About the author: Dominic Zijlstra used spaced repetition and other evidence-based methods to learn 3000 Chinese characters. He turned his method into a learning app called Traverse and learned web development and marketing along the way (using the same method). He continued learning languages and is now fluent in 6.
A few weeks ago, the room I’m sitting in now was a mess. Stacks of books on my desk and the bookshelf, my laptop and screen barely visible beneath a landslide of papers and sticky notes. Pens, headphones, chargers, microphones, and other obscure electric devices were scattered around on the floor and chairs.
Yet, I insisted that I’d be able to ‘find what I need, when I needed it’.
But then, my parents-in-law announced they’d visit. So I finally decided to tackle the task of sorting out this mess (and creating an impression of an organized person). In the end, it took less than an hour, and I felt a huge sense of relief.
Finally, everything was in the logical place it belonged, and I could feel my productivity jump almost instantly.
When learning something new, our experience is often similar. We just memorize the minimum basic facts to pass the next test, or look smart in the next meeting. Spaced repetition software like Anki, which makes it easy to remember many facts quickly, makes this approach even more attractive.
But there is a hidden cost to focusing on isolated facts. We lose sight of the forest for the trees. We never truly see how things connect to the bigger picture. This means that when the next exam or high-stakes meeting comes, we have to start learning all over again. And this time, the content is even more demanding, so we need to cram more facts, which generates even more stress... to the point where studying becomes an anxiety-inducing activity.
Just like tidying up your room provides a sense of relief, investing a bit of upfront time to actually think about what we’re learning, helps us connect the dots, and make logical sense of a complex topic. It saves hours of tedious repetition and stress down the line.
Deep inside, we already know this, it’s just that we tell ourselves that “ain’t nobody got time for that”, or “I’m not smart enough to really grasp this” - convenient lies which keep us in our bad study habits.
Popular study advice aggravates the problem: “spaced repetition and active recall is all you’ll ever need” - in other words, just memorize, review and repeat, repeat, repeat.
Don’t get me wrong: I’m a big believer in spaced repetition - it helped me learn over 3000 Chinese characters. But spaced repetition is a tool in a toolkit, not a universal remedy.
When spaced repetition is all you have, it can lead to hours of boring flashcards to review, with the number of cards due for review becoming more intimidating every day. But when used correctly, it is a powerful tool to solidify deeply learned principles, so that a single AHA moment will help you ace tests and solve problems throughout your whole career.
Here I’ll present a practical guide of how you can use spaced repetition for maximum effect on your academic performance, and where it fits into an overall effective study system for academic excellence.
Table of Contents
A recipe for remembering anything?How I learned 3000 Chinese characters using spaced repetitionThe real science behind spaced repetition (what study influencers get wrong)The myth of Ebbinghaus and the Forgetting CurveThe testing effect and the spacing effectHow Anki is different from ‘just flashcards’Does spaced repetition actually work?Obsessing over the optimal schedule: a waste of time?The problem with active recall and spaced repetitionThe “Zero notes in med school” mythWhat only the top 1% of students doEncoding, cognitive load and higher-order thinkingFlattening the forgetting curve with mind mapsThe right way to use spaced repetitionHow to make flashcards that workVarying your retrieval practiceThe best spaced repetition appApp reviewsAnkiQuizletRemNoteTraverseNotionObsidianNotabilityComparison TableConclusion: Prioritize Understanding, Optimize for Memory
A recipe for remembering anything?
Spaced repetition, and its practical implementation in apps like Anki, comes with a big promise: an automated, science-backed system that lets you remember anything you want. Making memory a decision, rather than something depending on what your monkey brain decides to pay attention to.
As tools-for-thought researcher Michael Nielsen puts it in his essay Augmenting Long-term Memory:
"The single biggest change that Anki brings about is that it means memory is no longer a haphazard event, to be left to chance. Rather, it guarantees I will remember something, with minimal effort. That is, Anki makes memory a choice."
The promise of memory as a choice seems to resonate with many people, and interest in spaced repetition has risen steadily over the past years:
How I learned 3000 Chinese characters using spaced repetition
I first heard about spaced repetition when I was learning Mandarin Chinese. I had tried many note-taking techniques and online courses to make those characters stick, but nothing worked.
When I first came across spaced repetition, it felt like magic. Suddenly I had a system for my review practice. And it showed me what I needed to learn at the optimal time!
While spaced repetition certainly wasn’t the only learning technique I employed (more on that later), it did enable me to memorize an amount of information that just didn’t seem possible before. I’ve memorized around 3000 characters now and am conversationally fluent in Chinese - as well as in six other languages.
Many students, like me, are getting good study results using spaced repetition, which undoubtedly contributed to and led to its current popularity.
But, with over 67% of students using flashcards nowadays according to one study, more and more students get stuck in ‘flashcard hell’, feeling numbed down, or spending many hours a day memorizing isolated facts, or are simply left feeling that ‘there must be a better way’.
This is not surprising, given that spaced repetition, and in particular Anki, is frequently portrayed as the one solution to everything study related.
But that is not at all how spaced repetition was intended. In fact, cognitive science offers us a vastly better and more complete solution, which I’ll show you in a bit! But first, let’s look at what the research says about spaced repetition:
The real science behind spaced repetition (what study influencers get wrong)
The myth of Ebbinghaus and the Forgetting Curve
The misconceptions around spaced repetition start with its very beginnings.
The invention of spaced repetition is often misattributed to Hermann Ebbinghaus, a 19th-century German memory researcher.
But what did Ebbinghaus actually do? His original research paper, first published in 1885, is an interesting read, but nothing close to the way spaced repetition is used to study:
- He tried memorizing nonsensical series of syllables, like WOB VYF NEC, which, from a neurological perspective, is very different from learning meaningful information like the bones in the skeleton
- He is talking about literally hundreds of repetitions, a few minutes apart, and then testing himself the next day. This looks more like cramming, which is the opposite of the effective study we’re trying to achieve when using spaced repetition.
- While he did write down a formula for a ‘forgetting curve’, it is not the exponential curve circulating in popular media. He never drew an actual cure, but when we plot his formula b = 100k/((log t)c +k), we get the curve below. Note that time is in minutes here! When we look at this curve at the time scale of multiple days, it becomes basically flat.
So who invented spaced repetition? It was actually the Polish Computer Science student Piotr Wozniak, who published the graph below in his master's thesis in 1990, based on his research five years earlier, exactly a hundred years after Ebbinghaus’ research.
As a practical person, Piotr developed a software around the idea of spaced repetition, which he called SuperMemo. I will not relate the full history of SuperMemo and spaced repetition here, as you can read it in detail on Piotr’s blog.
The algorithm behind SuperMemo would later become the basis for Anki, the most popular spaced repetition flashcard software today.
Apart from Wozniak’s master thesis, what is the actual scientific research on spaced repetition?
The testing effect and the spacing effect
When talking about Anki and effective study, we are actually talking about two things:
- The testing effect
Also called ‘active recall’, the testing effect states that it’s more effective to actively test yourself on a piece of knowledge by giving your brain a prompt, rather than passively re-reading that same piece of knowledge.
A recent meta-analysis of 118 studies in cognitive science showed that the testing effect is well-established, being on average 51% more effective compared to passive re-reading, and 93% more effective compared to ‘doing nothing’. The results hold both in the lab and in the classroom.
- The spacing effect
Contrary to popular belief, the spacing effect is not the same as spaced repetition. The spacing effect merely states that it is more effective to space out your studying over multiple sessions (spaced practice), compared to cramming everything at once (massed practice).
A meta-analysis of 29 studies showed that the spacing effect is also well-established, with spaced practice being 74% more effective compared to massed practice (cramming).
How Anki is different from ‘just flashcards’
So, both active recall and the spacing out of study sessions have been scientifically proven to be effective study methods. Two points for Anki.
But we can get these two benefits with any flashcard software, like Quizlet, or even paper flashcards.
What Anki, like Supermemo before it, does differently is the idea of spaced repetition: that the forgetting curve can be ‘reset’ by repeating reviews at increasing time intervals.
The popular explanation goes as follows: retention of newly learned information decays exponentially over time, as visualized in the forgetting curve.
The idea is, that by repeating the information after it has decayed to about 80% retention, you can not only reset the forgetting curve to 100%, but also decrease the exponential decay factor, so that the new forgetting curve decays more slowly.
Hence, the time interval for the next repetition is increased. When repeating this multiple times according to the optimal spaced repetition schedule, the forgetting curve becomes increasingly flat, meaning that you can now remember that information for the long term.
Does spaced repetition actually work?
Since the first spaced repetition software, SuperMemo, was built before any actual research into the forgetting curve and repetitions (apart from Ebbinghaus’ research dissected above), the origin of the forgetting curve and the spaced repetitions come from the engineers of SuperMemo, mostly Piotr Wozniak.
The idea sounded compelling and soon started to be researched.
Initial research, like this study, found spaced repetition to be effective indeed for learning simple language vocabulary, suggesting a schedule of "reviews 5-10 minutes after the end of the study period, 24 hours later, 1 week later, 1 month later, and finally 6 months later”.
More recent studies, 29 of them summarized in the meta-analysis mentioned earlier, confirmed the effectiveness of the spacing effect, but did not find strong evidence for the superiority of a schedule of increasing time intervals, as opposed to fixed intervals (for example, once a week for 6 weeks). This is especially true as the material to be learned is more meaningful (let’s say, the body's inner workings, as opposed to random vocabulary).
According to the meta-analysis, studies found on average that a spaced repetition schedule was only 3% more effective than a fixed repetition schedule.
Obsessing over the optimal schedule: a waste of time?
So it seems like the gains from finding the optimal schedule for spaced repetitions are very marginal.
Nevertheless, there are still clear benefits from using a spaced repetition software like Anki, because it generates a schedule in the first place, removing the boring work of planning and calendaring so you can spend more time learning the actual content. Besides, a nice side effect of a schedule of increasing intervals is that you’ll always have a good mix of new and old learning material.
But the obsessing about the optimal schedule that we often see seems like a misplaced effort, knowing that we can expect benefits at an order of just around 3%.
Instead, there is a whole other area of cognitive research which you can easily incorporate into your study practice with a much better return on time invested. Unfortunately, this hasn’t yet got the same amount of attention that spaced repetition has, so I’ll discuss it in the next section:
The problem with active recall and spaced repetition
All of the above is not saying that you should not use spaced repetition. The spacing and testing effect certainly do their job, and a spaced repetition is a nice optimization. But since these techniques have now reached the mainstream and about 67% of students use them in one form or another, active recall and spaced repetition no longer offer you any competitive advantage over your peers. They may be necessary in order to pass, but they are not sufficient to achieve top grades.
However, if you mix spaced repetition with a certain magic procedure, you’ll unleash its full potential. In this section, I’ll provide a fully science-backed solution to do that, which is still little known. I hope to change that, but until then you can use this little secret as a surefire way to outrank your peers.
The “Zero notes in med school” myth
Many of the popular YouTube study influencers fall into the same trap as I did, when I had no structure to my retrieval/ study practice. Rather than making an upfront effort to comprehend the material, they recommend directly making flashcards in Anki as we encounter material for the first time.
Or, according to some, not even that, but instead just load one of the many Anki shared decks which others have already created, and spend all your studying time reviewing those cards over and over again.
This is how the myth of passing med school while taking zero notes was born (I’m taking med school as an example here because the problematic advice seems most widespread there, but it applies to any reasonably complex field of study).
Here we are getting into the heart of what’s wrong with how spaced repetition is portrayed in mainstream media. Spaced repetition (and active recall) was never intended to be a complete study solution, not even by its most fierce proponents such as Piotr Wozniak or the creators of Anki.
Spaced repetition is part of retrieval practice. Retrieval is when we retrieve knowledge that was previously stored in long-term memory.
But how does it get into long-term memory, or LTM for short, in the first place?
When we read or hear something, it goes first into our short-term memory (STM). In 99.9% of cases, it’s forgotten seconds later. This is a good thing. We don’t want to remember every detail of everyday life.
Our short-term memory can only hold 7 items at the same time. So either you forget it, or you have to commit it to long-term memory (LTM).
The process of moving items from STM to LTM is called encoding.
What only the top 1% of students do
All of the talk about active recall and spaced repetition focuses on optimizing your retrieval practice. This matters, because every time you retrieve information from long-term memory, it is reconsolidated, making that memory stronger and easier to retrieve the next time (for example, on a test). Although the exact math behind retrieval is far from clear (as mentioned above), the fact that retrieval practice benefits memory is undisputed.
But what 99% of students ignore is the initial process of encoding new information and storing it in long-term memory.
This is the bit where I actually took the time to tidy up my room, and just put a bit of thought into where every item should be placed logically.
Putting thought into encoding is key, as there are many different ways to encode information and store it in LTM. The encoding you choose matters a lot for how well you remember it.
If you store isolated single items in LTM, they will be forgotten relatively quickly.
In terms of the forgetting curve, the initial decline will be steep.
For example, when I was learning Chinese characters, initially I was just learning them as isolated facts, and it took me many spaced repetition reviews to remember each. It wasn’t until I discovered how to break down characters into their basic components, that I could see how all characters connected to each other and was able to effectively encode them, by visualizing all character components in a mnemonic story (the ‘movie reviews’ I showed you earlier). Now I could learn by using understanding rather than rote memory, which saved me tons of time!
And this is the part only the top 1% of students know:
If you improve your encoding, the forgetting curve will decline much slower to begin with!
Digital pedagogist Efrat Furst calls this ‘making meaning’, an essential stage in both learning and teaching, before moving to a desirably difficult retrieval practice.
You save yourself tons of reviews by putting more effort into proper encoding.
And the great thing about doing good encoding is that it gives you these WOW and AHA moments of deep insight. Those moments are a sure sign of learning (whereas flashcard fatigue - the feeling of boredom when reviewing too many cards - means you’re NOT actually learning!).
Encoding, cognitive load and higher-order thinking
Understanding is memory in disguiseDaniel T Willingham - Why don’t students like school (2009)
So how can you do better encoding?
It’s like asking, “how can I better organize my room?”
Unlike spaced repetition, there isn’t an easy recipe (which is probably the reason that is hasn’t gotten as popular yet), since you actually have to put thought into it.
Encoding involves things like cognitive load theory and higher-order thinking. We have already written a more extensive treatment of encoding and listed some practical study tips around encoding, so I recommend checking these out if you’re interested in the topic.
Dr. Justin Sung, one of the advisors behind our app Traverse, also does a great job explaining it in his popular video The PROBLEM with Active Recall and Spaced Repetition (Truth Behind Studying Smarter).
I’ll briefly list some practical study techniques for encoding here which studies show can increase learning outcomes:
- Delayed, connected note-taking: taking high-level notes after the lecture (as opposed to verbatim notes in class). A meta-anaysis showed that note-taking in general increased retention by 22%, going up to over 50% when putting thought into notes rather than copying what the teacher said word for word
- Drawing out concepts, as opposed to writing, is associated with even better encoding, with studies showing retention improvements of up to 200%. A more structured way of drawing is mind mapping, first introduced by Tony Buzan in 1974.
The common denominator between all encoding techniques is that they increase cognitive load - they make you think. A whitepaper by iCanStudy suggests that students using their cognitive load based study methods improved study efficiency by 2x for 90% of students, while also improving retention and grades.
Mind- and concept mapping can be done in many different ways, and how it’s done matters a lot.
Studies directly comparing concept mapping and retrieval practice did not find much benefit from concept mapping without explicit guidance, as both tools-for-thought researcher Andy Matuschak as well as long-term spaced repetition expert Gwern Branwen pointed out to me.
This is probably the reason that many students say “I’ve tried mind mapping and it didn’t work for me” - it’s difficult to do it the right way. Justin Sung from iCanStudy has described in detail how to do mind mapping the right way, which we’ll recap for you below.
Flattening the forgetting curve with mind maps
Only 11.7% of students spontaneously create mind maps when learnings something new. This is good news if you’re part of that small group because, unlike flashcard practice, there is still a big opportunity here to perform significantly better than your peers.
In order to get the maximum learning benefit from mind maps, the following process (which we wrote about previously) should be followed:
- Identify the main groups or chunks of information within the learning topic
- Grow the knowledge tree by branching out each chunk
- Link chunks together in the most logical way
- Use visualizations to represent concepts as much as possible (learn more about leveraging your visual cortex to learn in our article about memory palaces)
- Add a logical flow by giving direction to the links and ordering the chunks
- Emphasize and prioritize what is important and what is detail
The most awesome thing is, that we can still incorporate spaced repetition flashcards into these mind maps, to combine an effective encoding practice with an optimal retrieval practice (which is why we built Traverse, the only study app that combines mind maps, notes and flashcards):
The right way to use spaced repetition
So now that we know that we need to tidy up our room first, and we got a glance at how to organize things for maximum results, we can look at what to do after everything makes logical sense to consolidate it into long term memory. This is where spaced repetition comes into play:
How to make flashcards that work
A good repetition practice starts with creating good flashcards.
Next to mind mapping, creating thoughtful flashcards can be a great way to improve how information is encoded into long-term memory.
A note on shared decks
Shared decks are a great supplementary source and you can get inspired by how others encoded the information. However, if you solely rely on someone else’s flashcards, you bypass your own encoding process. Essentially, you’re trying to memorize what you do not yet understand. This results in tedious flashcards, which need a lot of repetition and you may still not see the bigger picture. So use shared decks to supplement and inspire, not to mindlessly copy.
There are three main guidelines for making effective flashcards:
- A single flashcard should focus on a single concept
- The question should be precise (vague questions don’t allow you to evaluate whether you got it right or not)
- The flashcards should be effortful, actively making your brain work (high cognitive load)
For example, the following is considered a bad flashcard:
It focuses on multiple things (the location where transcription occurs, and the substance it creates), it’s vague and hard to evaluate, and, most importantly, it only requires you to recall a single fact in isolation. Having many of these flashcards can make you feel like you’re missing the bigger picture because you’re learning all these isolated facts without ever stopping to think about how they relate.
The flashcard below is much better:
It is simple and precise (asking only for ‘the first thing’), and it requires you to actively think about how things connect together (in this case, the process and the substances it produces).
For more guidance on how to create good flashcards, read our guide on creating effective flashcards, as well as the work of “tools-for-thought” researchers Michael Nielsen (Augmenting Long-term Memory) and Andy Matuschak (How to write good prompts: using spaced repetition to create understanding).
Varying your retrieval practice
Now that you have good flashcards, you can practice them with spaced repetition. The way to do that is to do flashcard reviews in ‘dead time’: time which you cannot use to practice techniques that require more dedicated attention (like mind mapping), for example when waiting in a queue, when in public transport etc. You just do however many flashcards naturally fit in these ‘micro-learning’ sessions every day. Do not in any way feel obliged to clear your flashcard queue.
Instead, you can use the focused study time you have on a given day to do higher-return study activities, resulting in an overall more varied practice. For example, you could rewrite flashcards and come up with new creative practice problems.
But retrieval practice is not limited to flashcard practice. You can also revisit and revise your mind maps, or use strategies like the Feynman technique (explaining the concept you’re studying to a layman, a method associated with up to 30% deeper understanding), elaborative interrogation (coming up with your own explanations), and interleaving (mixing different types of learning materials).
None of these techniques is perfect by itself, but that is the point: a varied retrieval practice helps you view the learning material from many different perspectives, so you can truly master it and are likely to nail any test (even if you have no idea in what way the material will be quizzed).
The best spaced repetition app
Now that we know how to use spaced repetition in an effective study practice, we can find the best way of bringing it into practice.
As we now know that spaced repetition is only a small part of an effective study process, we’re taking a holistic view, and including all of the most popular study apps. Some of them focus on flashcards, some on note-taking, some on mind mapping, and some provide a combination of features.
We’ve evaluated every app with the main criterium: does it allow you to set up an effective, evidence-based study practice?
App reviews
Anki
Anki is the classic choice for spaced repetition practice, and especially popular among medical students. While it is very customizable in terms of spaced repetition scheduling and flashcard content, the interface is outdated and the app has a steep learning curve. Apart from extensive support for grouping and tagging flashcards, there is little support for features that help you encode information better.
Conclusion: Anki can be used for spaced repetition practice only, but you would need to supplement your practice with other apps to achieve effective encoding and avoid getting stuck in ‘flashcard hell’.
Quizlet
Quizlet is another popular choice for flashcard practice. What it has going for it is that it’s much simpler to use than Anki. While it doesn’t have spaced repetition support, that doesn’t need to be a barrier (as we’ve seen from the research on increasing intervals). It does have a strong focus on shared decks though, so it’s easy to be tempted to not even write your own flashcards in the first place.
Conclusion: Quizlet’s flashcard experience is solid, but you’d have to supplement with other apps for encoding and need to watch out to not fall into the lazy shared decks trap.
RemNote
RemNote offers note-taking as well as flashcards. Notes can be interlinked and grouped in ‘rems’. Flashcards need to be created inside notes, which takes some getting used to, but overall the spaced repetition experience is decent. There is also partial support for importing Anki decks for students who want to move over, although schedules will not be preserved, and images, audio and video will only be imported in some cases.
Conclusion: RemNote is a decent attempt at combining both encoding and retrieval practice. The only limitation is that everything is plain old text, so that visual note-taking and mind mapping remain out of reach.
Traverse
Traverse is an app we developed with the explicit goal of offering a complete, science-backed study method all in one app. There are easy-to-use spaced repetition flashcards as well as note-taking, and everything is visually organized on a mind map, allowing you to deeply express your thoughts and learnings in a vivid and colorful way. For those moving over from Anki, decks can be imported including scheduling information, media and image occlusions.
Conclusion: Traverse is currently the only app out there that offers a complete evidence-based study process. No wonder it’s backed by advisors such as Dr Justin Sung.
Notion
Notion was never intended as a study app, but its popularity as a task-management tool has caught on with many students as well. This is unfortunate because apart from advanced note-taking features, Notion does not offer anything that supports the actual learning process.
Conclusion: a great task management tool (we use it to manage our projects at Traverse, as well as this blog!), but unsuitable as a learning tool.
Obsidian
Obsidian markets itself as a personal knowledge management tool. Since the focus is on building a ‘second brain’, rather than improving learning in the user’s actual brain, it lacks retrieval practice features such a flashcards and microlearning (although some form of spaced repetition can be added with custom extensions). Its capabilities for encoding knowledge are strong though, especially since they added a mind mapping canvas last year.
Conclusion: a great tool for encoding, but needs to be supplemented with other apps for retrieval practice.
Notability
Similar to Obsidian, Notability is a great app to express and encode new ideas and knowledge. It has a stronger visual focus than Obsidian, but is more limited in its note-taking capabilities.
Conclusion: like Obsidian, a great tool for encoding, but needs to be supplemented with other apps for retrieval practice.
Comparison Table
We’ve summarized all the learning science-related features of all popular study apps in the table below.
Traverse is the only app that covers the full spectrum, with flashcards, note-taking and mind mapping in one. Not surprising since our goal in developing is to create a complete evidence-based learning app.
Alternatively, a solid study practice can be achieved by combining some of the other apps listed. This however comes at the cost of frequently moving information from one place to another - time that could perhaps better be used for learning.
ㅤ | Anki | Quizlet | RemNote | Traverse | Notion | Obsidian | Notability |
Flashcards | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
Spaced repetition | ✅ | ❌ | ✅ | ✅ | ❌ | only with extension | ❌ |
Microlearning | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
Note-taking | ❌ | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ |
Mind mapping | ❌ | ❌ | ❌ | ✅ | ❌ | ✅ | ✅ |
Creating connections | ❌ | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ |
Color-coding | only with extension | ❌ | ❌ | ✅ | ✅ | only with extension | ✅ |
Grouping | ✅ | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ |
Visual organization | ❌ | ❌ | ❌ | ✅ | ❌ | ✅ | ✅ |
Free hand drawing | ❌ | ❌ | ❌ | ✅ | ❌ | ❌ | ✅ |
Anki import | Not applicable | ❌ | Partial (no scheduling, limited media) | Full (scheduling, media, occlusions) | ❌ | ❌ | ❌ |
(Features in blue relate to retrieval practice, while features in green relate to encoding.)
Conclusion: Prioritize Understanding, Optimize for Memory
To recap, spaced repetition is not a complete learning solution, but it has its place in a balanced, evidence-based study practice.
As a rule of thumb, when studying, you should prioritize understanding, and optimize for memory.
What we mean by that, is that the first and essential thing to do is to put effort into encoding the information properly into long-term memory. Visually map things out, and figure out how the pieces connect together in the bigger picture. Only once you have achieved this level of understanding should you focus on memorization.
Retrieval practice can then be optimized by using both active recall and spaced repetition. Test yourself, and space out your study sessions. Finally, vary your retrieval practice by revisiting mind maps and flashcards, as well as by using the Feynman technique.
Is it actually possible to achieve these results in real life as an overwhelmed and time-constrained student? With users of our app Traverse, we’ve seen that it is.
Take Raleigh Sorbonne for example. He was studying for the MCAT, a 6-hour exam to enter medical school. After researching dozens of tools, he had a strong feeling that there had to be a better way to learn. Finally, when coming across Traverse, Raleigh was able to study more efficiently than ever before, while saving time and having more fun in the process. When he took the test, he got a 99th percentile score.
So I have seen this method work for myself and others, and I know that it will help you as well, which is the reason that I’ve written it down in this format for your benefit.
If you are ready to try and incorporate effective encoding in your study practice, the best advice I can give you is to sign up for our app Traverse, import your Anki decks if applicable, and start grouping, connecting, color-coding and prioritizing your knowledge visually.
Supporting Studies and Research
- Report on Learning: A Practical and Learner-Centric Perspective by Sung · 2022
- The Relation Between Students’ Effort and Monitoring Judgments During Learning: A Meta-analysis by Baars et al · 2020
- Learning How to Learn by Oakley · 2018
- Problem of Schooling by Wozniak · 2017
- The multi-store model of memory by Atkinson and Shiffrin · 1968
- The magical number seven, plus or minus two: Some limits on our capacity for processing information by Miller · 1956
- Make it Stick by Roediger & McDaniel · 2014
- Rethinking the Use of Tests: A Meta-Analysis of Practice Testing by Adesope et al. · 2017
- Impact of reducing intrinsic cognitive load on learning in a mathematical domain by Ayres · 2006
- Learning as a generative process by Wittrock · 2010
- A Systematic Review of Higher-Order Thinking by Visualizing its Structure Through HistCite and CiteSpace Software by Liu et al · 2021
- Dialogue Mapping: Building Shared Understanding of Wicked Problems by Conklin · 2005
- Human problem solving by Newell & Simon · 1972
- Cognitive Architecture and Instructional Design: 20 Years Later by Sweller · 2016
- Perceiving effort as poor learning: The misinterpreted-effort hypothesis of how experienced effort and perceived learning relate to study strategy choice by Kirk-Johnson · 2019
- How and when do students use flashcards? by Wissman · 2012
- Everyday lessons from the science of learning by Lang · 2016
- Effects of self-explanation as a metacognitive strategy for solving mathematical word problems by Bielaczyc et al · 1995
- The Dunning–Kruger Effect: On Being Ignorant of One's Own Ignorance by Dunning · 2011
- A Meta-Analytic Review of the Benefit of Spacing out Retrieval Practice Episodes on Retention by Latimier · 2021
- Use Your Head by Buzan · 1974
- Chunks in expert memory: evidence for the magical number four ... or is it two? by Gobet & Clarkson · 2004
- Development of Theory of Mind and Executive Control. Trends in Cognitive Sciences by Lang et al · 1999
- Moonwalking with Einstein by Foer · 2011
- Über das Gedächtnis by Ebbinghaus · 1885
- Measurement of Cognitive Load in Instructional Research by Paas & Van Merriënboer · 1994
- The effects of interleaved practice by Taylor & Rohrer · 2009
- How to Take Smart Notes by Ahrens · 2017
- Learning how to use a computer-based concept-mapping tool: Self-explaining examples helps by Hilbert & Renkl · 2009
- Traditional and Inquiry-Based Learning Pedagogy by Khalaf · 2018
- Using elaborative interrogation by B Kahl · 1994
- Mind Mapping in Learning Models: A Tool to Improve Student Metacognitive Skills by Dyah Astriani · 2020
- The effect of mind-mapping applications on upper primary students’ success and inquiry-learning skills in science and environment education by Ali Günay Balım · 2013
- The Effect of Concept Mapping to Enhance Text Comprehension and Summarization by Chang · 2002
- The Random-Map Technique: Enhancing Mind-Mapping with a Conceptual Combination Technique to Foster Creative Potential by Charlotte P. Malycha · 2017
- Distributing Learning Over Time by HA Vlach · 2012
- Test-Enhanced Learning by Roediger & Karpicke · 2006
- Improving Students’ Learning With Effective Learning Techniques by Dunlosky · 2013
- How to become a Straight-A Student by Newport · 2006
- Experiential Learning: Experience as the Source of Learning and Development by Kolb · 2002
- Cognitive skill acquisition by VanLehn · 1996
- Atomic Habits by James Clear · 2018
- How to Read a Book by Adler · 1940
- Augmenting Long-term Memory by Nielsen · 2018
- How to Create A Memory Palace by Metivier · 2022
- How to write good prompts: using spaced repetition to create understanding by Matuschak · 2020
- The picture superiority effect in recognition memory: A developmental study using the response signal procedure by Defeyter · 2009
