Tag Archives: TU Dresden

Using twitter as a tool to let students discover that the topics of their courses are EVERYWHERE

This is a method that I have been excited about ever since learning about #birdclass in the “Evidence-based undergraduate STEM teaching” MOOC last year: Help students discover that the content of your class is not restricted to your class, but actually occurs everywhere! All the time! In their own lives!

The idea is that students take pictures or describe their observations related to course materials in short messages, which are posted somewhere so every participant of the class can see them.

One example where I would use this: Hydraulic jumps. As I said on Tuesday, hydraulic jumps are often taught in a way that students have a hard time realizing that they can actually observe them all the time. Most students have observed the phenomenon, maybe even consciously, yet are not able to put it together with the theory they hear about during their lectures. So why not, in your class on hydrodynamics, ask students to send in pictures of all the hydraulic jumps they happen to see in their everyday life? The collection that soon builds will likely look something like the image below: Lots of sinks, some shots of people hosing their decks or cars, lots of rivers. But does it matter if students send in the 15th picture of a sink? No, because they still looked at the sink, recognized that what they saw was a hydraulic jump, and took a picture. Even if all of this only takes 30 seconds, that’s probably 30 extra seconds a student thought about your content, that otherwise he or she would have only thought about doing their dishes or cleaning their deck or their car.


A collection of images, all showing hydraulic jumps of some kind.

And even if you do this with hydraulic jumps, and not with Taylor columns or whatever comes next in your class, once students start looking at the world through the kind of glasses that let them spot the hydraulic jumps, they are also going to look at waves on a puddle and tell you whether those are shallow water or deep water waves, and they are going to see refraction of waves around pylons. In short: They have learned to actually observe the kind of content you care about in class, but in their own world.

The “classic” method uses twitter to share pictures and observations, which apparently works very well. And of course you can either make it voluntary or compulsory to send in pictures, or give bonus points, and specify what kind and quality of text should come with the picture.

You, as the instructor, can also use the pictures in class as examples. Actually, I would recommend picking one or two occasionally and discussing for a minute or two why they are great examples and what is interesting about them. You can do this as introduction to that day’s topic or as a random anecdote to engage students. But acknowledging the students’ pictures and expanding on their thoughts is really useful to keep them engaged in the topic and make them excited to submit more and better pictures (hence to find better examples in their lives, which means to think more about your course’s topic!).

And you don’t even have to use twitter. Whatever learning management system you might be using might work, too, and there are many other platforms. I recently gave a workshop for instructors at TU Dresden and talked about how awesome it would be if they made their students take pictures of everything related to their class. They were (legitimately!) a bit reluctant at first, because you cannot actually see the topic of the course, measuring and automation technology (MAT), just the fridge or camera or whatever gadget that uses MAT. But still, going about your everyday life thinking about which of the technical instruments around you might be using MAT, and discovering that most of them do, is pretty awesome, isn’t it? And documenting those thoughts might already be a step towards thinking more about MAT. At least that is what I claimed, and it seems to have worked out pretty well.

We are about to try this for a course on ceramics (and I imagine we’ll see tons of false teeth, maybe some knees, some fuses, many sinks and coffee cups and flower pots, maybe the occasional piece of jewelry ), and I am hoping they will relate what they take pictures of to processes explained in class (like sintering, which seems to be THE process in that class ;-))

I am going to try to implement it in other courses, too. Because this is one of the most important motivators, isn’t it? The recognition that what that one person talks about in front of the class all the time is actually occurring in – and relevant to – my own life. How awesome is that? :-)

Have you tried something similar? How did it work out?

Preparing my workshop on how learning works

As you know, I’m preparing a workshop for teaching assistants in mechanical engineering at Dresden University of Technology. And even though I’ve given similar workshops successfully more than once before, it somehow happened that I changed my plan a bit here, and then changed a bit there, and am now constructing the whole workshop from scratch. Oh well…

Anyway, this is my current plan (which is going to change again more likely than not).

First: Start out with how people learn. It doesn’t work like this:

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This is not how learning works!

To talk about constructivism, I am using the examples presented in this blog post. I will talk about the consequences for teaching, for example that no matter how well we explain and describe, it would be really surprising if people understood exactly what we meant.

A nice game, by the way, that illustrates this nicely, was played at my friend Zhenya’s wedding: the couple is sitting, back to back, and each of them gets an identical set of Lego stones. Only that one person gets them assembled and the other person loose, and the person who got the assembled set has now to describe the assembled construction well enough that the other person can recreate it from their pieces! Quite fun, especially if — in contrast to how it worked at Zhenya’s wedding — they don’t define a common frame of reference first…

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“…and there are three branches on either side of the tree, and there is an apple hanging from the lowest branch on the right side”

Next, I want to talk about active learning. There are many papers on that that I have presented here on this blog, too, for example Freeman et al. (2014), Smith et al. (2009), or Crouch et al (2004). All those certainly deserve to be mentioned.

Then, I want to go into motivation, and you’ve seen a couple of blog posts on this recently (for example on why do students actually engage in learning activities or how do boundary conditions influence learning).

Obviously, the way those three topics are presented will not be a lecture, but I will be using various active learning methods (currently, there are a dozen on my list!). And while we are talking about those three topics and using those 12 different methods, we will always link back the current method to the theory of learning or motivation we are talking about at that moment.

Quite a tall order, you say? Well, yes. But all the parts have worked really well individually, so I am pretty confident that they will work even better when combined this way. I’ll let you know! And if you want to pre-book me to do a workshop where you are at, just get in touch! :-)

And even more on motivation

Last week we talked about motivation quite a bit: First about why do students engage in academic tasks?, then about how motivation is proportional to the expectation of achieving a goal. Today I want to bring it all together a bit more, by presenting two other theories (both also described in the Torres-Ayala and Herman (2012) paper, which — should you not have read it yet — I strongly recommend you look into!).

The self-determination theory describes three components of motivation: Autonomy (i.e. being able to determine what you learn, when you learn it and how you learn it), competence (feeling like what you are learning is giving you (more) options to achieve what you want to achieve) and relatedness (feeling connected to a group).


Self-determination theory

Those are all components that you, the instructor, do have some influence on. For example a feeling of autonomy can be fostered as easily as giving students the choice of three problem sets and asking them to choose the one they want to work on. Or to let them choose the group they want to work with rather than prescribing groups yourself. Or even only letting them determine the order in which you talk about homework questions.

A feeling of competence is a little more difficult for you to influence, but can be achieved by giving problem sets that gradually become more difficult, instead of giving them really challenging problems right away.

And a feeling of relatedness can be achieved for example by letting students choose who they want to work with, and by making sure you observe the group processes and intervene when necessary.

So far, so good.

There is a fourth theory in the paper, that I also drew little pictures for, but which when preparing for my upcoming workshop for TU Dresden, I chose to drop for now. After all, there is only so much theory one can take in at a time, and I know that what the participants of the workshop come for are methods, methods, methods. Which I might actually give them!

Anyway, I still want to look at the expectancy-value theory here.

Expectancy-value theory basically connects motivational beliefs with achievement behavior.

If you believe you can achieve your goal (expectancy) and reaching that goal is important to you (value), this will modify your behavior. For example, you will likely choose to practice more, and on harder problems than people who don’t have the same beliefs. You will likely be more persistent in pursuing your goal. The quality of your effort will be higher, your cognitive engagement will be higher, and your actual performance will also be better.


Expectancy-value theory

There are a lot of studies that link student beliefs with their behavior, and I find this super interesting. I’ll definitely get back to reading and writing about this very soon!

Ana T. Torres-Ayala, & Geoffrey L. Herman (2012). Motivating Learners: A Primer for Engineering Teaching Assistants American Society for Engineering Education

Motivation proportional to the expectation of achieving a goal?

In the last post I talked about a paper on “Motivating Learners: A Primer for Engineering Teaching Assistants” by Torres-Ayala and Herman (2012). Today, I want to present a different motivation theory, also described in that paper:

Attribution theory

Attribution theory basically says that motivation is proportional to the expectation of achieving a goal. Three different factors come into play: externality, stability and controllability. So there are basically four different mindsets students can have:

The most desirable one is one that places an emphasis on effort. Students believe that their chance for success is something internal and unstable, which means that since it is determined within themselves and is not fixed, it can be changed. So they know that if they work harder (or work differently), they can be successful. Since their fate is in their own hands, it is easy to be motivated to do your best.

Other students focus on their ability. This is not desirable, because while they still perceive their chance for success as something that is determined within themselves, they also think that they cannot influence whether they are successful or not. They typically feel like they are not smart enough (or — almost as bad — that they are so smart that everything has to go their way, no matter how much effort they put into it).

A third group of students focusses on task difficulty. Task difficulty is obviously determined externally and is stable – students are likely to feel like the exam was too difficult anyway and they had no chance of controlling whether or not they would be successful.

And then lastly, students that feel that their success depends on luck. Luck is also external, and it is unstable. They don’t know whether they will be lucky or not, but in any case they feel like there is no point putting in an effort.


My illustration of attribution theory of motivation

How does knowing about attribution theory help us improve our teaching?

When we know that students are basically only motivated when they feel like they have a direct influence on whether or not they will be successful, we should try and create an environment where learners do feel like that. That means fostering a growth mindset, i.e. not focussing on student abilities, but making sure they realize that they can learn whatever they chose if they put in the effort. It also means making sure that students can rely on the environment being exactly like you said it would be, meaning that if you say you won’t call on people which didn’t raise their hands, you can absolutely not do it. And it also means that students cannot get the impression that you favor some over the others, or that your mood and your grades depend on the weather. Lastly, it means that the task difficulty has to be appropriate. Some challenge is good, but if students don’t have a chance to succeed, they will not continue trying indefinitely (in fact, most quit a lot faster than expected). And who can blame them when their chances of success aren’t more or less proportional to the amount of effort they put in?

Ana T. Torres-Ayala, & Geoffrey L. Herman (2012). Motivating Learners: A Primer for Engineering Teaching Assistants American Society for Engineering Education

Motivation: dangle a carrot rather than threaten with a whip!

Why do students engage in academic tasks?

Next week I am giving a workshop on teaching large classes at TU Dresden. I gave a similar workshop there in spring, but because of its success I’ve been given twice as much time this time around. So there is a lot of exciting content that I can add to the (obviously already exciting!) workshop ;-)

When preparing what I want to talk about, I came across a paper that discusses motivation theories in the context of engineering education, and, even better, tailored to telling teaching assistants how they can improve their classes: “Motivating Learners: A Primer for Engineering Teaching Assistants” by Torres-Ayala and Herman, 2012. They give a great overview over theories on motivation, and today I want to talk about one of them:

Goal theory

Goal theory describes the different reasons why students engage in academic tasks. There are two different kinds of drivers students can have, avoidance or approach, and two kinds of quality of learning they can be striving for: performance and mastery.

Students who are in a state of avoidance and look for performance will state something like “I don’t want to fail this class!”, whereas students in avoidance striving for mastery will say “I don’t want to look or feel stupid!”. Students with an “approach” attitude, on the other hand, will say “I want to get an A!” if they are aiming at performance, or “I want to understand this material, so I can do … with it”.


Illustration of the different kinds of motivation described by the goal theory of motivation

While all four kinds of motivation for learning will produce some kind of learning, students with an approach mindset striving for mastery will be the most intrinsically motivated students who will likely do best.

So what does this mean for your teaching? Making students learn to avoid repercussions or public shaming, hence driving them into an avoidance mindset, is not as effective as creating a learning environment where students work towards something positive. And while having students work to earn, for example, bonus points gets them going in the short run, in the long run it is much more effective to help them discover what they can use the skills and knowledge for in their own lives for, discover the intrinsic value in them, and strive to learn because they want to apply the knowledge and skills to better their own future.

Or, as the authors say: Dangle a carrot to pursue rather than threatening with a whip.

Ana T. Torres-Ayala, & Geoffrey L. Herman (2012). Motivating Learners: A Primer for Engineering Teaching Assistants American Society for Engineering Education