Journal: What makes learning meaningful?
Entry 1: Describe your own meaningful learning experience
Your first entry should describe a meaningful learning experience that you have personally had in the past. You should describe one positive experience in detail.
You should provide as much detail as you possibly can, e.g. What age were you? What was the topic that you were learning? How did you learn it (or how was it taught to you)? The more detail you can provide at this stage, the easier it will be to analyse the experience in later stages.
Once you have described the learning experience, describe why it was meaningful to you. What makes you remember it still? What stood out for you? How was it different to other learning experiences? What were the factors that made it positive?
Entry 2: Assumptions about learning
Your second entry is a simple one: given whatever you have described in the first entry, what assumptions have been made (implicitly or explicitly) about how people learn?
For example, in a situation where people are asked to go over the same materials, or repeat the same actions, the assumption might be that people learn best through repeated practice. Here is an example: “My biology teacher made people do additional work in order to earn top marks in his class, the underlying assumption would be that people learn best when they are given an appropriate level of challenge.”
Again, try to think of as many of these “assumptions” as you can: remember that they can be, and often are, implicit. There are no right or wrong answers, and the more you put down now, the easier it will be to try and link these to learning theories later.
Entry 3: Theories of learning
Your third entry should focus on theories of learning (behaviourism, cognitivism, constructivism, or any other theories that you research independently).
Start by looking over what you have written in your first two entries, picking out the salient features of your learning experience. Then, reflecting on the theories of learning we have covered in class (or any others that you have encountered in your own independent research), how can you characterise your learning experience in terms of learning theories?
Is it predominantly behaviourist? Cognitivist? Constructivist? Something else? Or is it a combination of more than one learning theory?
When you write up your account of how various learning theories were manifested in your particular learning experience, you should justify your reasons for choosing a particular theory (or theories). Secondly, you should look at the specifics of your learning experience, describing how particular features of the experience map onto specific tenets of the learning theory in question.
For example, in the situation described above, a biology teacher made people do additional work in order to earn top marks in his class, I think that most of the teaching in the class was primarily behaviourist (learn facts, and reproduce the information on tests). However, the extra work had more of a constructivist element: it was learner led, and it was authentic (in the sense that learning to
conduct independent research and write it up is a key component of the work of a scientist, whereas taking tests is not). One could analyse several other features of the learning experience, including what it was not (e.g. collaborative), but this is just to give you an idea.
Entry 4: Theories of motivation
Your fourth entry should focus on theories of motivation, for example, the Lepper and Malone model, the ARCS model developed by Keller and Suzuki, intrinsic and extrinsic motivation as covered in Deci and Ryan’s Self Determination Theory, or any other theories of motivation that you have researched.
Let’s make the assumption that if the learning experience was positive, then it was motivating in some way (although feel free to say if this is not the case!). Looking at the experience as a whole, describe what made it motivating? How does this fit with theories of motivation?
Now, looking at the features of the learning experience that you picked out in your third entry, what particular features made it motivating? Again, how do these features relate to particular theories of motivation?
Here is an example: “I think the motivational aspect came down to the level of challenge. I did not find school very challenging and was used to coasting along. Suddenly the level of challenge was raised substantially, which initially came as a shock to me. At the start, the motivation was primarily extrinsic, as I was determined to continue to receive the highest marks in all of my courses. However, as I worked on the project, the motivation became more intrinsic: I enjoyed doing something out of the ordinary, learning how to do research, and feeling somehow that I was doing something that “proper” grownups did.”
Entry 5: From real to digital
Your fifth, and final entry is about the move from “real” to digital. Your learning experience is likely to have taken place in a face-to-face environment, but don’t worry if that’s not the case. The key here is to think about those features of the experience that made it meaningful: what were they, and how could you recreate them when designing a technology-enhanced learning experience? This is a very important step in the design process: when designing technology for learning, many of us simply copy what we’re used to. However, much of the technology-enhanced learning that is out there isn’t particularly inspiring, motivating, or well designed. It’s not always clear that the designers have thought long and hard about how to best engage and motivate their learners. So, it’s up to you to break the cycle!
You should approach this question on two levels: 1. How generally could you recreate the features that made your experience meaningful in a technology-enhanced learning environment and 2. with respect to the learning environment prototype that you have developed for the module, have you managed to incorporate some of these features and, if so, how?
Again, going back to the example presented above, there are two things that you could try and bring to the design of a digital learning experience: motivation (appropriate level of challenge) and authenticity. In the first case, very few digital learning experiences are tailored to the individual, and few systems can recognise when someone is simply coasting along. Artificial intelligence offers one way of looking at how to individualise learning, but it may be that something less complex might be effective: e.g. the method for determining that further challenge was appropriate could be quite crude. On the other hand, designing a system that can effectively evaluate open-ended inputs, such as a lengthy project report, is more challenging. This relates to the second issue, that of authenticity. The task that was given in the example story, could feel very much like what “proper” scientists do: it involved doing research, and synthesising findings, as opposed to simply answering what were, for the most part, multiple choice questions on a test. When designing for learning, it is important to be aware of the distinction between “learning about” vs. “learning to do/learning to be” and try to design in the latter category as much as possible.