Continuing to #WorkOutLoud to share parts of our writing for the Learning Science book. In that work, our ‘landscape of Learning Science’ has five major areas. Part 1 covered how people learn. Part 2 examines the states, characteristics, and contexts that influence learning.
By being responsive to individual, social, and contextual factors we have the opportunity to create more inclusive, engaging, and effective learning experiences, and in this section, we’ll consider some of these factors.
Factors that affect or moderate learning
No matter how well a learning experience is crafted and delivered, there are many external factors that affect whether it works for those learners, at that particular moment in time, and whether the experience will deliver its intended value.
One way to picture the range of factors that influence the learning process is to start with the individual: Consider all of the individual differences that might moderate whether and how someone learns, and then gradually open that lens wider to consider the learning context, the people and things around us that impact learning. And then wider still: the broader factors that influence our context, including the social environment, organisational dynamics, and even global conditions.
Let’s look at some examples.
[1] Individual Abilities
Our ‘abilities’ are rooted in our psychological and physiological makeup, and they include things like our eyesight and cognitive functioning.
To consider these, it’s helpful to envision the Information Processing Theory (which we discussed in Part 1): We first sense, attend to, and perceive (make sense of) information; we store the information in memory, and might later retrieve and use it.
Each of those processes can be affected by differences in our abilities. Most obviously, someone’s ability to see or hear will impact their capacity to view or listen to something. There are also more subtle differences, such as in ‘Nervous System Sensitivity’, brain injuries, congenital disabilities, age-related differences, and neurodiversity.
Beyond cognitive functionality, some physical differences can impact learning activities; for example, someone with diminished fine-motor control might struggle to use certain learning technologies.
Increasingly, L&D practitioners are working to better design learning experiences for everyone, using methodologies such as ‘Universal Design for Learning’ (a methodology for creating more inclusive learning experiences by designing flexibility into activities and materials, allowing learners to engage in various ways, representing instructional materials in different forms, and letting learners demonstrate their ability in diverse ways).
[2] Individual Capabilities
These are things such as our knowledge, skills, and prior experiences. Or to put it another way, our individual capabilities represent what we’ve picked up and developed on our unique journeys so far.
They’re products of our prior learning, both formal and experiential. They’re the things we’ve learnt to do, or the actions we’ve developed the capacity to perform, or the attitudes and experiences that have shaped our beliefs and character.
The first and most salient capability for learning is prior knowledge, skill, and experience relevant to the topic at hand. (If you’re studying French, then what vocabulary did you learn before, and how much experience with other languages or linguistic principles do you have?).
Building on this, our existing mental schemata (the mental models we’ve internally constructed to make sense of the world) substantially impact how we perceive and learn because we use those lenses to understand the world, to interpret new information, and to file new learning away into our long-term memories. Of course this can be a double edged sword, in that these mental models may also act as filters, occluding or preventing us seeing the world in new ways.
Schemata help us make connections between new information and existing knowledge, which can facilitate – or hinder – learning. If we have rich mental models, it’s easy to slot new learning into them, but if our mental frameworks are biassed, incomplete, or inaccurate, we may struggle to understand or integrate new information appropriately – leading to blindspots, misconceptions, or resistance to new ideas.
This is itself an interesting aspect of how we learn, and one that directly relates to how learning is a negotiated – not simply an additive – feature: we do not simply learn one thing ‘on top of’ another, but rather a new thing is ‘processed’ into the various structures and assemblages within which our capability is held. This means, in a very practical sense, that what we already know may occlude, deflect, pollute, or hinder, the new.
The development of our capability in this sense can potentially be seen as a sense of weaving into a tapestry: we have both underlying structure and threads woven around it. Learning changes both, but isn’t an unconstrained activity: we typically try to maintain a certain coherence in our understanding.
We like to be curious, and are willing to be uncertain, but typically not too much so. To lose our connection to our own certainty can be a risky business. So, we try to integrate new learning into our understanding and shape it to fit our existing sense of the world (our existing mental tapestries): gradually changing our understanding in the process. Or perhaps distorting the new knowledge to fit with our old understanding. Or, in some cases, perhaps ignoring the new knowledge, if it’s too disparate from what we already ‘know’ as our internal truth.
[3] Individual Traits
Our Individual traits are things such as our identity, personality, and other ‘noncognitive factors’ (which are socio-emotional and behavioural characteristics linked to the educational process but are outside of what we typically consider to be ‘thinking’ skills, for examples, persistence, teamwork, and conscientiousness).
Our traits are stable characteristics that influence how we act, think, and behave across different situations. Traits are relatively enduring; although it’s possible for them to evolve over time, albeit slowly.
Traits include personality factors (famously, the ‘Big Five,’ although in practice personality theory is more nuanced than that model implies), stable motivational factors such as ‘achievement motivation’, stable attentional factors such as ‘trait boredom’ (a proneness and lower threshold to feel bored), optimism (hopefulness and anticipation of positive outcomes), resilience (a capacity to negotiate and recover from stress or trauma), and locus of control (whether we internalise or externalise the causes of things that impact our lives).
Other noncognitive factors can also be considered here, including grit (courage and resolve), mindset (our established attitudes), learning orientation (someone’s attitude towards learning), self-efficacy (our belief in our ability to achieve certain goals), and self-regulation (ability to moderate ourselves without external intervention).
We’re also grouping some personal factors under this category, including some socially influenced concepts like identity, language, social groups, and culture – because they affect our self-concepts and mental schemata.
[4] Individual States
In contrast to ‘traits’ that are enduring and relatively stable over time, ‘states’ are transient – like a particular mood or feeling. States are conditions influenced by a specific situation or context. Given a particular situation, someone might be anxious or excited, hungry or tired, distracted or motivated.
Pretty much all traits have corresponding states. For example, someone’s ‘trait boredom’ describes their general tendency to feel bored, but their state of boredom describes how bored they’re feeling at the moment. Said another way, while traits are relatively enduring and difficult (or impossible) to change, states are highly malleable. Emotional states such as anxiety, curiosity, frustration, interest, enjoyment, confidence, boredom, and engagement as well as physical states such as fatigue, hunger, illness, and physical discomfort have all been shown to affect learning.
We all have traits, which you can imagine are like the land (stable and relatively unchanging), and states, which are like the weather (volatile and dynamic) swirling above the landscape.
[5] Interfaces
Learning is affected by the interfaces between a learner and the learning activity (whether that ‘activity’ is another person, like a teacher or peer, a book or video, a serious game or learning application, or any other learning experience). We’ll delve into the technologies used to facilitate learning in Part 4 of this series. For now, we’re just talking about the interface – the connection point that influences the context of learning. Interfaces might include technological User Interfaces (UIs), of course, as well as the availability and accessibility of the relevant technologies (e.g., internet access, ergonomic affordances).
Interfaces needn’t be computer-based, though. Audio and video (live or recorded), lectures, hands-on exercises, whiteboards, and textbooks all frequently serve as learning media, and each have interfaces that can facilitate or create barriers to accessing the learning. For example, a beautifully conceived mobile learning experience with a bad UI will hamper learning as might poor wi-fi in a classroom or a bad video-teleconference connection to your mentor. On the other hand, well-designed interfaces can encourage appropriate behaviours and strengthen engagement.
[6] Physical Context
The learning environment can also be considered an interface as well as a context for learning, because the physical space where learning takes place both moderates and encompasses the learning experience. Elements such as lighting, noise, layout, distractions, comfortability, and accessibility can influence individuals’ motivation, engagement, and ability to learn. The physical environment can also include affordances that ‘nudge’ our behaviour (that is, environmental features that encourage potential action based on their properties, like a door with a handle shaped to naturally prompt pulling).
An example of physical affordances in education are classrooms designed with movable small group tables (versus the traditional lecture-style seating) intended to encourage student-centred learning and collaboration. Similarly, work on ‘Active Learning Classrooms’, ‘Future Learning Spaces’, or the ‘21st Century Classroom’ fits here. Those efforts aim to integrate the latest concepts in space design with the digital tools that enhance learning, such as embedded digital whiteboards, RFID sensors, or holographic video displays.
[7] Social Context
A wide range of sociocultural factors influence learning. We’ve already covered some individual traits (above) that one could arguably categorise here, such as socioeconomic status, cultural background, and learned family values. Those characteristics not only affect how we see ourselves, but also how others see us and how we interpret new information. In other words, our sociocultural context combined with the societal and historical contexts around a learning experience all affect how we learn. Similarly, mentors and peers affect learning, through direct teaching and collaboration (which will be covered more in Part 3) as well as in more subtle ways, from offering social support and enabling vicarious learning (on the positive side) to encouraging social isolation and discrimination (on the negative side).
The people around us influence the social and psychological climate: indeed, under a framework of Social Learning we could go further and say that we learn within the arms of our communities. It’s our communities (and especially the subset of trust bonded tribal structures) which create (or inhibit) the space for divergence and discussion. Essentially our learning communities can facilitate or inhibit learning; they can establish criteria for membership and belonging, encourage or penalise risks and exploration, and help scaffold or create gaps to knowledge acquisition.
We generally fear exclusion, so in communities that insist on conformity to a norm, we are less likely to explore the boundaries of ideas at the edges of the group’s consensus. For instance, where there’s high psychological safety (that is, where people feel comfortable with interpersonal risk-taking), learners are more likely to engage in active learning, take risks, ask questions, and collaborate with others – positively influencing learning. Or where there’s a high authority gradient (that is, a high degree of perceived power distance between individuals or groups), learners might feel less empowered to ask questions or to participate in their own learning processes, which can reduce engagement and lead to less effective learning.
[8] Broader Context
Finally, the broader context that surrounds us influences how and what we learn. This includes direct and obvious factors, such as organisational learning requirements, faculty and employee workloads, and organisational support and incentives for learning. Many more distal factors could be added here, for example, public health conditions – something we likely all experienced as a moderator of learning during the pandemic. We could name many other factors in this vein, like government initiatives, economic pressures, the job market, resource availability, national stability, and even the global zeitgeist. The point is that everything around us – to some extent – influences us, and naturally that means all of these things affect one of our innermost functions: learning.
Summary
In this section, we’ve explored a broad range of individual, social, and contextual factors that impact on our ability to learn. Some of these are so obvious that it may seem simplistic to talk about them at all, but of course, these factors interact with one another to produce complexity. And the punchline is that each element, and their interactions, affects learning.
While it’s unrealistic to account for every difference, some are more easily adapted to, others are within our power to control, and a handful will have an outsized impact on learning. (Or as a learning scientist might say, account for a larger proportion of the variance in learning outcomes.) All of this speaks to a more holistic, more effective, and evidence-based approach to the design and support of Organisational Learning.
Or to put it another way: there are factors that affect learning that are simply, cheaply, and easily under our control or influence. Not every solution will be a new technology or grand idea. We can shift outcomes in small ways that are highly practical. It’s about taking a broad mindset and a little evidence as our foundations for action.
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