The Concord Consortium

Just got back from the Biennial Conference on Chemical Education (BCCE 2012), where I participated in a symposium titled “Web-Based Resources for Chemical Education.” About 60 people attended to learn about Molecular Workbench and other online tools and resources. One of the audience questions was about future availability of Molecular Workbench on the iPad and other tablets. Our latest work on the HTML5/JavaScript next-generation MW project, generously funded by Google.org, will address exactly this. We’ll be bringing much of the Java-based Classic MW to the browser, so that any device running a modern Web browser will be able to run our newest interactives and activities.

I didn’t get to attend many of the other sessions at BCCE because much of my time was spent staffing Concord Consortium’s exhibit booth to disseminate our free software. Jeanne Hurtz and I spoke with hundreds of people who stopped by our booth to hear about the current MW capabilities and see a next-generation MW model running on a tablet. We gave away about 350 MW buttons, but have a few left. If you’d like one of your own, please stop by our office at 25 Love Lane in Concord, MA, to pick one up!

It was great to share the excitement of MW’s potential and versatility with so many new people. We heard from many (surprised) guests at our booth: “This is free?”  Yes! And so is the button.

Last week, Paul, Ed, and I did physics. This is such a rare event that it deserves note. We actually developed a theory, collected data, compared theory to data, came up with new ideas and tested them. We only wish kids everywhere could have the same experience.

This investigation was prompted by Ewa Kedzierska’s presentation at the World Conference on Physics Education in Istanbul in early July*. She presented a student activity on bungee jumping that claimed that the jumper falls faster than a free-falling object. This seems difficult to believe, in spite of video data she presented—collected and graphed by the wonderful COACH software—that clearly showed this to be true. We immediately thought of many reasons why this should be impossible. Imagine jumping without a tethered Bungee cord—jumper and cord would fall in free-fall just as Galileo proved in his famous Tower of Pisa experiment (never mind the fatal consequences—this is physics!). Attaching the far end of the Bungee rope would seem to apply an upward force that could only slow the jumper, not speed her up!

As typical science skeptics, we had to do it ourselves and understand the mechanism, if the effect was true. Following the maxim that was current when CERN found neutrinos travelling faster than light—“Extraordinary results require extraordinary evidence”—we needed to do the experiment ourselves and get a feel for the situation. So Ed  gathered a stepladder, chain (substitute Bungee), tennis ball (for the jumper), and a camera that takes 240 frames per second, and we collected data.

Paul, ever the theoretician, showed that the far end of a horizontal chain link held steady at the near end would fall faster than a free body, and hence, could impart some force to the falling chain. Thus, each chain link, on reaching the bottom of the “U” formed by the falling links, could impart a bit of force on the falling side and make it fall faster than free-fall. Another way of saying this is that each link, when brought to a halt, rotates 180 degrees and can exert some torque on the falling side.

We collected the data, and clearly saw the effect. It is real! And it is huge when the falling mass is small. We photographed side-by-side tennis balls, one attached to a chain and one in free fall. The one with the chain fell faster! Every time. The picture shows a frame from a movie of the experiment, clearly showing Paul about to fall (he didn’t), and the free-falling ball going slower.

Don’t believe us? Do it yourself. We attached a force sensor to the end of the chain and could detect the force from individual links. The force increased non-linearly and dramatically. Stopping the last link required 50 N even though the entire chain weighed only 4 N (see graph). We are still arguing about why the force increases so much for the last few links.

I noticed that sometimes if the falling part of the chain is close to the tethered part, the links at the bottom of the “U” do not rotate, but slide. When they slide, they do not rotate and, hence, should not accelerate the falling chain. We could hear the difference, but our results were inconclusive, because near the end of the fall, the chain doesn’t fall evenly and this causes it to revert to the link-rotation mode.

In our next blog, we’ll present the data and our analysis. Stay tuned.

I recently attended the modestly named World Conference on Physics Education in Istanbul. One of the highlights of the meeting was connecting with my old friend Ton Ellermeijer and meeting his colleague, André Heck.

Some of the most innovative developments in educational technology have been made during the last 25 years at the AMSTEL Institute at the University of Amsterdam, The Netherlands, under the direction of Ton Ellermeijer. At this university, Ph.D. students in physics and other sciences could specialize in education at the Institute, which was on a par with more traditional areas of physics research. Sadly, a new dean eliminated AMSTEL in 2010. Ton soldiers on from a nonprofit he founded in 1987 (Foundation CMA), but with a reduced staff.

AMSTEL developed extensive probeware for real-time data acquisition, as well as several generations of COACH, software for analyzing these data, modeling, control, video data capture and animations. This technology has been integrated into STEM instruction using well-designed and tested materials. One area in which they have done particularly interesting work is sports physics using video analysis. Widely used in Europe, this material is unknown in the U.S., which is a great loss.

André Heck worked with Ton for a decade and published nearly 60 scholarly articles on various aspects of this research. This wealth of material has recently been collected in André’s Ph.D. thesis.The print version of the thesis comes with a CD ROM that includes all these articles as well as considerable student materials.

We’re in the midst of a remarkable transition in education – a change that will give teachers more flexibility in the resources they use in their classroom.

The growing role of digital textbooks is gaining momentum. Major publishers are not just converting their textbooks to digital format, they’re also reconceptualizing them, adding a more diverse array of embedded interactives and providing states and districts with the option to pick and choose sections to meet local educational goals.

Think about this for a moment.

We are used to the monolithic textbook package – a basal textbook, lab manuals, CDs and other ancillaries. Each major publisher offers its package. States and districts decide which publisher’s package to purchase. End of story.

But that world is changing. A district might choose several chapters from one publisher and other chapters from a second publisher. From a third publisher, they might select a lab manual that is especially engaging for their students. And they might select multiple online resources to extend student learning.

From the teacher’s perspective, this is potentially liberating. Instead of working through the standard textbook and its aligned support materials, teachers have a richer set of options. They can select resources based on personal expertise, knowledge of their students, teaching style and familiarity with the growing array of digital interactives.

How does Molecular Workbench fit in? MW helps students understand fundamental principles of physics, chemistry and biology, yet it hasn’t always been clear how to fit this into the classroom, as it might seem a diversion from the flow of the textbook.

With a more flexible approach to teaching and learning, science teachers will be able to easily integrate the power of atomic and molecular simulations into their classrooms. This will not be an aberration, but the new norm.

This change will take a few years to fully play out, but it is a welcome transition away from the dominance of the standard, one-size-fits-all textbook and towards freedom to use a robust set of resources – including Molecular Workbench.

For 14 years I was a teacher at Lincoln-Sudbury Regional High School. Today is the first day of summer vacation for my friends and colleagues there. Now I work at the Concord Consortium, but I remember fondly that day when all the grades had been turned in and “vacation” began. I usually took a couple of weeks to crash and recuperate, but contrary to the understanding of most non-teachers, many teachers spend a significant portion of their summer writing curricula, going to conferences, getting ready for the upcoming year and continuing that perpetual search for new and improved ways to teach.

I taught chemistry and one of the most difficult things I had to deal with was the fact that pretty much everything we explored had to do with atoms and molecules too small to see. Somehow chemistry students need to find a way to imagine a world full of uncountable, invisible particles flying around at blistering speeds, colliding, reacting, attracting and repelling. For the past 10 years we have been developing a piece of software to address this challenge–the Molecular Workbench. During that time I worked with the MW team to create simulation-based activities that give students a concrete handle for thinking about the atomic-level world. Using these activities, students do virtual experiments with atoms and molecules, push and prod them, change the parameters of various simulations and build their own mental model of the atomic foundation of the world around them.

Do you struggle with this issue or just want to “play” with some molecules? Below are a few of my favorites:

• Intermolecular Attractions
• Chemical Bonds
• Diffusion and Active Transport (This activity is a nice connection with biology. Did I mention we have models across physics, chemistry, biology and biotechnology?)

Check out the huge collections of models and activities found at http://mw.concord.org and be sure to take a look at our latest work in making the Molecular Workbench run in the browser without the need for Java.

Have a great summer. May it be both relaxing and productive.

Music playlists are windows to the soul (or so the general wisdom goes). Your taste in music, including your personal favorites, reveals much about your personality, your lifestyle and your values. So too your favorite websites.

Do you bookmark your favorite websites in categories or sequence the most important ones first? Have hundreds of favorites? Or a top ten list? However you manage them, your Web, music and other playlists are an essential part of keeping your technical life efficient and effective.

Such a “playlist mentality” is becoming increasingly clear in education. And the teachers we’ve interviewed have requested personal playlists of Molecular Workbench activities and models.

Needless to say, each teacher has his or her own style of teaching, manifested in how they use MW. Some use it mostly for classroom demos, others focus more on direct student use. Some use MW just a few times during the year, others almost weekly. Some use it during class time, others assign MW activities for homework.

Teachers also vary in how they sequence topics during the year. One chemistry teacher might teach organic chemistry late in the year as a synthesis while another might teach it earlier as a way to whet the appetite and spark questions.

The MW development team confronted this diversity challenge (and opportunity) early on. It was clear we could not create, for example, a single master flow of MW activities for high school chemistry. Instead, we need to support differences among teachers by providing a rich variety of activities. Teachers can select, adapt and integrate models and activities into their own style and classroom flow.

As we’ve been documenting in videos and articles, we are now creating a Web-based Molecular Workbench system, which will give teachers more flexibility in how they select and sequence the activities. At the simplest level, they’ll be able to use standard browser tools to bookmark their favorites, organizing them in whatever flow they want. And our teacher interviews have pushed us even further in thinking about design.

Our goal is to include the ability for teachers to store personal MW playlists – with even more information than you get in a bookmark, such as level of difficulty and duration of activity. Teachers will be able to provide playlists to students or share them with colleagues.

We still have to work out the details, but we’ve heard from teachers and high on their wish list is a personal playlist with lots of flexibility to meet their needs and style. That’s the best way to make sure MW is effective and widely used!

It takes a lot of computation to model the atomic and molecular world! Fortunately, modern Web browsers have 10 times the computational capacity and speed compared with just 18 months ago. (That’s even faster than Moore’s Law!) We’re now taking advantage of HTML5 plus JavaScript to rebuild Molecular Workbench models to run on anything with a modern Web browser, including tablets and smartphones.

Director of Technology Stephen Bannasch describes the complex algorithms that he’s been programming behind the scenes to get virtual atoms to behave like real atoms, forming gases, liquids and solids while you manipulate temperature and the attractive forces between atoms. See salt crystallize and explore how the intermolecular attractions affect melting and boiling points. Imagine what chemistry class would have been like (or could be like today) if the foundation of your chemical knowledge started here.

Technology and Curriculum Developer Dan Damelin goes on to describe how open source programming opens up possibilities. For instance, Jmol is a Java-based 3D viewer for chemical structures that we were able to incorporate into Molecular Workbench to allow people to easily build activities around manipulation of large and small molecules, and to make connections between static 3D representations and the dynamic models of how molecules interact. We’re planning to build a chemical structure viewer that won’t require Java and will extend another open source project based on JavaScript and WebGL to visualize molecules in a browser.

Interested in this innovative programming? Great! We’re looking for software developers.

The next-generation Molecular Workbench has a fundamental feature that is both simple and profound: MW models will be embeddable directly in Web pages. This simple statement means that anyone will be able to integrate these scientifically accurate models into their own work—without having to launch a separate application. Teachers will embed MW models and activities into their own Web pages. Textbook publishers will embed them in new e-books.  There is much room for creativity and partnerships here.

The significance of this advance struck me at a recent conference on educational technology sponsored by the Software & Information Industry Association. Many creative people and companies attended, from large publishers to innovative startups. Throughout the presentations and conversations, I envisioned ways these potential partners might use MW to enhance their products and services.

Ron Dunn, CEO of Cengage, gave a keynote describing their new digital textbooks and aligned homework helpers and other digital resources. He pointed out that 35% of their sales are “digitally driven,” and that technology is essential to their future. Other major publishers echoed those messages. When publishers embed Molecular Workbench models and activities throughout their e-books as a consistent modeling environment, students will be able to investigate fundamental principles of chemistry, physics and biology more deeply than the simple animations and videos now so typical in e-books.

SmartScience is a startup, developing supplemental science education activities. Their idea to link videos of science phenomena with corresponding graphing tools is clever. For example, in a time-lapse video of rising and falling tides, students mark the ocean height and automatically see their data in a graph in order to understand both the scientific phenomena and the graph output. Augmenting reality is great, and we love the idea of integrating videos of physical, chemical and biological processes at the macroscopic scale with MW models to show what happens at the microscopic scale.

Karen Cator, Director of the Office of Educational Technology at the U.S. Department of Education, discussed a new framework for evaluating the effectiveness of educational technology projects. Software can monitor how students work their way through online problems, providing teachers with deeper insights on student learning, especially in terms of scientific thinking and problem-solving skills. Teachers can focus on students’ higher-level thinking skills, and provide useful, real-time feedback to identify strengths, progress and areas in need of help. We agree whole-heartedly and have been working on ways to capture student data in real time and provide feedback loops for teachers. Our next-generation Molecular Workbench will record what students do as they explore the models and make that information available to teachers and researchers.

Partnerships with creative teachers, publishers, and software developers will help us ignite large-scale improvements in teaching and learning through technology. That’s our mission and our goal for Molecular Workbench. Thanks to Google funding, we’re working to increase access to the incredibly powerful next-generation Molecular Workbench.

The opposite of Thomas Dolby

I was terrible at the first four weeks of organic chemistry. I just couldn’t get the right pictures into my head.

The depictions of the chemical reaction mechanisms I was supposed to memorize seemed like just so many Cs (and Hs and Os and, alarmingly, Fs) laid out randomly as if I were playing Scrabble. And I swear the letters rearranged themselves every time I looked away, like a scene out of a movie about an art student’s science-class nightmares (minus the extended fantasy sequence in which the letters grow fangs and leap off the page to menace the poor protagonist – unless I’ve blocked that part out).

Fortunately, I knew exactly what to do: I had to start picturing molecules in 3D, and in motion, as soon as possible. That ability seemed to take its own sweet time to develop. But once things “clicked” and I could visualize molecules in motion, the reactions finally made sense, as did all the associated talk of electronegativity, nucleophilic attack, and inside-out umbrellas. I aced the final.

Now, our Molecular Workbench software isn’t specifically designed to help undergraduates get through organic chemistry. It is designed to help students at many levels by letting them interact with simulations of the molecular world so they get the right pictures into their heads, sooner. It’s here to help that future art student and movie director beginning to nurse a complex about the 10th grade science class he’s stuck in right now.

The weight of history

But the “Classic” Molecular Workbench we have now was built for a different world. It runs in desktop Java, for one thing, meaning (among other things) that it’ll never run on iPads. More fundamentally, it was built to be “Microsoft Word for molecules” in a time when Microsoft Word was the dominant model for thinking about how to use a computer:

“Hello, blank page! Let’s see, today I’ll make a diffusion simulation. I should write something about it … Let’s make that 12-point Comic Sans. No, my graphic designer brother-in-law keeps telling me not use that so much, so Verdana it is, then. Now how do I add that model again? Oh yeah, Tools -> Insert -> Molecular Model…”

This model is constraining even though it’s always been possible to download and open Molecular Workbench via the Web, and even though MW saves simulation-containing activities to special URLs.

We have somewhat different expectations these days because of the Web, social media, mobile apps, and casual games. If I build a great in-class “activity” based on a series of molecular models, then I should be able to share that activity with the world with minimum difficulty. And if you find one of the simulations I created particularly illustrative, you should be able to put that model in a blog you control, or include the model as part of your answer to a question on http://physicsforums.com/.

Moreover you ought to be able to perturb the running simulation by reaching out and touching it with your fingers, or simply by shaking your tablet to see what effect that has on the simulation “inside” it. You shouldn’t be required to operate the simulation at one remove, via a mouse and keyboard, when it’s not necessary.

That’s why we’re excited about the Google-funded, next-generation Molecular Workbench we have started to build. The HTML5 + JavaScript technology we’re using to build the next generation of our MW software (hereafter called NextGen MW for short) will make it much more practical to enable these kinds of uses.

Boldly doing that thing you should never do

But designing NextGen MW to be a native of the real-time Web of 2012 rather than a visitor from the land of 1990s desktop computing means that we’re committed to rebuilding the capabilities of “Classic” Molecular Workbench from scratch. That is, we’re doing the very thing Joel Spolsky says you must never do! But ignoring platforms which run Java badly or not at all isn’t an option, and neither is trying to run Classic MW in a Google Web Toolkit-style compatibility layer that compiles Java to JavaScript. (With the latter option, we would almost surely be unable to optimize either the computational speed or the overall user experience well enough to make it practical to use NextGen MW on phones, inexpensive tablets, or even expensive tablets. But even that misses the point. We’re not a consumer products company trying to optimize the return on our past investment. We’re an R&D lab. We try new things.)

But writing things from scratch poses a challenge. We want the molecular dynamics simulations run by NextGen MW to run “the same” as the equivalent simulations run in Classic MW. But “the same” is a slippery concept. In traditional software development, asking two different implementations of a function or method to produce the “same” result often means simply that they return identical data given identical input, modulo a few unimportant differences.

It would be nice to extend this idea to the two-dimensional molecular dynamics simulations we are now implementing in NextGen MW. Classic MW doesn’t have a test suite that we can simply adapt and reuse. But, still, we might think to set up identical initial conditions in NextGen MW and Classic MW, let the simulations run for the same length of simulated time, and then check back to make sure that the atoms and molecules end up in approximately the same places, and the measurements (temperature, pressure, etc.) are sufficiently close. And, voilà, proof that at least this NextGen MW model works “the same” as the Classic MW model. (Or that it doesn’t, and NextGen MW needs to be fixed.)

Never the same thing twice?

Unfortunately, this won’t work. Not even a little bit, and the reason is kind of deep. The trajectories of the particles in a molecular dynamics simulation (and in reality) exhibit a phenomenon known as sensitive dependence on initial conditions. Think of two identical simulations with exactly the same initial conditions except a tiny difference. Now, pick a favorite particle and watch “the same” particle in each simulation as you let the simulations run. (And assume the simulations run in lockstep.) For a very short time, the particle will appear to follow the same trajectory in simulation 1 as in simulation 2. But as you let the simulation run a little longer, the trajectories of the two particles will grow farther and farther apart, until, very quickly, looking at simulation 1 tells you nothing about where to find the particle in simulation 2.

Very well, you say: maybe simulation 1 and simulation 2 started a little too far apart. So let’s make the difference in the initial conditions a little smaller. Sure enough, the trajectories stay correlated a little bit longer. But a very little bit. Here’s the rub: if you want to simulation 2 to match simulation 1 for twice as long, you need the initial conditions to be some number, let’s say 10, times closer. But if you need the simulations to match for 1 more “time” as long, that is, 3 times as long, you need the initial conditions to be 10 times closer still, or 100 times closer. And if you want simulation 1 to make a meaningful prediction about simulation 2 for ten times as long? Now you need the initial conditions to be a billion(10⁹) times closer. In practice, this means that if there’s any difference at all between the two initial conditions, no matter how seemingly insignificant, then outside of a short window of time the two simulations will predict very different particle locations and velocities.

Perhaps you think this is a contrived situation having nothing to do with comparing Classic MW and NextGen MW. Can’t we start them with, not just similar, but identical initial conditions? Unfortunately, this escape hatch is barred, too. The tiniest and most seemingly insignificant difference between the algorithms NextGen MW runs and the algorithms Classic MW runs right away result in a small difference in the trajectories, and after that point, sensitive dependence on initial conditions takes over: the subsequent trajectories soon become totally different. Trying to run precisely the same algorithms in NextGen MW as in Classic, down to the exact order of operations, would not only intolerably constrain our ability to develop new capabilities in NextGen MW, but would be futile: the differing numerical approximations made by Java and JavaScript would result in yet another small difference which would in short order become a big difference.

Science!

So, wait a minute: You can’t test NextGen MW against Classic MW because even the tiniest difference between them makes them behave … totally differently? How do we trust either program, then? And how is this science again?

Well, notice that I didn’t say quite say the two programs behave totally differently. Yes, the exact trajectories of the molecules will quickly diverge, but the properties we can actually measure in the real world — temperature, pressure, and the like — unfold according to laws we understand, and should be the same in each (not counting minor, and predictable, statistical fluctuations.) After all, we can do beautifully repeatable experiments on “molecules in a box” in the real world without knowing the location of the molecules exactly. Indeed, when van der Waals improved on the ideal gas law by introducing his equation of state, which includes corrections for molecular volume and intermolecular attraction, the notion that molecules actually existed was not yet universally accepted.

So what we need are molecular models whose temperature, pressure, diffusion coefficient, heat capacity, or the like depend in some way on the correctness of the underlying physics. Ideally, we would like to be able to run a Classic MW model and have it reliably produce a single number which (whatever property it actually measures) is demonstrably different when the physics have been calculated incorrectly. Then we could really compare NextGen MW and Classic MW — and perhaps even find a few lingering errors in Classic MW!

Unfortunately for this dream, our library of models created for Classic MW tend to be complex interactives which require user input and aim to get across the “gestalt” of molecular phenomena (e.g., one model encourages students to recognize that water molecules diffusing across a membrane aren’t actively “aiming for” the partition with a higher solute concentrations but move randomly). The models are not intended to be part of numerical experiments designed carefully to produce estimates otherwise-difficult-to-measure properties of the real world. They require substantial rework if they are to generate single numbers that are known to reliably test the physics calculations. For that matter, there aren’t many Classic models at all that conveniently limit themselves to just the features we have working right now in NextGen MW, and we can’t just wait until we develop all the features before we begin testing.

Charts and graphs that should finally make it clear

Therefore, we have turned to making new Classic MW models that demonstrate the physics we want NextGen MW to calculate, and comparing the numbers generated in Classic MW to the numbers generated when the equivalent model is run in NextGen MW. I’ve begun to think of this process as creating the “datasheet” for Classic and NextGen MW, after the datasheets which contain charts and graphs detailing the performance characteristics of an electronics part, and which an engineer using the part can expect it to obey.

So far, we’ve just gotten started creating the MW datasheet. I’ve written a few ugly scripts in half-remembered Python to create models and plot the results and so far, sure enough, it looks like an issue with the NextGen MW physics engine that I knew needed fixing, needs fixing! (The issue is an overly clever, ad hoc correction I introduced to smooth out some of the peculiar behavior of our pre-existing “Simple Atoms Model.” But that’s good fodder for a future blog post.)

But we have ambitions for these characterization tests. Using the applet form of Classic MW, we hope to make it possible to run each of these “characterization tests” by visiting a page with equivalent Classic and NextGen MW models side by side, with output going to an interactive graph. But with or without this interactive form of the test, once characterization tests have been done they will help us to find appropriate parameters for automated tests that will run whenever we update NextGen MW, so that we can be sure that the physics remain reliable.

I’ll update you as we make progress.

The Molecular Workbench has been downloaded over 800,000 times, making it Concord Consortium’s most popular single piece of software. We’re heading to a million and documenting in video both our history and our vision for the future.

Learn from Charles Xie, Senior Scientist and creator of the Molecular Workbench, about the computational engines that accurately simulate atomic motions, quantum waves, and atomic-scale interactions based on fundamental equations and laws in physics.

Amy Pallant, who researched student use of Molecular Workbench, describes the phone calls she made to students months after they’d used the software—and how impressed she was with their memory of the science of atoms and molecules.

Dan Damelin, Technology and Curriculum Developer, recalls his time as a classroom teacher and his frustration with trying to describe atoms and molecules to his students with words and pictures. He wanted more—and found it in Molecular Workbench!

Dan sums up the goal for Molecular Workbench: “It’s going to be just a given that this is a regular tool that will just be part of learning science.” We hope so.

We’re closing in on a million downloads and looking toward the next million.