The Greek philosopher Plato once declared that ‘knowledge is the food of the soul.’ Classical philosophy posits that any meaningful learning must combine an existential knowledge of the self alongside the cognitive domain. In this sense, deep learning goes beyond learning ‘content,’ and is more concerned with the gaining of long-term wisdom and critical competencies that interact with our environment and can be transferred and revised in different contexts. If deep learning elicits deep understandings and profound change, it certainly is, as Plato declared, ‘food of the soul.’
Deep learning starkly contrasts to what we understand as the manufacturing model of learning that was, and to some extent, still is, at the heart of our modern education system. The Industrial Revolution fostered a passive learning model based on rote memorization, where students uncritically received content transmitted by an instructor. Plato would have turned in his grave.
Is it possible that the advent of our knowledge economy/society is bringing history full circle? With the individual learner returning to the forefront, deep learning supports vibrant and creative knowledge creation and the formation of innovation and critical thinking capabilities that underpin our knowledge economy. Accelerated technological change has forced us to reconsider definitions of learning, learning environments, and individual learners’ roles. Humanistic educators embrace a more holistic view of academic success to include non-cognitive outcomes such as emotions, social skills, and moral understandings.
More than ever, it is important for learners to develop rapid and transferrable understandings. This is where microlearning comes in with its precise selection of engaging needs-based content that is relevant and provided just-in-time. Cal Newport, academic and author of Deep Work, stresses that ‘to remain valuable in our economy you must master the art of quickly learning complicated things.’ It turns out that efficient learning doesn’t necessarily equate to shallow learning, and such associations between depth and length are misguided. High-quality microlearning is much more likely to eventuate in deep learning than any doorstop textbook or encyclopedic lecture. The golden rule is — if engagement is low, long-term retention will be low. Content that is tedious and doesn’t hold consistent relevance is notoriously low ROI.
How does microlearning support deep learning?
By utilizing a microlearning methodology, learning is not only more convenient and more engaging but has the potential to provide a deeper level of learning beyond content-level understandings. High-quality microlearning facilitates deep learning by providing learners with ongoing opportunities to solidify understandings, practice skills, gain feedback, and reflect on their learning and performance. Using technology to provide continuous support and instant feedback raises engagement levels and ensures that you don’t lose or disengage a proportion of learners along the way.
Deep learning is further supported by microlearning’s ability to simulate ‘hands-on’ learning experiences. Through a combination of interactive videos, gamified features, or through immersive technology such as augmented reality (AR), virtual reality (VR), and mixed reality (MR), multiple learning systems are activated within the brain, which serve to enhance the efficacy and depth of learning [side note: ‘deep learning’ is also a subset of AI machine learning systems that create artificial neural networks modelled on how the human brain works].
Microlearning achieves deeper retention by using short bursts of targeted learning to optimize cognitive load into the working memory.1 Microlearning’s incorporation of spaced repetition algorithms more effectively encodes deep learning into long-term memories.
Deep learning strategies
1) Flipped learning
One of the simplest ways to raise the ROI of face-to-face learning interactions is to use a microlearning component as a primer. Essentially, you want to flip the order of content so learners process ideas and frame their own independent mental models before walking into a face-to-face collaborative setting. While flipped learning could be as simple as a series of multiple-choice questions, if deep learning is the aim, combine the microlearning component with open-ended, higher-order questions that can be used as a prompt for collaborative creative thinking and problem-solving.
2) Learning campaigns/campaign-based learning
Instead of approaching training as a one-off initiative, take a leaf out of the marketing book to create a blended learning experience that is distributed over a longer period of time. Campaign-based learning uses marketing theories to zone in on a focus topic via interconnected bite-sized chunks of content through different mediums and different learning stages from pre-launch to follow-up campaigns. Consider blending digital content with offline points-of-contact (POCs) using social media, pop-up quizzes, company book clubs, posters, or town hall meetings. Learning campaigns help establish a continuous learning culture and have the power to create lasting behavior change.
3) Targeted learning
Priming students for deep learning is not reliant on traditional long-form content; in fact, it can be more effective to feed through a stream of strategically spaced learning bursts that are shorter in length, but highly targeted and broken down into discrete elements. Microlearning also makes it possible to send out ‘learning pulses’ in specific scenarios to allow for greater application of learning in context.
4) Double and triple loop learning strategies
Incorporating metacognitive ‘thinking about thinking’ into learning experiences is one of the most effective ways to transform content-level knowledge into more profound understandings. Harvard professor and influential management theorist, Chris Argyris, articulated this as moving from single to double-loop learning.2 In single-loop learning, we typically approach challenges and new ideas repeating the same patterns of the past with little critical scrutiny. Single-loop learning is, to borrow the words of Albert Einstein, ‘doing the same thing over and over again, but expecting different results.’ In contrast, double-loop learning requires some modification of our mental models and linking the development of skills to a broader outcome. For example, instead of thinking ‘the skill I am learning is an upselling technique,’ you might say, ‘how am I changing my behavior to learn to communicate with people and read their cues in different ways.’
It’s important to include deep reflective opportunities at different stages throughout a microlearning journey in order to complete a learning cycle. This double-loop learning cycle can be extended to a triple loop when learners reflect beyond what they learned to how they learned and how their thinking has changed. Incorporating simple thinking routines into a module will help enable learners to link content learning to changes in their thinking, and through this, establish more durable understandings. According to microlearning expert and cognitive scientist Markus F. Peschl, triple-loop learning transcends the domain of knowledge organization and intellect and enters into the domain of wisdom, resulting in a profound change in attitudes, values and personality.3
5) Social learning
One of the most effective ways to elicit profound change in people and their habits is through the formation of a shared reality. The ongoing nature of microlearning fosters a culture of continuous learning that becomes a shared reality for all participants. Within the microlearning environment, social features such as forums and peer-to-peer authoring tools provide learners with opportunities to reframe their understandings through interactions and observations.
6) Use pedagogical mental models
It’s important to consider relevant learning theories and instructional design checklists when embarking on designing a microlearning module. Incorporating pedagogical frameworks into your learning design could be as simple as employing Bloom’s Taxonomy as a checklist to ensure you have the right balance of scaffolding to higher-order activities. Learning theories can be particularly useful in aiding learning and development (L&D) leaders in pushing leaders to move from superficial to deep understandings.
Interested in taking an EdApp microlearning course that delivers interactive content to you in small, digestible chunks? Why not explore a course on Team Cohesion here, where you will learn how to build happy, well-functioning teams in a professional environment. This course – and all content in our growing, editable library – is completely free for you to take, as many times as you like.