Wednesday 1 July 2020

Applying cognitive load theory to Computer Science - Simon James

The focus for my research is around Cognitive Load Theory and how using Chromebooks and Google Applications can promote longer term memory and recall by considering the cognitive load on learners. 

Literature Review - Cognitive Load Theory
Cognitive Load Theory is based upon an understanding of how information is held in working memory and then processed into the long term memory. There are three types known as intrinsic load, which concerns the difficulty of the task; extraneous load, which is unnecessary thinking required by students, and germane load, which is load required by the teaching task to support the learning.

Why Bar-Model Works #2: Reducing Cognitive Load – Reading for Learning

Research into cognitive load suggests a number of different strategies particularly with the use of teacher presentations. Tharby (2019) suggests that “labels are integrated into diagrams and ensure that information is presented in close physical proximity to related information”. He further mentions the importance of “images to support complex and conceptual idea”, which can help reduce germane load. Tharby (2019) explores a range of different strategies to support effective classroom pedagogy:
  • Ensure that labels are integrated into diagrams and ensure that the information is presented in close physical proximity to related information.
  • Avoid reading out text that is already on the slide
  • Remove distractions or superfluous images
  • Use images to support complex and conceptual ideas
  • If you intend to explain an image, it is best not to include written text at the same time.
  • Never expect students to read something from the board while you are talking
  • Reveal processes stage by stage on the same slide.

Diagrams — OliCav
Oliver Caviglioli is a leading figure in applying cognitive load theory to diagrams and presentations (a link to a webinar is included below).

In our Computer Science department we have identified that students struggle with the cognitive load placed upon them due to the quantity of new knowledge that they need to process to be successful at the new GCSE specification. This load often causes students to become stressed, demotivated or both. A solution to this that will form part of my practitioner study is to introduce some of the knowledge required in the GCSE specification at an earlier level to help scaffold the knowledge, reducing load at a later stage. In lessons we should also be able to apply some of the techniques advised by Andy Tharby to support learning. Finally through the use of Chromebooks and the G-suite of educational tools such as Google Classroom we should be able to further reduce the cognitive load on students by building knowledge through routine low stakes assessment and supporting homework tasks.

Intervention
I aim to use my year 8 computer science class (82/Cs) they are a group of mostly high achieving pupils who have already had a number of difficult topics at GCSE computer science introduced in a way which reduces unnecessary difficulties and promotes long-term knowledge retention. Their long-term memory will be tested at regular intervals to check if cognitive load strategies help with completing these tasks.

The intervention will involve using pre-prepared examples, with models, flowcharts and other relevant images to support text (following the guidance of Andy Tharby). There will also be permanent access to task instructions and success criteria available on Google Classroom for the pupils to access. The resources will cover a whole half-term of learning which will deliver new content pupils haven’t been exposed to before on algorithms. The learning will also be supported by Google Form assessments that will be completed using Chromebooks.

Using the Cognitive Load and technology strategies suggested I am hoping to see an improvement in knowledge retention as the reduced cognitive load will ensure greater transfer of knowledge into the long term memory. This will be measured through the end of year exams and compared to other groups in year 8 who are not receiving the intervention.

Implementation
The topic for the term was ‘algorithms’ so I wanted to focus on reducing the intrinsic load of the knowledge, by including useful labels and diagrams to support the learning. This strategy along with using the formatting of bold and underline to help reinforce key pieces of information with pupils. After modelling the knowledge the students would complete a range of interactive tasks including defining, creating and reading a variety of flowcharts applying the knowledge learnt from my explanations.

After completing these activities, I explained to the pupils that their homework and classwork would be focussed around specific knowledge and skills this based upon the lesson content (rather than completing a project log for homework where they reflect on their learning journey). I explained that we would be focussing on exploring algorithms in great depth and how we would use Google Forms for assessment with the aim of promoting mastery. 


Impact
The pupils managed to show good improvement from the initial control group, which showed that they managed to grasp difficult topics which typically are taught in Year 9. They made strong progress during the 6 week half-term. They were taught an introduction to computational thinking; exploring the 4 main techniques of computational thinking (as seen above). The presentation and use of supporting images pictured above helped articulate each of the key words and then the exploration activities the pupils undertook in the worksheet allowed them to explore and build a strong cognitive understanding of the topic. Other groups learning about algorithms in the same term struggled possibly due to less attention on key subject terminology and more focus on practical task based tasked which overloaded them cognitively. 

The pupils typically are asked to complete a project log each week for homework, and after completing a questionnaire the results showed that 84% said they enjoyed completing the Google Forms assessments on their chromebooks and 63% said it helped them to remember the learning which happened in the lesson. In the following term I interviewed a small group of pupils to ask if they enjoyed the topic and the way the knowledge was presented this term. One pupil said “learning the algorithm theory then applying it to flowgorithm was great”. One pupil stated that “I now understand how processes work by using flowcharts”. I had a few suggestions and one pupil stated that “too much information in the first lesson - I couldn’t remember some of the points”. So I need to restructure the learning in this lesson to ensure that it isn’t overwhelming and presented appropriately.

Further research
It’s important to consider the ability of the learners in the control group and considering they are a high ability group the same strategies may not work with lower ability pupils. There are very few research articles around effective cognitive load strategies using technology so it’s always important to consider how technology is helping learning and avoid distraction from learning as much as possible.

The strategies used with this control group could be used as a wider study with other year groups assessing their understanding of algorithms and with older year groups checking understanding of that topic. How information is presented is essential and whilst textbooks are largely no longer used in education it’s important that pupils see the bigger picture of all concepts learnt in computer science for long-term memory retention.

Recommendations
  • Focus on key knowledge when introducing new learning, and don’t overcomplicate. The information shouldn’t be overwhelming and the use of images and diagrams will help to structure the information in a way that is accessible for all pupils to make strong progress.
  • Try to avoid distracting images on teacher presentations which will hinder learning for the pupil - and ensure that you assess understanding of new knowledge through effective assessment.
  • Allow enough lesson time for pupils to practically explore new knowledge and encourage effective discussions in the classroom around the new learning.
Further Reading

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