This video will cover:
00:22 The science behind cognitive load and the loss of attention
01:03 How ‘chunking’ can help control cognitive load
02:00 Why interspersing ‘chunks’ of teaching with information retrieval activities is so effective
Bjork’s analogy highlighting the effect of monotony could easily be applied to a 50-minute lecture dominated by uninterrupted content delivery.
Such monotony often leads to mind wandering. Now we know this isn't always the case; motivation plays an important role.
But what we definitely know is that maintaining attention is crucial to learning and therefore we should mitigate against its loss.
So, let’s look at the science behind the loss of attention. It’s very much affected by cognitive load.
A specific observation of cognitive load theory is the primacy recency effect, where learners remember the initial content in a list and the last, but not the middle. And this is due to our working memory having a limited capacity.
So, if we think that working memory can process four items quite comfortably, as the lecture progresses the working memory is brought to capacity.
Once greater than four items are asked to be processed, the working memory begins to struggle and is eventually overloaded. This has big implications for what’s being taught at this section of the lecture.
Final comments made may be retained as this is due to a change in attention.
Sousa pictorially presents this phenomenon, illustrating that as time goes on the amount of downtime increases exponentially. They propose the downtime is utilised as a practice opportunity, or consolidation period.
They also advocate that if the lecture is chunked, then the loss to downtime can be reduced. So why does this happen? Well, a possible consideration is that chunking controls cognitive load. Let’s illustrate this further.
Consider this fairly extreme example of how easily working memory can be overloaded. Trying to process these letters becomes increasingly hard the more letters that are presented.
But if we chunk the content, it becomes easier because now we see each letter as a combination – as one item. If we try to connect the content to what we already know, we free working memory space again as the number of items to process seems to be reduced.
So, breaking content up into chunks assists working memory. And making connections to schema relieves working memory further. Both of these will assist attention span.
Another interesting finding that supports this notion of chunking is the effect of test-potentiated new learning, which is effectively a form of chunking content spaced with the form of retrieval activity.
So, if we deliberately chunk content delivery and then place student-led active learning segments into the frame, we’re able to manage cognitive load, building during each delivery section, then worked on, to try to transfer it to the long-term memory.
But crucially, refreshing the working memory when the next new learning segment is presented. Let’s think about how this translates into the activities in a lecture.
We begin with a retrieval quiz, strengthening memory by transferring content from previous lectures into the long term memory, which facilitates these memories being automatically brought into cognition when new learning is presented.
The other bonus is immediate student interaction. This can be done old school with just questions on the Powerpoint screen or in the recorded lecture, set up before the video is played.
This needs strong logical design to ensure that the student embarks on the journey, and isn’t distracted on that journey to its completion. The first content delivery section should be about 10 to 15 minutes in length, building schema and modelling and introducing analogies. But also following multimedia principles to direct students’ attention to specific content, like I’m doing in this video.
The technology that can assist may be Powerpoint slides, you may be using a document camera for modelling, and then a recorded lecture, you’re definitely building the content piece by piece.
The next segment of the lecture is student-active, where students are practising, processing or discussing the content just taught.
They may be working in pairs to consolidate the understanding, or they may be using a Padlet or Trello board, where they can see other people’s answers and thoughts, providing opportunity for assimilation, accommodation or even cognitive dissonance with the content.
The next section is content delivery, the same as we’ve discussed.
And the following segment is formative assessment, again student-led, very much based on what has been taught in this session, as Finn and Davis propose.
In terms of a recorded lecture, interactive questions using H5P is an effective strategy to ensure that students are engaging with the questions actively, having to press play to resume the video after answering questions.
The teacher then delivers more content and, finally, the teacher and student work together to summarise and evaluate what has been taught, especially seeking connections to previous learning, facilitating the scaffolding of schema.
In the live lecture you may be having an introduction to a question posed on the LMS [learning management system] discussion board, encouraging that students now move into the asynchronous element of the course to deepen the processing and understanding of the content, and to prepare them for the next session.
It is when the lecture is chunked in this fashion that eagle-eyed attention is more likely, and also better learning outcomes.
This video was produced by Paul Moss, learning design and capability manager for learning enhancement and innovation at the University of Adelaide.