Nothing earth-shattering here. I just wanted to share the activity we worked on today, which was an introduction to quantitative energy conservation by doing a video analysis of a bouncing ball. (Up until now, we were only doing qualitative energy pie charts.) Here are the handouts and the video:
Feel free to edit and reuse the handouts as you see fit. They’re not perfect, but I figure it’s better to share them than having them collect dust on my flash drive.
PS: I’ll sheepishly admit that I don’t do the whole suite of paradigm labs in the Modeling unit to mathematically derive the energy equations from experiments. But we do some simple qualitative demos/experiments to discover what variables would be in those energy equations. We start by talking about how the further a rubber band is stretched, the more energy it stores. Then we launch carts into a rubber band “bumper” (i.e., big rubber bands from Staples and two C-clamps) to qualitatively see the energy stored.
In doing so, we see that the cart’s kinetic energy depends on its speed and its mass. (Or is it weight? What would happen if we repeated the experiment on the moon?)
For gravitational energy, we can repeat the experiment, but have carts rolling down an incline. Or use the rubber band to launch the cart up the incline. I’ve also dropped balls into sand and looked at the depth to which they get buried. Either way, we see that gravitational energy depends on height and weight. (Or is it simply mass? What would happen on the moon?)
For elastic energy, we already know it depends on the distance the rubber band is stretched. Then, we can swap out the rubber band in the bumper with a stiffer/looser one to see the effects of the spring constant on energy stored.
Then, after we predict what the energy equations might look like, I just give them the actual energy equations, or have them look them up. (Gasp! See Schwartz’s A Time for Telling, aka Preparation for Future Learning.)
So, modelers, what am I missing by not doing the full-blown energy paradigm labs? How do you introduce the quantitative energy equations?
I have the honor of being invited by Discovery Education to attend their second “Beyond the Textbook” forum to be held this Wednesday and Thursday at their headquarters in Silver Spring, Maryland. The event is spearheaded by Steve Dembo and, in exchange for travel expenses, he gets to pick my brain about digital textbooks, resources, and curriculum. There will be 18 other outstanding educators as well, including my edu-heroes Christopher Danielson, Michael Doyle, Karl Fisch, and Tom Woodward.
I keep thinking about what a physics iBook would look like. Not a book for consumption, as with a traditional text, but rather a book to enable exploration. So what would a student see when they first opened such a book?
Students should be learning to doscience, not simply learning aboutscience. They should be making observations, posing questions, conducting experiments, finding patterns, analyzing data, and sharing their conclusions.
In this sense, the iBook would function more like an electronic lab notebook. As with curricula like Modeling Instruction and ISLE, students would create the physics content from their own investigations and evidence, rather than deferring to authority.
Actually, the iBook wouldn’t be completely blank. While it would initially be empty of content, it would be chock-full of toolsto help students collect and analyze experimental data. Software like Tracker for video analysis, VPython and GlowScript for computation and visualization, LoggerPro for graphing and electronic data collection, along with PhET simulations and Direct Measurement Physics Videos for conducting virtual experiments.
In the realm of traditional physics textbooks, only a few make it a priority to incorporate experiments into their storylines. Three that come to mind are:
FIGURE P-2 Electronic temperature sensors reveal that if equal amounts of hot and cold water mix the final temperature is the average of the initial temperatures.
For example, here’s a video of a momentum experiment, followed by the corresponding section of the text.
But, as you can see, the text does the analysis for the student. In my opinion, this would make a good reference only after the student has completed a similar activity on their own. Fortunately, her text also comes with a workbook that asks students to do this sort of scientific reasoning on their own:
Also taking the “experiments first” approach is Live Photo Physics Interactive Video Vignettes, a collaborative project by well-known physics education researchers Robert Teese, Priscilla Laws, and David Jackson. During a vignette, students are asked to make predictions and do video analysis on-the-fly. Here’s a preview:
Science is never done in isolation, however, so the iBook would come equipped with tools for sharing data, content, photos, videos, and resources among students and between teacher-student.
For me, going beyond the textbook means giving students a toolbox rather than an instruction manual.
What’s your vision for the future of textbooks?
You can follow along with us at the Beyond the Textbook forum this week by searching for the Twitter hashtag #BeyondTextbooks.
Recently, Michael Pershan (@mpershan) and I had a great conversation on Twitter about lessons and planning. I’ve copied it below. And if you aren’t already following Michael or reading his blog, you’re missing out.
FN: In the beginning, my planning took a content focus — WHAT do I want students to know. Now my planning is task focused — the HOW.
MP: Interesting. Do you rewrite everything each year? What’s your prep like?
FN: While lessons are similar each year, I don’t think I’ve done the exact same lesson twice. Probably not good for my sanity.
MP: But what keeps you from reusing old tasks? I mean, you do, so what’s the new planning? Selecting from set of tasks for kids?
FN: For example, Hooke’s Law task. Do we: uses scales or probes or hanging weights? Do we use 1, 2, or 3 springs? Do we do multiple measurements per trial? Do I force kids to make stretch the independent variable, or do they choose? Do we graph by hand or on the computer? Do we use LoggerPro or Excel? Do we use ideal springs or ones that have a preload? Does each group use identical springs or does each group get different ones? Students in groups of 2, 3, or 4? Do I give them a worksheet or does it go in their lab notebooks? So many little decisions and permutations. All are important decisions that non-teachers don’t even realize we make.
MP: Are these decisions that, you feel, there’s an optimum solution to, or is it different with each batch of kids?
FN: Kids, time, what I want to emphasize, equipment … Lots of factors.
MP: I really appreciate everything you just tweeted. Thank you.
FN: You’re welcome. Not sure that was much help.
MP: Sorry to pry, just trying to get a look at what experienced teaching looks like.
FN: I’d say experienced teaching looks a lot like jazz.
Over the past few months, Audrey Watters, Dan Meyer, and Keith Devlin have been critical of Silicon Valley, edtech startups, and iPadtextbooks which hope to “disrupt” education. In my opinion, the real stumbling block to meaningful change is students’ formal reasoning skills — analytical thinking that cannot be cultivated by pausing and rewinding video or playing Math Blasters.
Here are my 5 points:
Many of our students are transitioning from concrete to formal reasoning.
A significant barrier to learning for understanding is students’ own formal reasoning skills.
Formal reasoning skills (and thus learning for understanding) can be developing when instruction is structured around the Learning Cycle.
Silicon Valley and edtech startups have been focusing on (often inappropriately) just a small fraction of the learning cycle.
My Challenge to Silicon Valley: Help students learn for understanding by innovating around the rest of the learning cycle.
1. Many of our students are transitioning from concrete to formal reasoning.
Below are 3 reasoning puzzles, each followed by a video of college students attempting to solve the puzzle while explaining and discussing their logic. It’s a highly illuminating look at students’ reasoning processes.
I. The Algae Puzzle (Combinatorial Reasoning)
II. The Frog Puzzle (Proportional Reasoning)
III. The Mealworm Puzzle (Scientific Reasoning)
2. A significant barrier to learning for understanding is students’ own formal reasoning skills.
You’re probably thinking, “So, what? Just because Johnny can’t figure out all the possible combinations of algae doesn’t mean he can’t learn physics.” But the research strongly suggests that it does, even in interactive engagement classes.
As you can see, interactive engagement course outperformed traditional courses in learning gains as measured by the Force Concept Inventory (FCI). The FCI is the most widely used test of physics understanding. But why is there such a wide range of FCI gains among the IE courses and (not shown) among the individual students within a particular course? A study entitled “Why You Should Measure Your Students’ Reasoning Ability” (Coletta, Phillips, and Steiner) suggests reasoning ability is strongly correlated with physics success.
In the study, several different physics courses administered both the FCI (to measure physics gains) and the Lawson Test of Classroom Reasoning Skills (to measure formal reasoning ability). The Lawson test contains several items very similar the three puzzles above. Here’s what they found:
The data were split into quartiles based on the Lawson scores. The light green bars represent the average Lawson test score for each quartile and the dark green bars represent the average FCI gain for each quartile. There is clear correlation between reasoning ability and learning gains in physics. I’d wager this correlation extends to other subjects as well.
3. Formal reasoning skills (and thus learning for understanding) can be developed when instruction is structured around the Learning Cycle.
According to Piaget, intellectual growth happens through self-regulation — a process in which a person actively searches for relationships and patterns to resolve contradictions and to bring coherence to a new set of experiences.
In order to get students to experience self-regulation and further develop their reasoning skills, classroom experiences should be constructed around the Karplus learning cycle, which contains the the stages of EXPLORATION, INVENTION, and APPLICIATION. From Karplus’s workshop materials on the learning cycle:
EXPLORATION: The students learn through their own actions and reactions in a new situation. In this phase they explore new materials and new ideas with minimal guidance or expectation of specific accomplishments. The new experience should raise questions that they cannot answer with their accustomed patterns of reasoning. Having made an effort that was not completely successful, the students will be ready for self-regulation.
INVENTION: Starts with the invention of a new concept or principle that leads the students to apply new patterns of reasoning to their experiences. The concept can be invented in class discussion, based on the exploration activity and later re-emphasized by the teacher, the textbook, a film, or another medium. This step, which aids in self-regulation, should always follow EXPLORATION and relate to the EXPLORATION activities. Students should be encouraged to develop as much of a new reasoning pattern as possible before it is explained to the class.
APPLICATION: The students apply the new concept and/or reasoning pattern to additional examples. The APPLICATION phase is necessary to extend the range of applicability of the new concept. APPLICATION provides additional time and experiences for self-regulation and stabilizing the new reasoning patterns. Without a number and variety of APPLICATIONs, the concept’s meaning will remain restricted to the examples used during its definition. Many students may fail to abstract it from its concrete examples or generalize it to other situations. In addition, APPLICATION activities aid students whose conceptual reorganization takes place more slowly than average, or who did not adequately relate the teacher’s original explanation to their experiences. Individual conferences with these students to help identify and resolve their difficulties are especially helpful.
4. Silicon Valley and edtech startups have been focusing on (often inappropriately) just a small fraction of the learning cycle.
Unfortunately, Silicon Valley has been dumping its disruptive dollars almost solely into the INVENTION phase and on the tail-end of the phase at that. It views education purely as a content consumption process and ignores the development of formal thinking and reasoning.
Remember, in the invention phase, “The concept can be invented in class discussion, based on the exploration activity and later re-emphasized by the teacher, the textbook, film, or another medium.” That’s Khan Academy videos, flipclass videos, iBooks, an similar technologies designed to present content via direct instruction. However, “Students should be encouraged to develop as much of a new reasoning pattern as possible before it is explained to the class.” Which means that this type of direct instruction should be as minimal as possible, because it robs kids from reasoning and making meaning. In other words, Silicon Valley is putting its energy into the portion of the invention phase that should be as small as possible!
Now let’s look at the application phase. There has been some development here as well, most notably in apps and exercise software which seek to gamify the classroom. But the application phase isn’t about getting 10 right answers in a row or solving problems to shoot aliens. Remember, “Without a number and variety of APPLICATIONs, the concept’s meaning will remain restricted to the examples used during its definition.“ Real learning with understanding means students can reason about the concepts well enough to use them in new and unique concepts (aka transfer). Applications should require students to examine their own thinking, make comparisons, and raise questions. Great applications examples are open-ended problems, problems which present a paradox, and student reflection on both successful and unsuccessful problem-solving methods. Deep learning does not end when the Application phase begins.
5. My Challenge to Silicon Valley: Help students learn for understanding by innovating around the rest of the learning cycle.
Real disruption isn’t going to come from skill and drill apps, self-paced learning, badges, YouTube videos, socially-infused learning management systems, or electronic textbooks. Students must be continuously engaged in the learning cycle. We need to equip our students with the reasoning skills to learn how to learn anything. Focus on experiences in the exploration phase, meaningful sense making in the invention phase, and worthy problems in the application phase.
But, in reality, we only have ourselves to blame. It shouldn’t come as a surprise to us when students can’t think — the status-quo in education has been to spend most of our time on content delivery while robbing students of exploring and reasoning opportunities. And current edtech trends aren’t fixing this problem; rather, they are making it easier to make the problem worse.
To be fair, a few “good disrutptions” have occurred in the other phases of the learning cycle. Motion detectors allow students to “walk a graph” so they can easily explore position-time and velocity-time graphs. GeoGebra allows students to explore and play with geometry and functions quickly and easily. PhET simulations allows students to conduct open-ended planetary orbit experiments that would be impossible in real life. And VPython programming gets students to apply what they learned to write their own simulations and visualizations.
So when presented with the next great edtech “disruption,” ask yourself: has this innovation actually changed how student think about math and science concepts? Or has it just allowed students to get a few more questions correct on the state exam?
The chemistry room I'll be sharing with 4(!) other teachers.
A quick update: Starting tomorrow, I’ll be picking up a section of Chemistry 2 (second semester conceptual chemistry). Our school’s conceptual science courses are split into semesters to make student and teacher scheduling easier. I usually have a section of conceptual physics or astronomy, but this year it’s chemistry.
There’s also no mandatory curriculum, so I am free to experiment. My plan is to implement the 3 modules about matter from the Operation Primary Physical Science (OPPS) curriculum. I’m really excited about it, especially since making my shopping list for the first module:
Hopefully no one will think I'm a terrorist.
Other things I like about the OPPS curriculum:
Inquiry-based
Structured around the learning cycle
Emphasis on student-created models and evidence-based reasoning
A detailed teacher guide and student workbook. (A must for a time-pressed teacher like me. I can tweak it next year if needed.)
I also plan on using the Thinking Science materials from Shayer and Adey (thanks to John Clement on the PhysLrnr list who is always talking about them). I’m going to do 2 pre/post tests: the Lawson Test of Classroom Reasoning Skills and an attitudinal survey (likely the CLASS, since that is what Carl Wieman has been using). I’m hoping to see some individual growth in these areas.
My chemistry class is also small — just 11 students. I’m aiming to get some real dialogue going in class and to leave detailed feedback in their journals.
The 3 OPPS modules (Nature of Matter, Mixing Matter, and Heating Matter) should keep us busy for most of the 3rd quarter. Not sure yet what we’ll be doing for 4th quarter.
Anyway, wish me luck! I’ll keep you all updated throughout the semester!
UPDATE 1/22/2012: Now with links and Apple’s iBook video!
Warning: This post is a brain dump of all thoughts and conversations I’ve been having about next generation textbooks since Apple’s iBook textbook announcement. Sorry this isn’t polished.
I keep thinking about what a physics iBook would look like. Not a book for consumption (like a traditional text) but rather a book to enable exploration. More like a text-journal-workbook-lab notebook combo, where students would create content from investigations (also pooling created content/data from classmates, etc) and also have reference text for afterwards in the same vein as the Minds-On-Physics text, the first edition of M&I, and the Physics by Inquiry texts.
Stuck on a problem? An intelligent tutor would be able to re-direct you back to a video or animation or even your own data from an exploration where you initially encountered the concept.
It’d be like an electronic version of the PSSC/Modeling/ISLE /PUM curricula on steroids. And I see this more as the teacher having these tools to deploy to the students, rather than the students following a linear path through text and activities. The class actually builds the text together, and each year the text is different.
The capabilities and content for this iBook already exist. No one has put them together in one package yet. I think it could even be web/cloud-based and platform independent if done with the proper tools.
Today’s guest post is from Colleen Megowan-Romanowicz, the Executive Officer of the American Modeling Teachers’ Association. It is the fifth post in a series which shares the stories of teachers using Modeling Instruction.
Colleen writes:
I am a physics teacher. I have been teaching for 25 years, and I have taught many other subjects, but my identity as a physics teacher is as firmly grounded in the texture of my being as my identity as mother, “leftie”, and redhead.
I entered teaching through “the back door”, when my first choice career, medicine, was no longer an option. In elementary school, I wanted to be president of the United States, in high school I was hooked on marine biology, but when I entered college in 1969, I was committed to pre-medicine. Four years later, in classic overachiever fashion, I not only had a bachelor’s degree, but a husband and two children as well. By age 23, I had given birth to my third child and come to the realization that medical school was out of the question. I considered nursing, but thought it likely that I would harbor secret resentment toward the doctors with whom I worked. Teaching seemed the only other practical alternative for someone with a biology major and chemistry minor, so back to school I went. A year later, when I completed student teaching I knew I had, quite by accident, found my calling.
Twenty two years ago I began teaching physics—not a trivial task for someone who had completed college physics 18 years earlier. But how hard could it be, to stay ahead of 12 seventeen year old girls in one section of high school physics? (I taught at a girls’ Catholic high school in Sacramento) I unearthed my old physics books, bought some new ones, and discovered what I had missed completely the first time around. Physics is the foundation. It is why chemistry and biology exist. It is both a context and a rationale for mathematics.
It was a life changing realization—my kids joked that it was like God’s voice from the burning bush. From then on, I wanted to become the best physics teacher I could be. I took classes and workshops. I gave classes and workshops. I discovered that to be a good physics teacher I needed to be a good mathematics teacher, a good cognitive scientist, a good linguist and discourse analyst, even a good philosopher. And by all accounts I was good. I had plaques and certificates to prove it. I grew the physics program at my high school and converted it to physics-first. We went from 12 students to over 170 (in a school with just under 500 students—all girls). But I knew deep down I wasn’t really that good. My students learned to solve tricky physics problems and they could get into good colleges, but they never did that well on the FCI.
In 1998 I discovered Modeling Instruction…another life changing experience. After my first Modeling Workshop at UC Davis (led by Don Yost and Wayne Finkbeiner…Mark Schober, our current AMTA president, and I were classmates in that workshop) I went back into my classroom thinking I finally had the key to really helping my students learn physics. Unfortunately things didn’t unfold quite as I had imagined. I was not brilliant. I struggled and so did my students, but even inexpertly implemented, I could see how much better modeling was at revealing what my students were thinking. The following summer I went back to Davis for my second Modeling Workshop and the next school year I did better (and so did my students). By year 3, I finally felt like I knew what I was doing. I became intensely curious about how and why modeling worked for my students. I read whatever I could get my hands on, but finally decided that if I was going to figure modeling out, I’d have to be systematic about studying it. I needed someone to guide my studies, and since I had met David Hestenes while I was at UC Davis and he encouraged me to look into a program in physics education research, I contacted him and asked if I could be his graduate student. He agreed.
Although I loved teaching at Loretto High School for Girls in Sacramento, ten years ago I moved to Phoenix, took the job of designing the mathematics and science program for the new Jewish high school (a physics first integrated science and mathematics curriculum), and began my graduate studies at ASU. My research interest was in the integration of physics and mathematics, the physics first sequence of instruction, and the ways in which student discourse shapes thinking and reasoning in physics. I completed the Physics Department’s Master of Natural Science (MNS) degree program in 2004, along the way engaging in the first of many classroom research projects in collaboration with three other teachers. We designed and tested a modeling instruction unit in special relativity. During this period I also began teaching the Leadership Workshop course and coordinating the action research component of the MNS program. Over the years I have mentored over 40 teacher action researchers through their required MNS research experience. In fact it was during a Leadership Workshop meeting one day I heard that a handful of teachers in the Advanced Modeling course who were concerned about the future of modeling instruction, had invented AMTA the night before over a pitcher of beer (or 2). I immediately took out my checkbook and wrote Patrick Daisley (another UC Davis modeling classmate, who still serves AMTA as treasurer) a check for $25 to become one of the charter members of the organization.
In 2007, under the guidance of David Hestenes, I earned my PhD in Physics Education Research from ASU. My research was a study of whiteboard mediated cognition in four different modeling classrooms. After doing a year of postdoctoral research on embodied cognition in science education for ASU’s Arts, Media and Engineering program I took a faculty position in one of ASU’s colleges of education (we had 3 of them at the time) teaching elementary science methods. I secured funding for the Modeling Institute—a middle school STEM Modeling MNS degree program. Last summer I gave an invited talk and a demonstration of modeling instruction in Beijing. (They loved it. Chinese teachers want to learn modeling instruction.) In the fall I started writing grants in earnest to obtain funds to help scale AMTA up. To date I have written four grants. None have been awarded yet—I think perhaps the NSF reviewers are having a hard time wrapping their brains around a grassroots organization of this type. This spring I offered my services to the AMTA executive board as executive officer. When they took me up on it, I resigned my faculty position at ASU and accepted a part-time research position so that I could devote as much time as possible to helping AMTA “go big”. (I am fortunate to have the support of a loving husband who tells me I should do what makes me happy.) My AMTA position will not be salaried until I can land us some external funding.
Pedagogically, I approach teaching via modeling theory, and cognitively I am particularly interested in the phenomenon of distributed cognition and how a situated group learning experience ultimately distills into individual student understanding. I am also convinced that mathematics and science instruction can and should be integrated. I undertook this with good results for three years at the Jewish high school, and I built this curriculum design into the NSF-funded master’s degree program for middle school teachers. I hope that my work will enable modeling instruction to become self-sustaining and I would like contribute to large-scale curriculum integration in mathematics and science. At the very least, I hope that by having a foot in both the mathematics education and physics education camps, I can foster a dialogue and an ongoing relationship between the two communities that ultimately enriches both.
From Harvard EdCast’s “The Celebrity Math Tutor” (transcript below)
Buffy Cushman-Patz: What efforts do you take to ensure that your pedagogy is consistent with what education research shows about how people learn, especially how people learn math and science?
Sal Khan: The reality is…when we’re going through the first pass of the videos there was very little effort; it really was just me doing my best shot and seeing what I would have liked to have and that my cousins and other people on YouTube seem to be benefiting from. Now we are getting pretty deep on our own analytics on our website. In terms of the broader research, I think there are people who come up with rules of thumb based on some study or another, and I’m not saying the study’s not valid, but I’m saying sometimes it’s not necessarily…you can’t come up with these rules the way all teaching has to be done like this. I think, for example, those research – you know there’s this one research study that’s been going around, kind of saying that… it first kind of hints at videos – maybe people can’t learn from videos and that if you do make a video you always have to address the misconceptions first and if you don’t address the misconceptions first, people are always going to conform whatever you say into their preexisting misconceptions. I don’t think that research is wrong; I think that is often the case. I don’t think it has to be religiously applied – that you have to, because in some areas people might not have even thought about something, they might not have misconceptions or maybe you explain once and you reemphasize that this goes against misconception A, B, C, or D. So I don’t think there’s one formula there. And I think frankly, the best way to do it is you put stuff out there and you see how people react to it; and we have exercises on our site too, so we see whether they’re able to see how they react to it anecdotally. You see, the comments they put, they’ll ask questions based on… Every time I put a YouTube video up, I look at the comments — at least the first 20, 30, 40 comments that go up — and I can normally see a theme: that look, a lot of people kind of got the wrong idea here. Or maybe some people did, and then I’ll usually make another video saying “Hey, look after the last video, I read some the comments and a lot of y’all are saying this is not what we’re talking about it’s completely different.” So that means I am attacking the misconceptions. But I think if you had a formula in place, and you do that every time, I think once again the learner will say, “This guy’s not thinking through it and he’s not teaching us his sensibilities, his thought processes. He’s just trying to meet some formula on what apparently is good video practice. “And I’ll go the other way: you can dot all the “i”s and cross all the “t”s on some research-based idea about how a video should be made, but if your voice is condescending, if you’re not thinking things through, if it’s a scripted lecture, I can guarantee you it’s not going to appeal with students. And I think the other mistake people… I’d like some research to be done with this, and it really goes against the grain against what most people assume is what even video is about is, that all the feedback that we’ve gotten is not seeing the face is, maybe, one of the most compelling things about it is hearing the voice, because the face is hugely distracting. And so long answer to a short question. I think it’s nice to look at some of the research, but I don’t think we would… and I think in general, people would be doing a disservice if they trump what one research study does and there’s a million variables there: who was the instructor, what were they teaching, what was the form factor, how did they use to produce it? You’d be doing yourself a disservice if you just take the apparent conclusions from a research study and try to blanket them onto what is really more of an art. It’s like saying that there’s a research study on what makes a nice painting and always making your painting according to that research study that would obviously be a mistake.
It’s unfortunate that “The Teacher to the World” was only able to mention one study about how students learn. A study which he then dismisses. And since he doesn’t describe any other efforts to be consistent with pedagogy, his real answer to Buffy’s question is: “I don’t.”
Let’s look at Khan’s response in more detail:
“Now we are getting pretty deep on our own analytics on our website.”
I don’t see how statistics about how many times students have watched/rewound each video or how many times students miss a question in the exercises tells us anything about how effective his videos are. I don’t see how he could use that data to refine his future videos in the same way a teacher would reflect and refine lessons from year-to-year.
“…you can’t come up with these rules the way, all teaching has to be done like this.”
He’s right. There is no one rule, no one formula, for teaching. The Physics Education Research User Guide website contains 51 different research-based teaching methods. The website can filter these methods by type, instructional setting, course level, coverage, topic, instructor effort, etc. And while 51 different methods may seem overwhelming, they all have one important characteristic in common: interactive engagement (IE).
So what is interactive engagement? Hake defines IE as methods “designed at least in part to promote conceptual understanding through interactive engagement of students in heads-on (always) and hands-on (usually) activities which yield immediate feedback through discussion with peers and/or instructors.”
A video lecture is not interactive engagement.
“…maybe you explain once and you reemphasize that this goes against misconception A, B, C, or D.”
Khan (along with most of the general public, in my opinion) has this naive notion that teaching is really just explaining. And that the way to be a better teacher is to improve your explanations. Not so! Teaching is really about creating experiences that allow students to construct meaning.
“And I think frankly, the best way to do it is you put stuff out there and you see how people react to it…”
This is flawed. People’s reactions are not indicators of effectiveness. Pre/post testing is needed to indicate effectiveness. Ah, but perhaps there is a relationship between people’s reaction and effectiveness? The research indicates otherwise. In the very research study that Khan says is valid (and then dismisses), student actually did better after watching the videos they described as confusing, and made no gains after watching the videos they described as easy to understand. Additional research indicates that when an instructor switches over to IE methods, course evaluations from students tend to be more negative than the previous year, despite gains from students going up. (Don’t worry, a few years after the switch to IE, the evaluations go back to pre-IE levels.)
“You see, the comments they put, they’ll ask questions based on… Every time I put a YouTube video up, I look at the comments — at least the first 20, 30, 40 comments that go up — and I can normally see a theme: that look, a lot of people kind of got the wrong idea here. Or maybe some people did, and then I’ll usually make another video saying “Hey, look after the last video, I read some the comments and a lot of y’all are saying this is not what we’re talking about it’s completely different.” So that means I am attacking the misconceptions.”
Again, it’s not about crafting better explanations. It’s about helping students wrestle with their conceptions and guiding them.
“But I think if you had a formula in place, and you do that every time, I think once again the learner will say, “This guy’s not thinking through it and he’s not teaching us his sensibilities, his thought processes. He’s just trying to meet some formula on what apparently is good video practice.”
Another naive notion of teaching. The goal is not for the teacher to teach the students his sensibilities and thought processes. The goal is for the teacher to have the students use their sensibilities and thought processes to reason through the concepts. Empower the student to think for themselves, rather than consuming the teacher’s ideas.
“And I’ll go the other way: you can dot all the “i”s and cross all the “t”s on some research-based idea about how a video should be made, but if your voice is condescending, if you’re not thinking things through, if it’s a scripted lecture, I can guarantee you it’s not going to appeal with students.”
“…and I think in general, people would be doing a disservice if they trump what one research study does and there’s a million variables there: who was the instructor, what were they teaching, what was the form factor, how did they use to produce it? You’d be doing yourself a disservice if you just take the apparent conclusions from a research study and try to blanket them onto what is really more of an art. It’s like saying that there’s a research study on what makes a nice painting and always making your painting according to that research study that would obviously be a mistake.”
The six thousand students in Hake’s study were not in a single class. They were in 62 different courses, from high school to university, taught by a variety of instructors with different personalities and expertise. And yet ALL the IE courses made greater gains (the slope of the graph — between 0.34 and 0.69) than the traditionally taught courses (average 0.23). It should also be noted that the green IE courses above were NOT identical and did not follow some magic teaching formula. They only had to conform to the Hake’s broad definition of IE given above. So you see, those “million variables” that Khan mentions don’t matter. METHOD trumps all those other variables.
But surely teacher expertise matters, right?
Yes and no.
NO: As seen in Hake’s study above, when comparing IE teachers to traditional teachers, expertise doesn’t matter because IE always trumps traditional.
NO: Note the small spread of the red-colored traditional classes shown above, which hover around an average gain of 0.23. Traditional methods produce very similar results no matter the level of the course or instructor.
YES: When comparing IE teachers to other IE teachers, expertise does matter. IE gains ranged from 0.34 and 0.69. As instructors get more comfortable using IE methods, gain increases. See, for example, this graph about the effectiveness of modeling instruction:
Expert modelers had higher gains than novice modelers.
But surely there is a place for lectures, right?
Yes, BUT students must be “primed” for the lecture. According to the PER User’s Guide FAQ:
It is possible for students to learn from a lecture if they are prepared to engage with it. For example, Schwartz et al. found that if students work to solve a problem on their own before hearing a lecture with the correct explanation, they learn more from the lecture. (For a short summary of this article aimed at physics instructors, see these posts – part 1 and part 2 – on the sciencegeekgirl blog.) Schwartz and Bransford argue that lectures can be effective “when students enter a learning situation with a wealth of background knowledge and a clear sense of the problems for which they seek solutions.”
For more information about how people learn, I highly recommend two great FREE online books from the National Academies Press:
And just in case you think I’m an armchair critic with nothing to contribute, I want you to know I’ve opened up my classroom to the whole world on my Noschese 180 blog, where I’ve been sharing a picture and a reflection from each school day. It’s not quite the Noschese Academy, but I hope you find it worth reading and commenting, as we journey through teaching together.
Today’s guest post is from Fran Poodry, the president-elect of the American Modeling Teachers’ Association. Fran teaches high school physics in Pennsylvania. It is the fourth post in a series which shares the stories of teachers using Modeling Instruction. Fran writes:
I was a physics major in college and I knew all along that I wanted to become a teacher. I took all my undergraduate education courses at a small private liberal-arts college, where I learned many things that are now called “21st century education” which I find humorous. Since I planned to teach, a professor I knew (but not at my school) suggested I join the physics teaching mailing list, PHYS-L, and from there I learned about Physics Education Research. I also got to know (virtually) Joe Redish, Dewey Dykstra, Priscilla Laws, and others. I wound up working for Priscilla Laws for two summers, learning about Workshop Physics, Vernier probes and interfaces (remember the ULI?) and analyzing data from student surveys pre- and post-instruction.
I graduated with a BA in Physics and a Pennsylvania teaching certificate in 1992, and I have been teaching physics since January, 1993. I taught for five and a half years in Philadelphia public schools. Jane Jackson recruited me for a modeling workshop when I attended a summer AAPT meeting at University of Maryland (having known me from my online presence), and I took modeling workshops in 1997 and 1998. These workshops were at University of Wisconsin-River Falls and were led by Rex Rice and Dave Braunschweig. I still make Rex’s guacamole recipe—yum!
As with many, my life was changed by Modeling Instruction. I felt like I had discovered the way I wanted to teach, I just hadn’t figured it out before. Also, I was amazed by how much physics I learned at the workshops! Though I loved using Modeling Instruction, the situation in my school was taking its toll. The large class sizes, under-prepared students, tragic events, and the bars on the windows were all hard to deal with. I decided I had to leave Philadelphia or leave teaching. I left the School District of Philadelphia in 1998.
After leaving Philadelphia schools, I have been teaching in various suburban districts in New Jersey and Pennsylvania. I love my current school (where I am starting my 10th year), and I have great colleagues, but only one of my colleagues is also a Modeler (though we have four full-time physics teachers in my building). I have used Modeling Instruction with kids in conceptual classes, honors classes, and in-between, and from a variety of socio-economic levels. I have struggled to use Modeling with my AP students, since they have already (mostly) had a year of Modeling Instruction in their first-year physics class with my colleague. While I have enjoyed teaching mostly conceptual-level classes and AP classes for the past 8 years, I am looking forward to teaching honors-level and AP classes this school year, and trying out Standards-Based Grading.
I joined the AMTA board last year as Vice President, so am currently the President-Elect and I will be President next year. I feel very strongly that the work of AMTA is vital for keeping Modeling Instruction alive and growing and funded, unlike previous worthy programs that were not self-sustaining (IPS, PSSC, Project Physics, etc). One way that to help this happen is through greater publicity. Most science teachers in my district have no idea what Modeling is, and when offered a 2-hour introduction on an inservice day, only two teachers (out of over 40 high school science teachers) came to the session – the rest chose other sessions. Not only teachers need to know about Modeling Instruction, the word also needs to get out to the politicians, the parents, and the voting public.
Action-Reaction 