'How memory works and why it often does not: Systems through which we process knowledge'

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By Dennis Sale

Many students, and this is not unique to such folk, claim to have poor memory. However, when I test them by presenting 16 familiar words (and then ask for immediate recall), I find that most can accurately recall around 7±2 of the words presented. This was originally documented by Miller (1956) and was established as an evidence-based measurement for the capacity of short-term memory; now re-framed as working memory (WM). More recent research (eg, Van Merrienboer & Sweller, 2005) suggests that in everyday situational use, WM tends to be only able to retrieve two to four elements at a time.

By way of analogy, human memory is akin to having a Maserati sports car, but being able to use only the first gear, except in special circumstances (as explained later). A Maserati will hit a top speed of 185 miles per hour, but certainly not in first gear. Our memory has two main systems, long-term memory (LTM) and WM, as identified above. LTM seems to have unlimited storage capability. It’s not that our brain gets bigger as we learn more; rather it becomes denser in terms of neural connectedness, though we can never live long enough to test its full capability.

However, before information can be effectively processed and stored in LTM, it must first pass-through WM which, apart from limited capacity, requires quick rehearsal – otherwise it is typically lost (forgotten) after only a few seconds.

It has been popular in many educational circles to downplay the importance of memorisation in the learning process. After all, we want flexible, adaptive, and creative thinkers today – right? Yes, but such high-level human capability is largely based on what we have already acquired in our LTM system. Quite simply, if there is not much information there, and it’s not particularly well organised and connected, there is little chance of creative or even useful outcomes.

What is crucial, therefore, is the effective and efficient transfer of new information through WM to connect meaningfully to what is already in LTM, thus enhancing our understanding of what is being learned. In basic terms it is how we think about the knowledge being processed that is crucial. As Paul (1993) summarised:

‘…thought is the key to knowledge. Knowledge is discovered by thinking, analysed by thinking, organised by thinking, transformed by thinking, assessed by thinking, and, most importantly, acquired by thinking.’

The effective transferring of information from WM to LTM involves:

  • Not overloading the capability of WM at any one learning interval.

  • Ensuring that what is being learned is meaningful.

  • Rehearsal and retrieval practice of what is being learned.

Rehearsal is the mental process of repeating and visualising new information in your mind. Retrieval practice is checking/testing that you have the information/understanding in your LTM. Brown’s (2014) summary is spot-on:

‘Practice at retrieving new knowledge or skill from memory is a potent tool for learning and durable retention.’

Furthermore, when you consciously retrieve information from LTM into WM, this enables checking that it’s still there and accurate (and if not, find it from source and go through the rehearsal process again). Most importantly, through the process of periodic retrieval practice, knowledge in LTM becomes increasingly cemented neurologically in the brain that underpin the mental representation (schemata) in the mind. Hence, the knowledge – especially understanding – in LTM is what’s really important for deep learning. As Kircher et al (2006) concluded:

‘…long-term memory is now viewed as the central dominant structure of human cognition. Everything we see, hear and think about is critically dependent on and influenced by our long-term memory.’

Research clearly shows that a major factor that differentiates experts from novices is that expert problem-solvers can draw on the vast knowledge bases in their LTM and quickly select the best approach and procedures for solving a given problem. As Kircher et al explained:

‘We are skilful in an area because our long-term memory contains huge amounts of information concerning that area. That information permits us to quickly recognise the characteristics of a situation and indicates to us, often unconsciously, what to do and how to do it.’                                  

For experts, when dealing with problems in their field, WM has no limitations when dealing with masses of information retrieved from LTM, as it dramatically alters the functionality of what is taking place within the memory systems. The two systems effectively merge into one fluent dynamic entity working towards meeting the conscious goal of desired information retrieval and solving the problem in hand. This in when your memory resembles the Maserati in fourth gear. As Hattie and Yates (2014) summarised:

‘When your knowledge becomes so automatic that you can access it quickly, with virtually no effort, then the WM system is said to be bypassed through the automaticity stage – a most desirable place to be.’

To illustrate, the elegance of this process, here’s a story I like:

An expert chemical engineer was called into a plant emergency where the on-site engineers could not identify why a reactor was not starting up, and where losses could run into many thousands of dollars a day if not rectified. The expert engineer walked around the plant, looked at different parts of the system, made certain adjustments to various parameters in the units, and within a couple of hours had the reactor working perfectly. Later she billed the company $20,000. The company, not challenging the cost, given the alternative scenario, did ask the consultant engineer for a breakdown of the bill. The reply went something like this, ‘$1,000 for the call-out, $19,000 for what’s in my head’. 

In summary, for teaching and learning practices, students need time to rehearse, process, and consolidate new information to existing mental schemata in LTM, which is facilitated through skilful questioning and application activities that generate appropriate types of thinking (eg, analysis, comparison and contrast, inference and interpretation, and evaluation). Expert teachers provide this structure, adjust the pace of instruction accordingly, and facilitate sufficient retrieval practice. Students and the teacher can then do a quality check on what has been learned, remediate lost elements, clarify overall understanding, as well as reinforce desired learning.

An additional snippet of information for you:

Talking to oneself, when memorising for an exam, if it is about the ‘right stuff’, is far from madness; it is a good learning strategy. 

  • Dennis Sale worked in the Singapore education system for 25 years as adviser, researcher, and examiner. He coached over 15,000 teaching professionals and provided 100+ consultancies in the Asian region. Dennis is author of the books Creative Teachers: Self-directed Learners (Springer 2020) and Creative Teaching: An Evidence-Based Approach (Springer, 2015). To contact Dennis, visit dennissale.com.

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