Making Learning Memorable

How to Design Better Courses and Improve Learner Retention by Understanding Memory Systems

By Jacques Fourie

Memory is a fundamental aspect of all learning since it stores and retrieves learned information. Conversely, learning also depends on memory because stored knowledge in your memory provides the framework to link new knowledge. Subsequently, high-quality learning experiences should be memorable. In this blog post, we will unpack what memory is, how it works, and how to best align learning design frameworks to the cognitive architecture of learners

Memory and Formal Education

Our memory systems play a vital part in all learning processes, and our stored and recalled memories are indicators that learning has taken place. In formal education, such memories will include:

  • factual learning of items of substantive and disciplinary knowledge;
  • skill learning, that is, processes of how to do something; and
  • understanding, the formation of concepts, and how meaning is assembled and extracted from knowledge.

What is Memorable Learning Design?

Memorable learning design is a highly effective, evidence-based approach that informs the design and organization of learning experiences. The approach is grounded in the relationship between learning and memory, and it is supported predominantly by empirical research conducted by cognitive psychologists.

In cognitive psychology, experts have agreed on principles that explain the relationship between memory and learning. Memorable learning design acknowledges these principles and approaches and uses them to inform the design of learning experiences.

To create memorable learning experiences, we need to consider the cognitive architecture of learners, i.e., mental structures and processes, and evidence-based practices to ensure that encoding and retrieval happen optimally. So, let’s examine how memories are formed through exploring an influential model utilized in cognitive psychology.

Human Cognitive Architecture: The (Non-Linear) Multi-Store Model

The (Non-Linear) Multi-Store Model, emerged from research in cognitive psychology, and it describes memory as consisting of three interconnected components. Namely, sensory memory, working memory, and long term memory.

1. Sensory memory refers to the part of the system that transforms incoming stimuli into information. It has a large capacity, but a very short duration (less than three seconds). The ability to glance at something and remember what it looked like is an example of sensory memory.

2. Working memory is what you are currently thinking about, it is where you hold new information, and it is where you integrate new information with your knowledge from long-term memory. It has a limited capacity (about seven chunks of information). Working memory has three distinctive features:

  • A phonological loop – for storing auditory information.
  • A visuospatial sketchpad – for storing visual information.
  • An episodic buffer – to integrate information from the phonological loop and visuospatial sketchpad with knowledge that exists in our long term memory.The phonological loop and visuospatial sketchpad do not compete for resources and the visuospatial sketchpad has a larger capacity than the phonological loop. This means that visual information is more memorable than auditory information, and importantly, we can enhance the capacity of the working memory of students if we include both visual and auditory information since they do not compete for resources. Lastly, the episodic buffer indicates that new information is more memorable if the learner has prior knowledge about a topic.

How information flows and creates long term memory.
3. Long term memory is a permanent store of knowledge and potentially, it has an unlimited capacity. There are two main types of long term memory —  Implicit and Explicit Memory:

  • Implicit memory does not require conscious recall. Procedural and priming memory are examples of implicit memory.
  • Explicit memory does require conscious recall. Semantic and episodic memory are examples of explicit memory.

In education, we predominantly develop a learner´s explicit memory, which is weaker than our implicit memory.

All three components—sensory memory, working memory, and long term memory—interact with each other and long term memory plays an important role in influencing what we allocate attention to, what information we process, and what we remember. Let us explore some evidence-based educational principles that emerged from the multi-store model.

An Overview of Evidence-Based Principles and Practices

There are four general memory principles that we can use to guide our learning design practices. These principles and practices are explained below.

1. Sensory memory: unattended information is lost.
    Best Practices:

    • Learning designers should use a spiral design i.e., material should be revisited and built upon over time, to ensure that relevant information is recycled. The more prior knowledge we bring to learning, the easier it is to maintain attention, and store information. Subsequently, to get learners to attend to target information, they require a preliminary understanding of a topic and a spiral design is a great approach to ensure that prior knowledge is actively recycled and developed.
    • Instructional graphics are also efficacious in drawing a learner’s attention to the most important information.
    Ask Yourself:

    • In my deliverable do I build concepts?
    • Are concepts revisited throughout the deliverable (information, practice, assessment)?
    • Did I use instructional graphics to emphasize and explain key concepts?
2. Working memory has a limited capacity and if exceeded you cannot learn new things.
    Best Practices:

    • Apply John Sweller’s cognitive load theory to minimize extraneous load and maximize germane load in your deliverable. Sweller essentially suggested that we should design instruction to minimize unnecessary working memory load by removing extraneous instructional material, and, ultimately, develop instruction to support learners to acquire germane knowledge through deep processing.
    • Organize information effectively to maximize the effectiveness of working memory. Instructional graphics and videos can help learners to organize and integrate information in ways that are meaningful. Also, visual and auditory components do not compete for space in working memory. Therefore, instructional graphics and videos can maximize the effectiveness of working memory.
    • Add instructional material that prompts the learner to reflect on relevant prior knowledge. Through doing this, learners can chunk information, allowing working memory to work more efficiently.
    Ask Yourself:

    • In my deliverable did I organize information effectively?
    • Did I reduce extraneous information?
    • Did I chunk information in small, digestible units?
    • Did I use instructional graphics to organize information effectively?
    • Did I use technological components, graphics, and videos to synchronize information?
    • Did I include reflection questions in my deliverable that activate prior knowledge?
    • Did I include instructional material that draws links between what the students have learned and new information?
3. Explicit long term memory is supported through effortful processing and making information meaningful.
    Best Practices:

    • Include activities that prompt learners to make content meaningful by elaboration. Learners should add and extend meaning by connecting new information to existing knowledge. Instruction should prompt learners to make connections between an idea in working memory and an idea in long-term memory. Material that is elaborated when first learned is easier to remember.
    • Use mnemonic cues in your deliverable to help learners make connections with previous knowledge. An icon can be used as a mnemonic cue. For example, a relevant icon can be used to indicate a chunk of information, and the same icon can be used when adding and extending meaning to a preceding chunk of information.
    • Include activities that prompt learners to make content meaningful by explanation. Explaining information is a constructive process that helps learners make their ideas explicit, enabling them to overcome gaps in material or generate new inferences. It involves making connections between what they are learning and earlier material or prior knowledge. This could include reflections, discussions, and assignments where learners have to analyze information or even the creation of graphics to explain a concept.
    Ask Yourself:

    • Did I provide opportunities within my deliverable for learners to actively elaborate on what they have learned?
    • Did I include mnemonic cues within my deliverable to ensure that learners can retrieve information effectively and further, elaborate on previous learnings?
    • Did I provide learners with the opportunity to explain information?
    • Did I include ‘why’ questions in my deliverable?
4. Forgetting can be Minimized
    Best Practices:

    • Retrieval practices can be used to minimize forgetting. A retrieval practice might take the form of a quiz or an essay question. It can be added at the end of a section in a course. Trying to remember something improves learning and, often, it is more effective than rereading information.
    • Designing instruction to enable accommodation can decrease forgetting. Interference from competing memories inhibits transfer to long term memory. As a learning designer, you should identify where in a course interference is likely to occur and subsequently, design instruction, by including scaffolding or metacognitive activities, to improve accommodation.
    Ask Yourself:

    • Did I include retrieval practices strategically across my course?
    • Did I help learners to encode information that might disrupt previously developed ideas and meaning systems?

Through applying these evidence-based practices in your course design, learners will develop rich and differentiated schemas. This will improve their ability to store new and more complex information, and ultimately, help learners to solve real-world problems with a higher degree of automaticity.

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Jacques Fourie

Jacques Fourie
Learning Designer

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