math, he writes, is:

…the notion that mathematics is about formulas and cranking out computations. It is the unconsciously held delusion that mathematics is a set of rules and formulas that have been worked out by God knows who for God knows why, and the student’s duty is to memorize all this stuff. Such students seem to feel that sometime in the future their boss will walk into the office and demand “Quick, what’s the quadratic formula?” Or, “Hurry, I need to know the derivative of 3x^2 – 6x +1.” There are no such employers.

Prof. Lewis goes on to describe some ways in which this central misconception is worked out in our schools and in everyday thinking. The analogy between mathematics instruction and building construction, in which he compares current high school mathematics instruction to a building project where the scaffolding is constructed and then abandoned because we think the job is done, is pretty compelling. The whole essay is well worth reading.

I do think that it’s a bit too easy to lay the blame for the current state of mathematics instruction at the feet of American high schools, as Lewis does multiple times. Even if high schools do have flawed models of math instruction, certainly they are not alone in this. How many universities, even elite institutions like Fordham, have math classes or even entire curricula predicated on teaching math as rote mechanics? And what about the elementary math curricula? Pointing the finger at high schools is the natural thing to do for college professors, because we are getting students fresh from that venue and can see the flaws in their understanding, but let us not develop tunnel vision and think that fixing the high schools fixes everything. Laying blame on the right party is not what solves the problem.

Lewis brings up the point that we should be aiming for “genuine understanding of authentic mathematics” to students and not something superficial, and on that I think most people can agree. But what is this “authentic mathematics”, and how are we supposed to know if somebody “genuinely understands” it? What does it look like? Can it be systematized into a curriculum? Or does genuine understanding of mathematics — of anything — resist classification and institutionalization? Without a further discussion on the basic terms, I’m afraid arguments like Lewis’, no matter how important and well-constructed, are stuck in neutral.

Again coming back to higher education’s role in all this, we profs have work to do as well. If you asked most college professors questions like What is authentic mathematics?, the responses would probably come out as a laundry list of courses that students should pass. Authentic mathematics consists of three semesters of calculus, linear algebra, geometry, etc. And the proposed solution for getting students to genuinely understand mathematics would be to prescribe a series of courses to pass. There is a fundamentally mechanical way of conceiving of university-level mathematics education in which a lot of us in higher ed are stuck. Until we open ourselves up to serious thinking about how students learn (not just how we should teach) and ideas for creative change in curricula and instruction that conform to how students learn, the prospects for students don’t look much different than they looked 15 years ago.

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Filed under Education, High school, Higher ed, Liberal arts, Life in academia, Math, Teaching

Monday discussion thread: Business curricula

It’s been a packed last couple of weeks, leaving me picking up the pieces and trying to clear some of my grading backlog before the Thanksgiving break. Rather than leave the blog alone for another week, let’s try an open thread based around something that’s come to mind just now, namely: Business degrees and the pedagogy used in the curricula for those degrees.

The usual way business courses play out is the usual way any set of courses plays out: You have a sequence of classes on various topics, the early ones being mainly theoretical or overview courses, maybe not in the business department at all. (For example, all business majors at my school have to take Calculus, which is why I am thinking about this in the first place.) The classes get more specialized and, usually, harder as you climb the ladder. Eventually you get to the top of the degree program and have a “seminar” class that is project-based, usually involving case studies.

So, for your discussion, consider this idea: Business degrees should not be conducted in this way. Instead, EVERY course should be project-based, beginning with the first semester of the freshman year and continuing on. (For the sake of argument, restrict your attention just to courses in the business department, not outside classes like calculus.) You can have a syllabus of basic learning outcomes for business majors if you like, and maybe some way of assessing student acquisition of those outcomes prior to graduation, but EVERY business class should be predicated on project-based learning — and let students go learn the theory on their own, with professor guidance if necessary, if and only if that theory has something to say about the project they’re working on. Courses based on imparting “material” through lectures or lab assignments disconnected from the context of a specific problem would be eliminated.

I’m not saying I am in favor of this. It’s just a provocative alternative. Discuss.

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Calculus and conceptual frameworks

I was having a conversation recently with a colleague who might be teaching a section of our intro programming course this fall. In sharing my experiences about teaching programming from the MATLAB course, I mentioned that the thing that is really hard about teaching programming is that students often lack a conceptual framework for what they’re learning. That is, they lack a mental structure into which they can place the topics and concepts they’re learning and then see those ideas in their proper place and relationship to each other. Expert learners — like some students who are taking an intro programming course but have been coding since they were 6 years old — have this framework, and the course is a breeze. Others, possibly a large majority of students in a class, have never done any kind of programming, and they will be incapable of really learning programming until they build a conceptual framework to  handle it. And it’s the prof’s job to help them build it.

Afterwards, I thought, this is why teaching intro programming is harder than teaching calculus. Because students who make it all the way into a college calculus surely have a well-developed conceptual framework for mathematics and can understand where the topics and methods in calculus should fit. Right? Hello?

It then hit me just how wrong I was. Students coming into calculus, even if they’ve had the course before in high school, are not guaranteed to have anything like an appropriate conceptual framework for calculus. Some students may have no conceptual framework at all for calculus — they’ll be like intro programming students who have never coded — and so when they see calculus concepts, they’ll revert back to their conceptual frameworks built in prior math courses, which might be robust and might not be. But even then, students may have multiple, mutually contradictory frameworks for mathematics generally owing to different pedagogies, curricula, or experiences with math in the past.

Take, for example, the typical first contact that calculus students get with actual calculus in the Stewart textbook: The tangent problem. The very first example of section 2.1 is a prototype of this problem, and it reads: Find an equation of the tangent line to the parabola y = x^2 at the point P(1,1). What follows is the usual initial solution: (1) pick a point Q near (1,1), (2) calculate the slope of the secant line, (3) move Q closer to P and recalculate, and then (4) repeat until the differences between successive approximations dips below some tolerance level.

What is a student going to do with this example? The ideal case — what we think of as a proper conceptual handling of the ideas in the example — would be that the student focuses on the nature of the problem (I am trying to find the slope of a tangent line to a graph at a point), the data involved in the problem (I am given the formula for the function and the point where the tangent line goes), and most importantly the motivation for the problem and why we need something new (I’ve never had to calculate the slope of a line given only one point on it). As the student reads the problem, framed properly in this way, s/he learns: I can find the slope of a tangent line using successive approximations of secant lines, if the difference in approximations dips below a certain tolerance level. The student is then ready for example 2 of this section, which is an application to finding the rate at which a charge on a capacitor is discharged. Importantly, there is no formula for the function in example 2, just a graph.

But the problem is that most students adopt a conceptual framework that worked for them in their earlier courses, which can be summarized as: Math is about getting right answers to the odd-numbered exercises in the book. Students using this framework will approach the tangent problem by first homing in on the first available mathematical notation in the example to get cues for what equation to set up. That notation in this case is:

m_{PQ} = \frac{x^2 - 1}{x-1}

Then, in the line below, a specific value of x (1.5) is plugged in. Great! they might think, I’ve got a formula and I just plug a number into it, and I get the right answer: 2.5. But then, reading down a bit further, there are insinuations that the right answer is not 2.5. Stewart says, “…the closer x is to 1…it appears from the tables, the closer m_{PQ} is to 2. This suggests that the slope of the tangent line t should be m = 2.” The student with this framework must then be pretty dismayed. What’s this about “it appears” the answer is 2? Is it 2, or isn’t it? What happened to my 2.5? What’s going on? And then they get to example 2, which has no formula in it at all, and at that point any sane person with this framework would give up.

It’s also worth noting that the Stewart book — and many other standard calculus books — do not introduce this tangent line idea until after a lengthy precalculus review chapter, and that chapter typically looks just like what students saw in their Precalculus courses. These treatments do not attempt to be a ramp-up into calculus, and presages of the concepts of calculus are not present. If prior courses didn’t train students on good conceptual frameworks, then this review material actually makes matters worse when it comes time to really learn calculus. They will know how to plug numbers and expressions into a function, but when the disruptively different math of calculus appears, there’s nowhere to put it, except in the plug-and-chug bin that all prior math has gone into.

So it’s extremely important that students going into calculus get a proper conceptual framework for what to do with the material once they see it. Whose responsibility is that? Everybody’s, starting with…

  • the instructor. The instructor of a calculus class has to be very deliberate and forthright in bending all elements of the course towards the construction of a framework that will support the massive amount of material that will come in a calculus class. This includes telling students that they need a conceptual framework that works, and informing them that perhaps their previous frameworks were not designed to manage the load that’s coming. The instructor also must be relentless in helping students put new material in its proper place and relationship to prior material.
  • But here the textbooks can help, too, by suggesting the framework to be used; it’s certainly better than not specifying the framework at all but just serving up topic after topic as non sequiturs.
  • Finally, students have to work at constructing a framework as well; and they should be held accountable not only for their mastery of micro-level calculus topics like the Chain Rule but also their ability to put two or more concepts in relation to each other and to use prior knowledge on novel tasks.

What are your experiences with helping students (in calculus or otherwise) build useable conceptual frameworks for what they are learning? Any tools (like mindmapping software), assessment methods, or other teaching techniques you’d care to share?

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Filed under Calculus, Critical thinking, Education, Educational technology, Math, Problem Solving, Teaching, Technology, Textbooks

What I learned at the ICTCM, day 1

Created by me MysteriousMystery for use on Wik...

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Busy day here at the ICTCM. I need both an extended time for brain-dumping and a full night’s sleep, and I think the latter is going to win. So here’s a brief listing, in no particular order, of some of the standout items I’ve learned today.

  • I learned first thing this morning that rigorous, scientific scholarship of teaching and learning does actually exist, and it’s being done by Dave Pritchard of MIT. Prof. Pritchard was our keynote speaker this morning. In his words, he has basically forsaken a successful career in atomic physics (in which role he mentored or taught three Nobel laureates) to devote his energies to physics education. His keynote this morning gave me enough reading material for a semester and a whole new outlook on what educational research could look like.
  • I learned (through Pritchard’s keynote) that there is a school of thought that says partial credit in math and science courses should not be given, because — and I quote — “Partial credit rewards partial understanding”. More to think about here.
  • I learned that, thanks to the research of Pritchard and his cohorts, there is a growing field of educational data mining, or one might say educational informatics, out there, designed to take data from online assessment tools and making observations about student learning. There’s even a journal.
  • I learned that the difference between novice and expert behaviors in learning pretty much describes all the issues I’ve encountered with the MATLAB course and other courses I’ve taught.
  • I learned, through Scott Franklin’s prezi on this subject this morning, that online lectures can be done that aren’t just lectures.
  • I learned that Geogebra is pretty cool, and I’ll learn more tomorrow as I take a minicourse on that software.
  • I learned there’s a whole website out there — and probably more than this one — for project-based learning ideas.
  • I learned that MATLAB has an interactive GUI…. for creating interactive GUI’s. Definitely something to play with later.
  • I learned that Gino’s East Pizza is among the best stuff I’ve ever ate, and the copious amounts of it in my stomach right now are a strong argument for sleeping over brain-dumping.

Tomorrow will be a Geogebra minicourse, as I mentioned, and more sessions which I haven’t mapped out yet. We’re getting sporadic wireless access, so I’m able to tweet a lot. More to come!

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