The relationship between learning and the limitations of our working memory

I’ve been reading more and more recently about the connection between adult learning theory, cognitive science, and the underling physiology of learning – this is a critical body of literature for those planning and creating education. And while the complexity of this field of study is seemingly limitless, one of the simplest, most practical, and perhaps most valuable ways of understanding the relationship is to consider the critical role played by our memory system, or systems as it were.

If we accept that the ultimate goal of our educational programs is to increase knowledge (sustained knowledge) such that it may be called upon to support behavior change and improve performance; then what we are really saying is that we want to ensure that the information we are providing within our educational programs is effectively integrated into a learner’s memory systems. This might be one of those blinding-flashes-of-the-obvious moments – learning is fundamentally dependent on our memory systems.

So what do we (the CE community) need to learn ourselves to better understand how the memory systems affect learning – well this was beautifully explored in the 2014 work by Young et al “AMEE Guide no 86 – Cognitive Load Theory – Implications for medical education” and I would highly recommend that you download the article and share with your team!

Here is a sneak peak at the critical lessons for educators to learn and apply:

1. The intersection of learning and memory is well described by the Cognitive Load Theory (CLT) which builds upon an established model of human memory that includes the subsystems of sensory, working and long-term memory.
2. Working memory (WM) can only process seven elements of information at any given time. This constraint creates a ‘‘bottleneck’’ for learning and limits the speed at which information is processed to long-term memory (LTM).
3. There are three forms of ‘load’ that impact WM: intrinsic (complexity of content to learners), extraneous (environmental distractions or learning action barriers) and germane (effort invested in cognitive strategies of learning, i.e. schemata construction).
4. When the 3 forms of cognitive load associated with a learning experience exceeds the learner’s WM capacity, performance and learning is impaired.
5. To facilitate learning, educators MUST work to minimize extraneous load (Learning Actions Model), titrate intrinsic load to the developmental stage of the learner (e.g. simplify content without de-contextualizing) and allow learners to reserve cognitive capacity for the germane load (automation and schema formation).

It might help to read through these practice pearls once more, but the takeaway is that there are REAL, SCIENTIFICALLY VALID, CRITICAL limitations to learning that we, as educators, MUST accept and design our educational interventions to overcome. This is why large multi-day congresses, 3-hour symposia, passive eLearning (i.e., hour long, play-and-stay video lectures), and unstructured educational experiences are largely ineffective for learning – you cannot force more information into the heads of learners whose working memory has reached capacity because they are uninterested, unengaged, and incapable of processing more information. The limitations of our biology prohibit it!

As my research into this subject has grown over the past years, I have come to see these limitations as both necessitating and validating our Learning Actions Model. In as much as learning experiences can be better structured and motivation and awareness can be continually nudged, the extraneous load associated with learning can be minimized and learners may be better equipped to actually learn.

By addressing the parts of the learning experience that we more readily control, educators may facilitate learning the following ways.

• Through better instructional design, information may be presented more logically
• By structuring information more logically, connections may be drawn more rapidly
• By presenting content in more accessible ways, learner engagement is maintained, and
• By engineering better structured learning environments the burdens of cognitive load and the limitations of memory systems can be overcome