Unprecedented levels of content, gamification, and growth “hacks” vie for our attention. Yes, there are more ways than ever to connect with your learners. But let’s face it, cute cat GIFs and social media are often more enticing. Humans are just wired that way…
At Arist, we’ve built a platform that enables organizations of all stripes and sizes to harness the power of psychology, messaging trends, and micro interactions to grab back the attention of learners. Our tools enable you to reach learners where they already spend more than half of their time: messaging tools like Slack, Microsoft Teams, WhatsApp, email, and SMS text.
It’s worked for students in war torn countries. It’s worked for global sustainability firms providing safety training for employees. And it’s worked to raise completion and retention rates of emergency preparedness learning for an entire state.
The emerging science of microlearning is at the core of our offerings. But to gain the most from microlearning, you have to learn a few concepts, facts, and best practices first. Welcome to our decidedly non-micro guide on microlearning 😎
Table of Contents
Microlearning – also known as nano learning, bite-size learning, or micro training – refers to elearning content and delivery that is optimized for length. As a rule of thumb, microlearning content is as short and to the point as possible without sacrificing important details.
These bite-sized sections of curricula are often referred to as “micro units.” Additionally, microlearning utilizes best practices for engagement and retention including spaced repetition, chunking, and content and delivery that mimics the way we solve problems in real life (more on these techniques later).
A common feature of microlearning includes the delivery of learning “within the flow” of work. Learning may also occur on mobile devices, enabling greater flexibility and a range of “nudges” supporting educational objectives. Some microlearning courses embed the process of learning into daily routines to enhance recall and course completion rates.
Successful microlearning can be characterized as learning that supports the same or better educational outcomes as traditional learning while utilizing less time from each learner.
It’s worth noting that topics covered in microlearning don’t have to be “micro.” In fact, renowned educational psychologist Theo Hug outlined “micro,” “meso,” and “macro” components of microlearning. For example, when using microlearning to learn a language, topics covered could include the conjugation of a verb (a micro topic) as well as cultural differences in nations that speak a given language (a macro topic). Topically, microlearning has been successfully utilized in a wide range of subjects and skill levels of learning participants.
Microlearning has emerged as one of the most promising techniques within access to education initiatives and corporate training. A study from late 2020 notes over 460 peer-reviewed studies have been published on the topic. With this said, the psychological and educational concepts behind why microlearning is effective have been emerging for much of the last century.
The bedrock for microlearning has been discussed since the 1950’s when Harvard-based cognitive psychologist George A. Miller coined “Miller’s Law.” Through a robust analysis of many past studies, Miller’s Law states that the average number of objects humans can hold in their short-term memory is 7 plus or minus 2.
Objects held in short-term memory run the risk of being forgotten. But a process known as consolidation occurs when objects within short-term memory are not crowded out by competing stimuli. When objects can be held in short-term memory for a longer period of time, they can then enter into long-term memory where they can then be recalled.
In other words, most people learn best when they focus on a small number of objects and can keep distractions at bay.
The spacing effect is a phenomenon originally noted in 1885 by psychologist Hermann Ebbinghaus. The basics are that when you actively recall information you’re trying to learn across many different sessions it’s less likely the information will be forgotten. Research in the 1970’s specified that the optimal use of the spacing effect occurs when items are presented four to six times over a period of time and then tested 24 hours later.
In short, we can only hold so many objects in our short term memory, and it takes time to consolidate these memories into long-term memory. Therefore, we should spread exposure to the optimal number of learning objects (7 plus or minus 2) out over time.
The relationship between mobile devices and learning is a growing area of study in workplace efficiency and educational circles. Many of the world’s most popular apps have utilized “growth hacking” techniques to increase feelings of reward – e.g. dopamine levels – for increased in-app engagement. You may have experienced the phenomena of “phantom vibrations” in which you perceive a notification on your phone when there isn’t one. Additionally, use of many recreational apps has been well noted to distract from time or attention spent on school, work, or other responsibilities. In short, user experience and form factor can hold your attention.
Applied to non-recreational uses of time, numerous studies have shown that educational endeavors can leverage the form factor and learned behavior characteristics of smart phones for better learning outcomes. The ability to learn outside of the classroom enables learners to make a wider range of associations with new material, increasing retention. Additionally, the increase in dopamine levels you experience in a notification from an app can be transferred to other apps (such as those providing microcourses).
Now, what isn’t backed by science…?
The notion that human attention spans are shrinking has circled the internet for a number of years. It was even quoted by a Harvard researcher, propelling the myth further. The claim is that the average attention span is down from 12 seconds in 2000 to 8 seconds in 2015 and was originally published by the Consumer Insights team at Microsoft Canada. However, this wasn’t Microsoft’s original research. Rather, the original citation was for a website called Statistic Brain.
Recent investigations have tried to track down this website’s vague citations, with no luck. In fact, researchers say the idea of an “average attention span” is pretty much meaningless.
The notion that our attention spans vary depending on the task at hand is backed by research. Most healthy adults can drive for long periods with relatively few distractions. We stream our favorite shows and tune in for hours. Part of what makes the attention span myth above so believable is that when we talk about attention span we’re really talking about two separate actions.
Transient attention is exhibited when something “catches” your attention temporarily. Perhaps a push notification or a loud noise. Experts disagree about the precise amount of time transient attention lasts, but it’s quickly passing. But grabbing transient attention can be used to transition to sustained attention.
Selective sustained attention lasts for much longer. Estimates for this form of attention start at 10-15 minutes but range into multiple hours when including the action of a person continually re-focusing themselves.
Microlearning is able to leverage both forms of attention. Transient attention is leveraged through notifications within workflows or via phone. Microlearning units tend to take less time than the lowest estimate of selective sustained attention to complete. This means successful microlearning doesn’t have to fight for attention. Rather microlearning relies on the natural amount of time most individuals can focus.
While we’ve barely scratched the surface of research that backs up microlearning, we’ve covered many of the core concepts. At this point it’s safe to say that one of the primary benefits of microlearning is that research shows that it is effective. Microlearning leverages ways in which humans are most comfortable and effective in finishing learning exercises as well as retaining information.
Let’s connect the dots here. We’ve walked through the research-based rationale for microlearning. Now let’s see how these connect to training KPIs.
This is actually an example of a best practice in microlearning: separate related but discrete points into their own units.
Among our 1,000+ microlearning customers and the industry at large, here are some of the most common benefits we’re seeing from microlearning.
Cognitive overload is one of the main culprits of bad learning outcomes. Ever heard that multitasking is a “myth?” Turns out, the “feeling” of multitasking is simply switching between tasks quickly, leaving us less effective at each. This is at the root of cognitive overload. We retain less information when there’s too much of it at once, or too many simultaneous tasks.
Arist’s microlearning leverages nudges “in the flow of work” to gain attention in a constructive way. Microlearning then utilizes best practices in regards to repetition, lesson size, and interactivity to keep cognitive overload to a minimum (regardless of concept).
Microlearning also reduces the burden on educators. No more lengthy lectures that fight for the attention of learners!
Most corporate learning is difficult to tie to business outcomes. One-off learning events are quickly forgotten, and stats like “the average viewer watched 33% of your video” are unactionable.
Microlearning promotes interactions that are clearly validated. Meanwhile the “depressurized” setting of personal text messagesHigher participation rates means better feedback and improvements to future courses. Whether it’s a “read receipt” or a simple text message response to a multiple choice question, you know your learners are engaged. Because content is separated into discrete micro topics, you can discern precisely what information is being engaged with.
Knowledge workers spend over 50% of their time in messaging tools (Slack, Microsoft Teams, email, WhatsApp, SMS text). Meanwhile the average worker spends just 2% of their time in learning management systems. Interactions on unfamiliar platforms add up.
The average knowledge worker checks messaging apps roughly every 6 minutes and 80% of knowledge workers don’t go more than 20 minutes without checking their messaging apps. Microlearning leverages these moments already occurring in most knowledge workers’ days to build in scientifically-backed moments of learning that build off of learners' existing attention.
Learning expert Ray Jimenez highlights that microlearning reduces elearning content development time by 300%, vastly lowering costs on the creation end.
On the learner side, microlearning doesn’t require a great deal of time for effective outcomes. The asynchronous nature of text-based learning also puts the “ball” in the learner’s court allowing them to complete learning when it is personally most effective.
This means more “brain space” to tackle other activities on the part of the teacher and learner.
Hubspot reports that microlearning increases engagement and completion in online training by 4x.
Course completion isn’t a function of whether learners want to complete a course. It’s a matter of making learning as easy, seamless, effective, and rewarding as possible. We all live busy lives, and learning that fits into bite-sized chunks simply works better for many learners and use cases.
95% of individuals answer a text within 3 minutes of receiving it. That’s a quick turnaround for educational settings! Effective “moment of need” education helps to prevent blockers within workflows. “Moment of need” learning also incorporates the notion that learners don’t need to know specific pieces of information until they are blockers. This aligns with the best practices of not overburdening or distracting potential learners.
A 2018 State of Training Industry report notes that the second-largest expenditure in corporate training includes travel, facilities and equipment. Cutting back even a portion of these expenses in favor of microlearning across devices all team members already have can make a huge difference. What’s more scalable than text-based training?
We’ve seen microlearning in a huge range of locations and topics. But that doesn’t mean it’s the best learning choice for every solution. Rather, view microlearning as a low-barrier addition to your training efforts. Much as your content strategy should incorporate multiple formats and distribution channels, so should your educational development strategy.
Some of the most innovative use cases we’ve seen for microlearning center around locales where mobile phone adoption is high, and other traditional educational resources are scarce. For workers in the field, app and mobile-based learning is often the only feasible option for time and cost effective training.
Microlearning leverages interactions that are innately engaging such as conversations through messaging apps and “nudges” via push notification. Unlike traditional education settings in which course creators try to hold attendees' attention for extended periods of time, microlearning doesn’t require as much time to take effect. We'll jump into best practices below, but as a rule of thumb use as much multimedia as you can, visually separate points, and start with a great "hook!"
There are many delivery methods and forms of elearning for a reason. There are situations where each could be the best call for your learning development needs. While we see daily success in a wide range of topics, skill levels, and industries using microlearning, that doesn’t mean that there aren’t challenges.
There’s an art to saying more with less words, and it’s not an easy one. Great communicators may find it easy to translate most topics into microlearning. But even then some topics may defy distillation. With this said, there’s an argument that some topics simply can’t be distilled into a small number of words without missing key details. The core curriculum for a graduate class on the War of Roses likely isn’t a good choice for microlearning-only delivery.
Historically microlearning has been viewed as best suited to applied knowledge, knowledge that requires repetition (for example, foreign language learning) and non-advanced topics. While there are some topics that microlearning likely shouldn’t be the only delivery method for (e.g. surgery), microlearning can tackle smaller topics (e.g. ‘proper hygiene in surgical settings’). We say that a weeklong microlearning course (displayed at once micro lesson a day) is equal to about 2-3 hours of traditional training. Without scaling up your instances of microlearning, there are some obvious caps to how large of a topic can be tackled.
In tandem with our last two points, microlearning is often one delivery method among multiple. While there are instances of skill-based, upskilling, and professional development courses that may be able to live entirely on microlearning platforms, microlearning is often used to augment other delivery methods. The same can be said for any learning delivery method. At Arist, we take this point and try to make the course creation, delivery, and metric tracking take up as little of your times as possible. Want to repurpose other content you already have? It’s a cinch!
Fragmented learning occurs when there are not clear objectives for time spent learning, or when learning time is not clearly delineated from other activities. While learning in the flow of work and life can be beneficial for providing additional “hooks” for your memory, fragmented learning is harder to measure and can lead to poor outcomes. You wouldn’t try to do your taxes while at a movie theater, would you? The solution for this is stronger management of expectations, the ability to catch and hold the attention of your learners, and clearly communicated objectives for each learning episode.
At Arist, we like to call our learning platform the world’s most pragmatic learning. Backed by real data from thousands of successful microlearning courses, we’ve had a front row seat to what works and doesn’t in microlearning. While our platform design stems from cutting-edge educational research, sometimes emerging data speaks for itself and can lead to iterating faster than theory can keep up.
In line with pragmatic learning, start by specifying precisely what you want course attendees to be able to do differently by the end of the course. From here you can break down this high-level goal into the fewest number of sub-tasks it will take to hit this learning objective. Additionally, you can only determine what you’re going to measure in a course relative to what goals you have.
Starting with a specific goal for each individual module helps to prevent fragmented learning. Discrete goals also make it easier to pare supporting content back. Neither you nor your course attendees have all day or an endless attention span. Specific goals can be supported by actions in the KUAR framework (more on this below), which in turn informs even smaller segments within your course.
We’ve seen the most success in microlearning courses when courses are broken down into distinct action-centered activities. In particular, KUAR stands for knowing, understanding, acting, and reflecting. Our progression roughly aligns with Bloom’s Revised Taxonomy. But we’ve found these four categories of actions fit the best with making modules short and impactful. It’s worth noting that these four types of actions pair together well. Example modules could include the following for a project management microcourse:
While knowing, understanding, acting, and reflecting can all occur within the same day of a microlearning course, we’ve seen better results when there’s a 50/50 split between new knowledge and action to codify this knowledge. For instance, you may have a day of a microcourse that focuses on knowing and understanding (introduction of a new concept). And then the following day may include actions and reflections based on this new material.
Most microlearning platforms let you specify the pace at which you send out materials. While we’ve seen the best outcomes when sending a module as well as follow up information (depending on user response) once per day, you have a choice of how many days you want to circle back and then finally test for retention.
Studies on the spacing effect note that the best retention comes from circling back to a concept or fact four to six times, and then waiting 24 hours afterwards to test. This delivery pattern is often best achieved by first introducing new concepts (knowing and understanding) and later applying these concepts (acting and reflecting) across a range of interactions.
Additionally, concepts already covered can be built upon in new lessons, continuing to reinforce the original concepts.
We recommend focusing on one discrete concept per module. But concepts can have several supporting points. Miller’s Law notes that the average human mind can keep 7 (+/- 2) facts in short term or “working” memory at once. Spread out points by using bullets or visually representing information.
A second component of being bite-sized is managing the amount of time learners should spend on their learning. Few text-based microlearning exercises should take long, but applied tasks can easily take too long, losing learners’ attention and lowering task completion rates.
If you’re following the above tip on bite-sized learning, you’re likely well within the bounds of selective sustain attention spans (10-15 minutes before refocusing is needed). Utilizing nudge-based prompts, catchy “hooks,” and engaging animations and videos can help to grab transient attention of learners.
We’ve covered a lot in this decidedly non-micro guide on microlearning! Prefer to see what we mean in a microcourse? Then be sure to check out our free introduction to text based learning course.
To summarize a bit of what we've worked through, we started with the basic definition that microlearning content is as short and to the point as possible without sacrificing important details.
Additionally, microlearning often makes use of mobile devices and nudges within the flow of work (or life) to grab users attention.
Microlearning has been found effective in many studies, with many more studies backing up the underlying educational practices.
We've seen thousands of course makers and attendees benefit from microlearning but like any delivery method, it's not without it's limitations.
On that note we turned to the best practices for creating microlearning content. There are many ways to progressively fine-tune your course, and microlearning makes it easy to iterate quickly for better course outcomes. But some of the basic rules of thumb include starting with your top-level goal for the course, breaking this up into smaller tasks, and keeping engagements targeted and full of direction. Using spaced repetition, the KUAR framework, and keeping modules to <7 points also up retention and engagement.