Tag Archives: literature

What’s your perspective on good teaching?

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Taking a test as a basis for reflection in teaching beliefs, intentions and actions.

I am always looking for ways to make teachers think – and talk – about best practice in teaching. And one important aspect is, of course, what the teachers themselves believe to be best practice. There is no one single answer to this, and many people only start reflecting on it when we start talking about it.

After sifting through several others, I came across a tool recently that I liked a lot: The Teaching Perspectives Inventory. You are asked a lot of questions about what you believe you should be doing, what you are doing, and what you are planning on doing in your teaching (focussing on one single setting, because your teaching style likely varies depending on the context). The tool then groups your answers and gives you scores for five different teaching perspectives, both summing up all your answers and differentiating for beliefs, intentions and actions. There are very helpful videos that show how to read the results by talking through an example.

I had thought a lot about what my perspectives in teaching were before taking the test, but I found it enlightening nevertheless and would totally recommend you take the test!

 

Oceanographic concepts and language, reloaded

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How we might misunderstand our students and therefore diagnose misconceptions where there are none.

Imagine you are in an Earth Sciences class and your teacher talks about glaciers and how they are “retreating”. They probably also show you pictures comparing a very old photograph from, say, 1900, with a current photo of the same glacier. What you see is that where used to be ice, ice and nothing but ice, now there is likely only a little left somewhere up high on a mountain, and that the whole plain in the foreground that used to be covered in ice is now bare rock. I’m sure we’ve all sat in that class at some point.

Now consider the everyday usage of the term “retreat”: When we talk about a retreat, we talk about movement away from a place or situation especially because it is dangerous, unpleasant, etc.. So what a student who hasn’t thought about glaciers much before associates, is the poor glacier crawling back up the mountain to safety.

This is a pretty easy misunderstanding to clear up. If you think about it, there is no mechanism that would drive enormous amounts of ice up a mountain, and the other explanation, that the backward melting at the front of the glacier is faster than the forward motion of the glacier itself, is a lot more plausible.

This was one of the examples I used to set the scene for my recent talk at FIE in Madrid. Our paper on “misalignment of everyday and technical language” is basically a summary of my earlier posts on this blog on oceanography and language (see below), where we talk about a couple of cases where everyday and technical language are misaligned, and to what kind of problems that can lead.

But there are other misunderstandings that are a lot more persistent and harder to even diagnose. I recently read the paper “”Force”, ontology, and language” by Brookes and Etkina (2009). I found it a really difficult read, but a very worthwhile one.

What I’m taking away from it:

When physicists talk about force, they typically do so in a very short-hand kind of way. As they talk among themselves, this is not a problem because the meaning of the shorthand has been negotiated and even though people might not be aware that they are talking in metaphores, everybody is aware of the underlying meaning of what is being said.

The authors now span the space of physicists’ language along two axes: role and location. This leads to four quadrants in which they can place recorded physicists’ language about forces (see figure below):

  1. active & internal: Force is an internal desire or drive. Example: “the moon is attracted to the Earth”.
  2. active & external: Force is an agent. Example: “The force acts on an object”.
  3. passive & external: Force is a passive medium of interaction. Example: “A applies force to B“
  4. passive & internal: Force is a property of an object. Example: “the tension in a rope”
Brooks2009

My rendition of Brookes & Etkina (2009)’s Figure 1: The dimensions of physicists’ language about force.

Looking at those examples (and there are more in the paper, so go read the original rather than my take on it!) it is clear that in the way we speak about force, we do assign properties, at least by the way we are using language about it, if not intentionally.

The authors come up with a model of language in physics and do a very careful analysis of what this means for different case studies, but the very compelling message that I am taking away from this is:

What we might conceive as misconceptions on the student’s part might very well be just a miscommunication because, taking all the grammatical clues I am giving through my language, the student understands what I am saying differently from what I think I am saying. Being aware of this might help us answer the questions the students are asking, rather than the ones we are hearing. Which, in turn, will make it easier for them to understand what we think we are saying. So let as close with a quote of the final two sentences of the paper: “If learning physics involves learning to represent physics, then learning physics must involve a refinement of terminology and cases in language. And part of the teacher’s role in the classroom must be to support that learning process—something that we, as teachers, are often unaware of.”

On purpose and aim of hands-on experiments.

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Why it is important to make clear the purpose of experiments in teaching.

As you all know by now, I am a big fan of hands-on experiments in teaching. One reason is that I enjoy running the experiments. Another is that students generally enjoy running experiments. And the third is that I believe that hands-on experiments offer learning opportunities that cannot be replaced by any other form of teaching, and that are a valuable and necessary part of any science and engineering education.

All the more reason to pay close attention when colleagues say that they don’t see the value in letting students do experiments themselves. In the paper “What is the purpose of this experiment? Or can students learn something from doing experiments?” Hart et al. (2000) state that despite of many historical claims of the value of lab work in schools, research often doesn’t support the expectation that lab work leads to meaningful learning. They give many reasons that can prevent students from actually learning in lab work settings, for example that students are, in those settings, mainly concerned with the completion of the task at hand, which can overwhelm any serious learning possibilities. In the same vein, lab experiments can lead to a cognitive overload because there are so many things to recall at the same time. Most importantly, the authors state that students often fail to relate the hands-on experiments to the other aspects of their learning.

The authors go then on and run a lab course which is not primarily aimed at conveying scientific knowledge, but which has as a main purpose that the students understand how the scientific process works. From that successful course, the authors come to the more optimistic conclusion that lab work can actually help learning – if not learning of science knowledge, so at least of other things.

The main point I am taking from the article is that the purpose of the lab work (the pedagogical reason why the teacher chose to run an experiment at that specific time) and the aim of the experiment (for example proving Newton’s law) are two very different things, that need to be communicated as two very different things. Students need to be aware that the process is the most important thing right now, or their learning to use a specific instrument, or whatever the purpose is, so they can focus and consciously engage in the learning process rather than focus on something meaningless (like finding the correct numbers to write in the lab report without understanding the process).

This article is very interesting to me, because I am currently trying to structure an article on the purpose of lab work at university. Apart from stressing again the importance of discussion in the process, I think we need to clearly distinguish two purposes of lab works: understanding of concepts and learning of methodology. And these two types need very different labs.

If the purpose of lab work is conceptual understanding, experiments need to be simple, easy to conduct and quick. That way students have the time for discussion and reflection that they need to actually learn and understand.

If the purpose, on the other hand, is to learn a methodology or how to handle an instrument, the experiments can be a lot more complex and time-consuming. But it is important that in this case it is clearly communicated that the purpose is to learn a new practical skill, otherwise students are likely to just go through the steps, completing them one after the other without actually engaging in the learning process.

And then in both cases it is of course important that the whole course is designed following the concept of constructive alignment: If the purpose of the experiment is to learn how to use the scientific method, this is what should be practiced during the course and also what should be evaluated in the end, regardless of whether the scientific method led to the correct results of any given experiment. If, however, the purpose is to learn to use an oscilloscope, this is what needs to be practiced and evaluated – not whether the students know any theory about oscilloscopes.

So what is the purpose of the experiments you are having your students run?

All learning is relearning

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Where did the concept of “elicit, confront, resolve” come from?

We often imagine that ideal learning happens the same way we often imagine ideal teaching*: We enter a room, students are waiting with anticipation of the new topic, the blackboard is clean and we can dive in and start drawing a picture from scratch. The students have no prior knowledge (or only exactly the prior knowledge we want them to have) and it is organized exactly the way we want it to be. The reality is, of course, different. The blackboard is hardly ever clean when we enter the room. And what is worse: Everybody always has a more or less articulate idea on any topic, and those ideas will interfere with any new information or theory that the teacher wants to convey.

Kolb states that a lot of resistance to new ideas stems from their conflict with pre-existing ideas that are inconsistent with the new ideas we are trying to convey. From this, he suggests an education process that has been termed “elicit, confront, resolve” by others later (compare, for example, McDermott’s (1990) Millikan lecture), which Kolb describes as “If the education process begins by bringing out the learner’s beliefs and theories, examining and testing them, and then integrating the new, more refined ideas into the person’s belief system, the learning process will be facilitated”.

The new ideas can enter the learner’s belief system in two ways: By integration or substitution. According to Kolb, integration lets the new ideas become part of a highly stable conception of the world, whereas substitution can lead to a dual theory of the world where both ideas exist in parallel** and where the reversion to earlier understanding is a possibility.

The challenge is now to successfully integrate the new ideas with the pre-existing ideas. While for example Muller et al. (2008) show that explicitly stating misconceptions helps subsequent learning of the correct conceptions, there is still no easy fix that could routinely be used in university teaching (at least that I am aware of). Plenty of work to do still! :-)

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*of course, this is not _my_ idea of ideal teaching

**a nice example of two parallel ideas about gravity is shown in Derek Muller’s video on “misconceptions about falling objects” where the interviewees explicitly state what they expect will happen, which is in contrast with what science told them will happen.

Kolb’s learning cycle

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A very brief history of learning theories.

Discussing a paper on learning theories with a friend last week, I realized how far I have come from when I first started reading those papers. Then I felt like most of those papers were a lot of hot air, a lot of waffling around, completely disconnected from the real world. Especially when looking at the diagrams for some of the theories, I just never got what all the fuss was about. So now I am hoping to explain one theory in a way that is understandable – and maybe even interesting. Give me a shout if things are unclear and I’ll try to do better!

One of the classic papers in education is Kolb’s (1984) “Experiential learning: experience as the source of learning and development”, where a theory of the process of learning is presented. Kolb bases his theory of learning on earlier theories of Lewin, Dewey and Piaget, and rereading his paper recently put things into a new perspective for me.

Lewin imagines learning as a cyclic process, where he emphasizes the here-and-now concrete experience to test abstract concepts. Learning, as a feedback process, starts from a concrete experience, which leads to observation and reflection. From that, abstract concepts are formed to explain the new situation. Those concepts and their implications are then tested in even more new situations, leading to new concrete experiences, and the cycle is hence repeated over and over again. So far so good.
Lewin_learning_cycle

My adaptation of Lewin’s learning cycle

A similar feedback process is described in Dewey’s work, where a purpose is formed through a cycling through similar stages: An initial impulse (I1) is carried out, and its effect on the surrounding conditions is observed (O1). Together with knowledge (K1) of what has happened in similar situations in the past, as well as through information, advice and warnings from others, a judgement (J1) is created, which leads to a modified impulse (I2). This would be where Lewin starts the second round around his circle, but to visualize that the two impulses are different, Dewey does not close the circle, but rather forms a spiral. Still the process is repeated until several cycles later a purpose is formed. The purpose differs from the initial impulse: “mature purpose develops from blind impulse” through modification by observation, knowledge and judgment.

Dewey_learning_cycle

My adaptation of Dewey’s learning spiral

Piaget then describes the learning process as a cycle of interactions between an individual and its environment. He links different steps in the cycle to steps in child development. For me, his main message on the topic is the interaction between the accommodation of concepts or schemas to experiences, and the assimilation of events or experiences into existing theories. He describes two extremes: One, where accommodation is a lot stronger than assimilation, where actions of the individual are determined completely by the environmental constraints. Or the other, where assimilation is a lot stronger than accommodation, where the individual lives in a dream world and sticks to their concept without being influenced by the environmental realities.

On the basis of this, Kolb developed his learning cycle. According to Kolb, there are four different skills an effective learner needs to master, all pretty much similar to the earlier theories described above:

  1. Concrete experience: learners must be able to enter into new situations openly and without bias in order to experience them fully.
  2. Reflective observations: the learners must be able to reflect on their new experiences from different perspectives.
  3. Abstract conceptualization: from the observations, the learner must be able to form logically sound concepts and theories.
  4. Active experimentation: the learner must be able to use those theories to make decisions and to solve problems.

Learning thus requires abilities that are polar opposites of each other: A learner must act and reflect on a given topic, as well as bring together concrete experience and theoretical reflections.

This is shown in the orthogonal axes in the classical picture of Kolb’s learning cycle:

Kolb_learning_cycle

My interpretation of Kolb’s learning cycle (1984)

Contrary to my first interpretation of that image, the axes don’t span up the polar opposites of different learner types, but each endpoint is a necessary part of the learning process. For successful learning, we need to create situations in which all four of those processes can occur.

This is especially relevant for me (and readers of this blog) who like to include hands-on activities in their teaching. While I think hands-on activities are great, I implicitly understand them to include more than just the hands-on parts – namely reflection, conceptualization and transfer (which happen to be the other steps in Kolb’s learning cycle!). But in my opinion, this needs to be made explicit more, for two reasons: Firstly, so that both instructors and students are aware that those are necessary steps in the learning process. And secondly, so that the old “oh, so you are just playing – in my classes students learn the hard way!” can stop. Using hands-on activities is activating an additional channel (and we’ve talked about the importance of peer discussion before and after running experiments), but by no means is that the only channel we should be using, or are using right now.

Development of student attention over time

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Do we really know how student attention develops over time?

One thing that is shown over and over again in teachers’ trainings is the curve of how student attention peaks 10-15 minutes into the lecture, then declines sharply, and then starts picking up again at about 40 minutes (so 5 minutes before the end of a typical lecture).

aufmerksamkeitskurve

The curve shown traditionally in teachers’ trainings

I come across this curve all the time, and I’ve always been curious how one would be able to measure student attention, and whether those measurements would really be valid. So I finally got around to doing a literature search on the empirical basis of this curve and found a literature review by Wilson and Korn (2007). They were also getting curious about the origin of this curve, and looked into empirical studies on the topic.

What they found is interesting, though not surprising: the literature does not support the “attention drops after 10 to 15 minutes” claim that is often made. However, it is also clear that student attention does vary throughout a lecture, but there are more important variables than just a time dependency. Which is encouraging – if student attention does depend on more than just time into the lecture, there are ways to influence it, too. The authors call for more research and an empirically based estimate if people want to continue using the student attention curve to encourage teachers to develop ways to keep students interested in their lectures. They conclude that “Beyond that, teachers must do as much as possible to increase students’ motivation to “pay attention” as well as try to understand what students are really thinking about during class.”

What could teachers do to increase students’ motivation to pay attention during class? The main thing seems to be to change activities regularly. For example introduce clicker questions or show demonstrations (but then don’t forget the peer instruction phases before and after the demonstration to increase learning!). Or have students work in groups for a bit, or even just switch from a Powerpoint presentation to explaining something on a blackboard. Or include some quick physical activity. If you are getting bored by your own classes, chances are students have been asleep for hours and you just haven’t noticed.

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Wilson, K., & Korn, J. (2007). Attention During Lectures: Beyond Ten Minutes Teaching of Psychology, 34 (2), 85-89 DOI: 10.1080/00986280701291291

Why talking to your neighbor might help more than listening to the lecturer

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Why does learning through peer instruction work?

As you might have noticed by now, I’m a big fan of concept questions combined with “talk to your neighbor” peer instruction. And studies show that talking to your neighbor is often more successful in teaching you new things than listening to the lecturer is.

In their paper “Why peer discussion improves student performance on in-class concept questions“, Smith et al., Science (2009), try to separate two possible reasons for the success of peer instruction: Does learning gain through PI result from gains in understanding during discussion, or simply from peer influence of knowledgeable students on their neighbors?

In order to separate those effects, the authors first ask a multiple choice question, let the students vote, use peer instruction, and let students vote again. They then ask a very similar question, which students who didn’t vote correctly the first time for the first question likely wouldn’t be able to answer correctly, either. So if those students answer correctly now, that supports the idea that they gained understanding during discussion rather than being just influenced by the knowledgeable students in the previous case. And their data shows that the third vote consistently gives better results than the first vote, and, surprisingly, often even better results than the second vote after peer instruction.

The power of increasing understanding through conversations with the neighbor is also supported by 47% of students disagreeing with the statement “When I discuss clicker questions with my neighbors, having someone on the group who knows the correct answer is necessary in order to make the discussion productive”. Discussing concepts seems to be the key, not being convinced by someone more knowledgeable.

Learning with fluid toys

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How fluid toys can be used to demonstrate principles of fluid mechanics.

I guess every attempt to hide that I LOOOOVE fluid toys of any kind is futile. So imagine my excitement when my colleague sent me an article titled “Serious Fun: Using Toys to Demonstrate Fluid Mechanics Principles” by Saviz and Shakerin (2014). While their ideas are not really applicable to the kind of courses I usually teach, it is refreshing to see them embrace fluid toys in teaching, and it made me realize that I didn’t post movies that I made of toys that my sister gave me and my dad for our Birthdays back in May.

If you fancy seeing this thing in motion, go watch the videos below!

Making science topics relevant to students’ lives increases interest and performance

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Duh!

That students are more interested, and hence perform better, when they are motivated to learn something sounds not terribly surprising. But did you know that you can actually increase motivation by making the students write about the relevance of the topics you are teaching?

In the study “Promoting Interest and Performance in High School Science Classes” by Hulleman and Harackiewic (2009), 262 high school students taught by seven science teachers were randomly assigned one of the following tasks, to be conducted periodically throughout the semester: either to summarize the content of the lessons, or to write about the usefulness of the course material in their own lives.

At the end of the school year, the authors of this study found that the grades of students writing about the relevance of the material to their own lives were on average a full grade point higher than those of the students only summarizing the material. This effect was especially large for students with low expectations of performing well in class.

Yes, this was only one study on a limited number of high school students and those results are not directly transferable on every other course. But they seem significant enough to warrant considerations in the way we plan our courses. Writing more always seems to be a good idea (at least in the field I teach in). But if tweaking the writing assignment just this tiny little bit can have such an effect on learning outcomes, why not just tweak it and make students think about the relevance of course content in their lives?

Will getting it wrong help or hinder future learning?

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A study shows that unsuccessful retrieval attempts enhance subsequent learning.

I’ve talked about how testing drives learning a while back, and today’s post is on a similar topic. If testing drives learning, what happens when you don’t know the right answer on a test – will it help or hinder future learning?

In the paper “Unsuccessful retrieval attempts enhance subsequent learning” by Kornell, Hays and Bjork, students are tested on material where they can’t possibly succeed at the first attempt, for example by asking fictional general-knowledge questions (like what peace treaty ended a fictional war) or questions where a correct answer, based on a weak association, is unlikely (and correct answers were excluded from the analyses).

Two cases are compared: the test condition, where participants try to answer the questions and are only shown the answers afterwards, and the read-only condition, where the participants are shown questions and answers at the same time. In both cases, unsuccessful retrieval attempts enhanced learning.

The authors conclude that “These results demonstrate that retrieval attempts enhance future learning; they also suggest that taking challenging tests—instead of avoiding errors—may be one key to effective learning.” They comment on the practical implications of this research and recommend that both educators and learners should introduce challenging tests as learning events, even though initially the likelihood of the wrong answer being given is quite hight. Under the crucial condition that feedback is being given, this will help learning in the long run.

There are practical implications of this for my work, too. For example results of this study should help dissipate fears that pre-tests (which we would like to pose in order to determine the learning gain throughout a course), where students likely will not likely know most of the answers, will make students remember the wrong answers they gave. Or, similarly, that clicker questions will cement the wrong answers in the students’ memories. Or even that asking questions during a lecture without immediately providing the correct solution will have negative effects on student learning. Quite the contrary, the study shows: “the attempt to retrieve the answer may enhance the activation of these related concepts, which may, in turn, create a fertile context for encoding the answer when it is presented.”