New mechanics course; learning goals for (modern) mechanics

My research group was awarded a grant to explore how students engage with scientific practices in a introductory physics context. As part of that work, we are developing a new course that emphasizes core ideas of mechanics and scientific practices. Below is the start of that planning for this course, that will run next fall.

Check them out below and give me some feedback. Here’s where the inspiration for these goals came from.

Core Ideas and Practices

Ideas that are core to (modern) mechanics

  • C1 – Macroscopic phenomena are the result of atomic interactions.
  • C2 – Forces external to a system can change the system’s momentum.
  • C3 – Work done on or by a system and heat exchanged with the system’s surroundings can change the system’s energy.
  • C4 – Left to it’s own devices; a system will evolve to the most populated macro-state.

Practices

  • P1 – Developing and using models.
  • P2 – Planning and carrying out investigations.
  • P3 – Analyzing and interpreting data.
  • P4 – Using mathematics and computational thinking.
  • P5 – Constructing explanations.
  • P6 – Engaging in argument from evidence.
  • P7 – Obtaining, evaluating, and communicating information.

Learning Goals

Interactions and Motion

  • Identify when an interaction has taken place and determine what change has occurred such as changes in speed, velocity, state.
  • Perform the following mathematical operations on (physical) vector quantities: vector addition/subtraction, magnitude/unit vector.
  • Sketch vector quantities and perform graphical (physical) vector addition/subtraction.
  • Compute displacement, change in velocity/momentum, average/instantaneous velocity and acceleration and linear momentum.
  • Predict the motion of a single-particle system executing constant velocity or constant acceleration motion using appropriate representations (this includes verbal, graphical, diagrammatic, mathematical, and computational representations).
  • Collect, analyze, and evaluate data to determine the type of motion and the properties of the motion of a single-particle system.

The Momentum Principle

  • Determine the net force acting on a single-particle system using a diagrammatic representation (free-body diagram) and by performing any necessary calculations.
  • Explain the motion of single-particle systems using interactions (forces) as the basis for the explanation.
  • Apply the momentum principle (; ) analytically to predict the motion or determine the properties of motion/net force acting on a single-particle system where the net force is a constant vector (e.g., due to the near Earth gravitational force).
  • Apply the momentum principle (;) iteratively/computationally to predict the motion or determine the properties of motion/net force acting on a single-particle system where the net force is not constant (e.g., due to spring-like restoring forces or dissipative drag forces).
  • Collect, analyze, and evaluate data to explain the motion of objects and the responsible interactions.
  • Evaluate the applicability/limitations of models and the validity of predictions for different types of motion.

The Fundamental Interactions

  • Predict the motion of a system of gravitationally interacting objects analytically and computationally.
  • Predict the motion of a system of electrically interacting objects.
  • Evaluate the validity of predictions for the motion of gravitationally interacting objects.
  • Generate free body diagrams for a system of multiple objects and identify the Newton’s 3rd Law force pairs in order to explain physical phenomena.
  • Explain physical phenomena involving multi-particle systems using conservation of linear momentum.
  • Predict the motion for constituents of a multi-particle system, which includes predicting the motion of the center of mass (e.g., in systems where two particles collide elastically in one dimension).

Contact Interactions

  • Use the microscopic model of matter (ball & spring) to explain macroscopic phenomenon including tension, compression, speed of sound in materials, and friction.
  • Use the microscopic model of matter (ball & spring) to predict macroscopic material properties including the Young’s modulus and the speed of sound of a material.
  • Generate free-body diagrams for systems subject to tension, compression, and friction forces to explain and/or predict the motion of those systems.
  • Collect, analyze, and evaluate data to determine the properties of materials and to evaluate when linear models for those materials become insufficient to explain the data (e.g., Young’s modulus).
  • Use the microscopic model for gases (non-interacting particles) to explain phenomenon including buoyancy and pressure.
  • Generate free-body diagrams for systems subject to buoyant forces or external pressures to explain and/or predict the motion of those systems.

Rate of Change of Momentum

  • Generate free body diagrams for single-particle systems where the momentum is not changing (statics & uniform motion) to explain the motion of the system and/or to predict various physical quantities associated with the system.
  • Generate free body diagrams for single-particle systems where the momentum is changing (direction and/or magnitude) to explain the motion of the system and/or to predict various physical quantities associated with the system.
  • Decompose the net force vector parallel and perpendicular to the direction of motion to explain how the momentum a single-particle system changes magnitude and direction and apply this decomposition to explain/predict phenomenon such as decreased/increased apparent weight, the motion of gravitationally interacting bodies, and wires snapped during motion.

The Energy Principle

  • Evaluate when using the low-speed kinetic energy formulation is valid.
  • Determine the change in kinetic energy of or work done on/by a single-particle system.
  • Explain the sign of the work on a single-particle system using verbal, mathematical, diagrammatic, and/or graphical representations.
  • For single-particle systems where little or no heat is exchanged with the surroundings, use conservation of energy () to explain and/or predict the final state of the system (this includes choosing a system, and setting up initial and final states consistent with that system).
  • For multi-particle systems where a change of rest energy occurs, use conservation of energy () to explain and/or predict the final state of the system.
  • Compute the work done by non-constant forces, which are integrable and depend only on position (e.g., spring force).
  • Using diagrammatic, graphical, and/or mathematical representations of gravitational (electrical) potential energy, explain what motion is possible under given or desired conditions.
  • Explain under what conditions linear approximations to the gravitational potential energy are valid.
  • For multi-particle systems where little or no heat is exchanged with the surroundings, use conservation of energy () to explain and/or predict the final state of the system (this includes accounting for the potential energy of each pair of interacting particles; gravitational PE).
  • Analyze and describe the energy exchanges of gravitationally (electrically) interacting objects using a computer model.    

Internal Energy

  • For multi-particle systems where little or no heat is exchanged with the surroundings, use conservation of energy () to explain and/or predict the final state of the system (this includes accounting for the potential energy of each pair of interacting particles; spring PE).
  • For multi-particle systems with internal degrees of freedom, deformable states, and/or energy flow due to temperature differences, use conservation of energy () to explain and/or predict the final state of the system (this includes choosing an appropriate system, and accounting for energy, work, and heat exchanges consistent with that system).
  • Use the microscopic model for gases (non-interacting particles) to explain phenomenon such as air resistance and spin-dependent forces.
  • Predict the motion of systems that experience dissipative interactions computationally.
  • Collect, analyze, and evaluate data to determine the flow of energy in a multi-particle system.
  • For a multi-particle system, predict the motion of the constituent objects and analyze the exchanges of energy for the system using a computational model.    

Energy Quantization

  • Use conservation of energy and appropriate diagrammatic/mathematical representations to explain and/or predict phenomenon such as electron excitation, photon emission, and photon absorption.
  • Use diagrammatic representations to explain the effect of temperature on emission and absorption spectra.
  • Use conservation of energy, the microscopic model of atoms (ball & spring model), and diagrammatic/mathematical representations to explain and/or predict vibrational energy levels.
  • Use diagrammatic representations and the microscopic model of atoms to explain the broadening of emission lines due to rotational and vibrational levels within electronic levels.

Multi-particle Systems

  • For a multi-particle system, determine the center of mass, the momentum of the center of mass, and how the center of mass momentum is changing.
  • For a multi-particle system, explain and/or predict the motion of the center of mass.
  • For a multi-particle system, use conservation of energy () to explain and/or predict the final state of the system (this includes using rotational and vibrational kinetic energies as well as the moment of inertia for the particles and/or system).
  • For a multi-particle and/or deformable system, use conservation of energy for the center of mass system () to explain and/or predict the final state of the center of mass.
  • For a multi-particle and/or deformable system, use conservation of energy for the center of mass system () and the real system ()  to explain and/or predict the final state of the system.
  • For a multi-particle system, predict the motion of the constituent objects as well as the center of mass, and analyze the exchanges of energy for the both the center of mass and real system using a computational model.

Collisions

  • Evaluate if two colliding objects can be modeled as point particles (a construct with no extent).
  • For a system that can be modeled as two point particles, use conservation of energy and linear momentum to explain and/or predict the final state of the system after a one-dimensional collision has occurred.
  • For a system that can be modeled as two point particles, use conservation of energy and linear momentum to explain and/or predict the final state of the system after a two-dimensional collision has occurred.
  • Use the center of mass system to explain the motion before, during, and after the collision of two objects that can be modeled as point particles.
  • Use conservation of energy and linear momentum to explain the Rutherford model of the atom.
  • Collect, analyze, and evaluate data to determine the type of collision and the exchanges of energy occurring during a collision.
  • Predict the motion and analyze the exchanges of energy for two colliding objects using a computational model.

Angular Momentum

  • For a single-particle system, determine the system’s translational angular momentum.
  • For an extended or multi-particle system, determine the system’s translational, rotational, and total angular momentum.
  • For a single-particle system, use the angular momentum principle (; ) to explain and/or predict the motion of the system (this includes defining a rotation point and using the torque about that point).
  • Use the angular momentum principle to explain an object’s orbit.
  • For a multi-particle or extended system, use the angular momentum principle (; ) to explain and/or predict the motion of the system.
  • For a multi-particle or extended system, use the momentum principle (; ), energy conservation (), and the angular momentum principle (; ) to explain and/or predict the motion of the system.
  • Use the quantization of angular momentum to explain the Bohr model of the atom.

Entropy: Limits on the Possible

  • Use the microscopic model of matter (spring & ball) and quantized harmonic oscillation to explain the microstates of a collection of atoms.
  • Given a set of oscillators and amount of quanta (energy), count using mathematical and diagrammatic representations the number of macrostates and the number of microstates in a given macrostate (for large numbers of oscillators and quanta, use a computer to do so).
  • Use the concepts of microstates and macrostates to explain the flow of thermal energy between two solid materials in contact and the idea of thermal equilibrium.
  • For a system of two blocks in thermal contact, explain and/or predict the distribution of quanta at thermal equilibrium and use this to explain the second law of thermodynamics as well as the irreversibility of some physical processes.
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Can respecting student ideas drive higher attendance and deeper engagement?

This past week was Thanksgiving break, but Michigan State’s classes met until Wednesday. I had heard from colleagues that many students do not attend classes this week. In fact, some said that in their classes of 250+ students, about 10-30 will attend on the Wednesday before Thanksgiving, a claim corroborated by my own observations of other’s classes on Wednesday. This decreased attendance has led some of my colleagues (and me) to question why we even hold class on the day prior to Thanksgiving. To be fair to our students, East Lansing is a college town and most of them have family in other parts of Michigan, and who wouldn’t want to get home to their family earlier?

But this post isn’t about that (really). It isn’t about how my class attendance is still high, even for this past week, the penultimate week of class. What it is about is what I think drives that high attendance and what we might do nurture it. Some colleagues have asked me about this. My daily attendance still hovers around 85%, and this week I had 180 students attend Tuesday’s class and over 100 attend Wednesday’s.

I have been hard-pressed to identify a single feature that helps me understand this phenomenon. Some of my colleagues have attributed it to me (“Your students really like you.”), some to the pedagogy (“Your class is really active.”), and others to the syllabus (“Clickers are mandatory?”). I believe what is most likely contributing to this phenomenon is that students want to learn in an environment where their ideas are respected and validated. Respecting and validating student ideas is part of the instructor’s role and can be done using particular pedagogies, but is what, I believe, students want from the teaching of their classes.

Getting students to express their ideas in a large lecture section

In a class of more than 250, getting students to express their ideas freely is very challenging. Students must feel the learning environment is safe and comfortable, that is, that their ideas can be expressed, that we (the class) want to hear them, and that we (the class) want to discuss them to gain a deeper understanding. When students feel comfortable doing this, each class meeting is that much more valuable.

I have worked to cultivate this type of environment over the entire semester. Because of the size of my class (and other environmental and cultural constraints), my primary pedagogy has been clicker questions coupled to Peer Instruction. While clicker questions can be used for good as well as evil, I chiefly use them for two things: (1) To check how students’ “knowledge development” is going, and (2) To have students express their ideas (right or wrong). Checking in with students using qualitative clicker questions is a common pedagogy for this size of class. But, a number of clicker questions are simply “What do you think?” or “We’re just looking for ideas here.”

These questions are meant to act as discussion starters. They might involve thinking about a strategy to approach a problem (should we use conservation of momentum vs conservation of energy), what physics can be extracted from a given situation (what is the slipping condition for some system), or what a solution might imply about some real world application (what can a melting ice cube tells us about global warming). Students then offer answers and I encourage them to (respectfully) critique the ideas of others until we come to some consensus. Usually, this takes about 5-7 minutes of class time, which is a lot given the pace of this course (a chapter per week).

A “result” of respecting students’ ideas

This brings me to last Wednesday class when 100 students attended the last class meeting prior to Thanksgiving (which absolutely shocked my colleague who teaches after me). I asked my students in the previous class, “How many of you will be here tomorrow?” About 85 said they would. So, I asked my postdoc to attend class, so we could run a tutorial activity. Students are learning about simple harmonic motion; there’s few tutorials out there for this topic. We modified a middle-division tutorial developed at UMaine and GVSU.

The room in which our class is held is a typical large auditorium. Prior to class, we placed numbers 1-20 around the edges of the room and asked students to draw numbers from a hat. We started 20 groups of 5 (or so) students working on the tutorial. Only 1 student chose to leave when he realized there would be “no lecture.”

At first, most of the students were working individually (and were fairly quiet). As we walked around the room, we asked individuals to compare the answers they were writing with their group members (who were often working individually as well). Many times their answers didn’t agree, which lead to productive discussions. As the class went on, students began sitting on the floor and climbing over rows to discuss with their group mates. The volume in the room went up tremendously.

I have used tutorials a lot. I wrote several for middle and upper-division mechanics while I was a postdoc at Colorado. Just like clickers, they are not a silver bullet, but they can be used to encourage students to express their own ideas. And if the tutorials are facilitated such that students feel their ideas are validated and respected (even when they are not quite correct), they work hard to develop their own understanding of the material.

Investing in students

In the future, I would like to use more activities like tutorials in classes at MSU. The challenge is the scale that we are working with. Empirical evidence shows that a student-to-instructor ratio of around 20:1 works well for these activities. In this class meeting, we were fortunate that one of our lecturers was very interested in observing the tutorial. We started with a 50:1 ratio, and he quickly became another facilitator giving us a ratio closer to 30:1. For a 250+ person class meeting, this represents an investment of 12 to 13 instructional staff (professor, graduate and undergraduate TAs), which is tall order. If you have ideas on how to broach this, I’d love to hear them.

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Rethinking Introductory Physics at Michigan State

It’s been a while, but I’ve been busy. At MSU, we are beginning to reconsider what and how we teach introductory physics. This is, in part, motivated by our recent award from the American Association of Universities, and, in part, by our own faculty’s interest in changing the way we do things. The first steps of this transformation are considering what is important in our introductory courses, and what we want students to be able to do when they complete these courses. This is not generating a list of topics or skills. We are thinking very carefully about what the core ideas are in mechanics and electromagnetism and what practices we want students to engage in when taking our courses. Ultimately, we will blend the core ideas and practices into what we really want students to know and be able to do when they complete our courses (i.e., learning goals).

So, we got 20 physicists in a room and went at it. Believe me, this was tough. As it turns out, many faculty haven’t thought about their courses in this way. It’s absolutely fascinating to hear them discuss topics, move to concepts, and then finally to why the concepts matter. This was a productive and lively discussion. In the discussion, we produced the following lists from which we will build out our goals, and, eventually, our new curriculum. To be clear, these are traditional physics faculty engaging in a discussion about what they want their students to know and be able to do.

So take a look at the list and tell me what you think.

Core Ideas in Mechanics

  • Energy is conserved.
  • Forces cause changes in momentum.
  • Torques cause changes in angular momentum.
  • Exchanges of energy increase total entropy.
  • Measurements depend on frames of reference frames.

Core Ideas in E&M

  • Charges generate fields.
  • Fields affect charges.
  • Charge is quantized and conserved.
  • Energy is conserved.
  • Light can act as a wave or particle.
  • Measurements depend on frames of reference.

Scientific Practices

  • Construct and use models.
  • Communicate science effectively.
  • Engage in evidence-based arguments.
  • Evaluate solutions for reasonability.
  • Solve problems using mathematical and conceptual reasoning.
  • Design and execute experiments.
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Your World is Your Lab

You are teaching a class of students who are learning physics for the first time in their lives. What is important for them to experience? Using physics concepts? Doing physics experiments? Communicating physics ideas? “Thinking like a physicist”? How would you design a class to create these experiences?

Maybe you’d design a model-focused course that emphasizes laboratory experiences? And to that you might add video analysis; it’s just cool for students to take and process their own data. In my opinion, video analysis also helps students experience physics in a more authentic way. You might also have them write a few simulations that model the physical phenomena they are learning about. This gives students another “cognitive hook” to use when thinking and talking about physics.

And how many students are you teaching in this theoretical class? 10? 20? maybe 40? What about 40,000? Or more?

A MOOC with a lab

As I mentioned in an earlier post, I am helping to do research in a massively open online course (MOOC). Our course is called “Your World is Your Lab”. By leveraging modeling, video analysis, and numerical computation, we are attempting to provide this type of authentic, scientific experience. Here’s the intro video for the course:

Now I am very skeptical of this MOOC business. But, I think it’s also important to know a lot about something before dismissing it entirely. That’s why I’m deeply involved in the planning of and research into this MOOC.

“Your World is Your Lab” is a different type of MOOC because it contains a home laboratory component. Students go out into the world, take video of some phenomenon, analyze it, and construct a video report of their observations and analysis. These reports are graded by their peers (i.e., other students taking the MOOC) and these laboratories constitute the major portion of the “grade” in this MOOC.

My main issue with MOOCs is that they perpetuate the transmissionist model of education (see below).
Calvin
I think laboratory experience helps to bring in the constructivist model and by coupling that with “peer review”, we actually emphasize that doing physics is a social act.

Unfortunately, that is where it ends. Lectures are pre-recorded, interactions with the teaching staff are limited, and homework and exams are computer-based. So, we will have a pretty cool lab experience (if people can figure it out) and an average lecture experience.

Participation will vary greatly, and it’s unclear how many students (and how often they) will perform the laboratories. This is an ambitious undertaking; porting an entire introductory physics course to the MOOC format. That is why the research is so important.

Major media outlets (e.g., David Brooks in the NYT) are touting the coming digital education revolution, but it’s unclear if students will actually participate when the course looks like a real college course. Equally unknown is which students complete the course, what factors influence their success, and what they learn from these courses. To start answering these questions, we are collecting a variety of demographic data, answers to conceptual assessments, and affectual measures from students taking our MOOC.

I hope that some of you will sign up for the course and tell me what you think. Oh, and if you are a high school teacher who completes the course, you can earn 6 continuing education credits from AAPT.

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A thoughtful review of the MOOC experience

To follow up this post about MOOCs, I wanted to mention an opinion piece in the New York Times by A.J. Jacobs that I read yesterday.

In it, Mr. Jacobs describes his experiences with eleven different MOOCs. The beginning of his piece bothered me quite a bit because it read like the same old stuff. Early on he says, “I’m getting Ivy League (or Ivy League equivalent) wisdom free. Anyone can, whether you live in South Dakota or Senegal, whether it’s noon or 5 a.m., whether you’re broke or a billionaire.” It’s unclear that impoverished Senegalese are completing MOOCs en masse. More likely, white men from the US, Canada, and Europe are the certificate earners.

But later in the article, he gives a thoughtful critique of each aspect of his MOOC experiences. The most telling part is the low grade he gives to instructor-student interactions. Most instructors can hardly manage a class of 200, let alone a class of 40,000. MOOCs have very little instructor-student interaction. It’s a one way conversation.

Jacobs believes that, “[f]or MOOCs to fulfill their potential, Coursera and its competitors will have to figure out how to make teachers and teaching assistants more reachable. More like local pastors, less like deities on high.” That is, to do anything meaningful, MOOC providers must abandon the transmissionist model of education and develop technologies to facilitate that change. He goes on to mention that providers are looking to enhance instructor-student interaction.

But, what will the increased cost of those interactions be? Could MOOC providers produce something close to the brick-and-mortar experience? I’m still pretty skeptical. But then again, I love my ivory tower.

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What’s the COWYAAPT section up to?

I went to my AAPT sectional meeting today. I love going to sectional meetings. Everybody shares why they are so excited to be a physics teacher, which always reminds me how much fun my job really can be. I just want to share some of the highlights.

  • Steve Spangler (who lives in the Denver area!) dropped by for the keynote address.He showed us a few demonstrations and told us how he got into TV. It’s a really cool story involving someone from NBC asking if he wanted to be the next Don Herbert (Mr. Wizard). Apparently, he called Don and asked him for advice when he first started. Don said, “Don’t let the bastards put you in a lab coat!”, which means try to make science accessible. Don’t look like a “scientist.”He also told us about the time he was questioned by police for blowing up bottles of liquid nitrogen. Here’s the video of that:

    I had not heard of Steve Spangler before this meeting, but I will definitely be using his YouTube channel for my future demo ideas.
  • My buddy, Ariel, gave a great talk about PhET sims. He talked about how sims are designed and why they are designed they way they are. He left folks with a few best practices. He said, “just let students play with the sims for 5 minutes.” You won’t have to tell them where all the controls are. They’ll figure it out themselves.
  • I gave on talk about the Global Physics Department that was well received. I have a feeling there’s going to be a lot of new blood joining the meetings. Here’s a copy of my powerpoint slides for anyone interested.
  • Stephan Graham (Arrupe Jesuit High School) gave a fantastic talk about how he teaches the language of physics using literature. He teaches at a predominately Latino school where more than 50% of students are English Language Learners. Stephan uses short stories in his physics classes to get students to identify when “physics” language is used in a physics context and when it is used in a figurative/literary context. Very cool stuff. Here’s the list of short stories he recommended: Bill Naughton’s Spit Nolan (velocity and acceleration), Liam O’Flaherty’s The Sniper (projectile motion), Francisco Jimenez’s The Circuit (series and parallel circuits), Michael Cunningham’s White Angel (impulse and momentum), and Kurt Vonnegut’s Harrison Bergeron (force).
  • Finally, the whole meeting ended with the classic sledgehammer/nail bed demo. Here’s a video I shot.

I’m really sad to be leaving this section. I’ve been to only two meetings, but I can tell it’s a really tight-knit group that is doing a lot of great things in the physics education community.

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The revolution is digital. Or is it?

Massively open online courses (MOOCs) are all the rage among “elite” universities. And why not? What university wouldn’t want to teach more students, grant more degrees, and diversify their alumni?

The problem is that the MOOC phenomenon is the higher-education equivalent of “Keeping up with the Joneses.” Universities are getting involved because others are, but it’s unclear what students are learning (in anything) in these new environments.

Now, I don’t want to come off as critiquing something that I know very little about. In a future post, I will talk about my involvement in the development of and research around an introductory physics MOOC. But for now, let’s just talk about what folks are saying about MOOCs, and what the reality seems to be (so far).

Can we transmit knowledge?

There are a number of articles written by well-known journalists on the “MOOC revolution.” But, most of them seem to say the same thing, universities are too darn expensive and MOOCs can help change that. Now, those statements are connected by a tenuous strand of reasoning: MOOCs can reproduce a university education. David Brooks goes into detail about what online education might be able to do for students.

But, I think he misses the point entirely. Education is not just about transmitting knowledge for preparing the workforce. It’s also about empowering individuals to live in the world and empowering society to meet the challenges of our modern age. Education is the means by which society replicates itself. It is how we move forward together. A college education does not just prepare you for a job, but it prepares you to interact with the world, to process complex information and make decisions based on that information, and to engage in societal discussions.

Sure, you might call some of this “practical knowledge” (as Brooks seems to), but his framing that such knowledge is imparted or absorbed says a lot about what he thinks education is. To him and others writing about MOOCs, education is the transmission (or absorption) of knowledge. That is why it is so easy for him and others to accept the MOOC model. If we can simply figure out how to transmit this knowledge into the student’s mind as efficiently as possible, we can “educate” millions.

It’s premature to think that MOOCs can or will replace brick-and-mortar institutions. In 1913, Thomas Edison said of the motion picture, “Books will soon be obsolete in the public schools. Scholars will be instructed through the eye.” It’s been a century and that still hasn’t happened. Why? Because there’s much more to education than just transmitting knowledge.

But what does the data say?

The data from MOOCs are just coming in. Over the next couple of years, we will collect more data that will help us explain what these new environments are doing for students.

The best preliminary data that I have seen so far comes from this presentation by four computer science professors. It shows the following:

  • There appears to be a well-established power law drop off for MOOC students. Only about 5-10% will earn a certificate, that is, complete the course successfully (Slide 4).
  • MOOCs are not serving a diverse audience. Certificate earners are predominately middle-aged, white males (Slide 31).
  • MOOCs are serving those who already have degrees (perhaps degrees in the field). The vast majority of certificate earners tend to hold at least a bachelor’s degree (Slide 32).

Now, these conclusions are based on a handful of courses. So that doesn’t mean such results will hold. Moreover, it’s not clear from these data what certificate earners have learned from these courses. There’s no independent measure of learning in these courses, we just see what students completed as part of the course.

My involvement in an introductory physics MOOC attempts to answer some of these questions, at least for a physics course marketed to first-time physics students. We are collecting much more demographic data from students and giving pre-post assessments that can be compared to brick-and-mortar performance. I guess we will see what happens in the fall.

Feel free to leave your comments on MOOCs below.

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Disclaimer:
The views presented here are not necessarily those held by other members of my research group. The work discussed here is under active investigation or development and might be part of a peer-reviewed journal article in the future. I present it here because it's important that this information be discussed among those working in the community. If you are interested in any of the work I discuss or in collaborating with our group, please contact me.
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