recursal/Fanatic-Fandom huggingface dataset:
Léonie Couffaine

## Character Information

### Other names:

PrincessLittle Chloé

Darlin'

### Occupation:

Student at Collège Françoise DupontSuperhero

Fashion model

Voice actor

Acrobat

### Likes:

ModelingAcrobatics

Going to the park

Dressing up

Hanging out with friends

Anime

Video games

Superheroes

Baking

Macaroons

Music

Singing

Babysitting (sometimes)

### Dislikes:

CamembertBeing pressured

Villains

Bad people

Dishonesty

Being alone

Feeling helpless

Babysitting (sometimes)

Dogs

Plagg being annoying

## Section Header

### Affiliations:

Sherri Hill (brand)FranceFlower (brand)

Bourgeoiselle (brand)

Miraculous holders

French Miraculous superhero team

### Relatives:

Luka Couffaine (Father)Chloé Couffaine (Mother)

Camillè Couffaine (Older Sister)

Lyna Couffaine (Older Sister)

Liffé Couffaine (Younger Brother)

Anarka Couffaine (Paternal Grandmother)

André Bourgeois (Maternal Grandfather)

Audrey Bourgeois (Maternal Grandmother)

Ali Achu (Uncle)

Juleka Achu (Aunt)

Aalia Achu (Cousin)

Juliete Achu (Cousin)

### Friends:

PlaggLuis Kurtzberg

Noah Kurtzberg

Jyóte Minneyé

Lila Kurtzberg

Alice Kurtzberg

Romy Lê

Harry Dion

Jordan Germaine

Sophia Graham de Vanily

Finn Graham de Vanily

Roxane Lê

Kalvin Lê

Eliot Bruel

### Enemies:

Sasha Agreste (Rival)Málinda Chamois (Rival)

Corrupted Kwami's

## Miraculous Information

### Powers and abilities:

ModellingVoice Acting

Singing

Ballet

Quick Costume Change

Baking

Acrobatics

Enhanced Speed

Super Stealth

Night Vision

Cataclysm
Self-explanation effect

## Promoting The Learning of Explicit Knowledge Components via The Self-Explanation Effect

One way to promote the learning of explicit knowledge components, is by deliberately making students explain why they did something i.e. explaining their implicit knowledge component.

For more in-depth information about the self-explanation effect, see:

Self-explanation is a powerful learning technique, according to meta-analysis of 64 studies involving 6000 participants

Excerpt from the article:

> **It is better to ask a student to see if they can explain something to themselves, than for a teacher or book to always explain it to them.**
>
>

By making them more aware of the explicit knowledge components this, in turn, enables them to engage much easier in metacognitive pre-assessments (alone or in class) and, once again, promote robust learning.

## Writing

And of course, writing about what you have learned is one of the best ways to learn things. Essentially, you are trying to *learn by teaching*, also called the Feynman technique. This I do through this autobiography. An even better way, of course, is to truly have someone in front of you or multiple people that you try to teach things.
Miraculous: Tales of the Lost Kwami's

Template:Comics

>  *"Transform, Purify. How hard can that be?"*
>
> -Tagline

**Miraculous Tales** is set in the time after they all got married and their children grew up and became teenagers. The kwami's are all lost and gone but what will happen when they come back as corrupted monsters? Who will keep Paris safe from harms way? Well might it be our new miraculous superhero's

## Plot

Lyna, Léonie and Alana's world turn upside down when a strange little creature, called kwawmi's, ask them to help safe their friends or all of Paris will be in trouble. Now they have to live their every day lives while struggling to keep their identities safe and also finding out who it is causing all these troubles.

## Characters

 **Alana Agreste** | Owns the Fox Miraculous and together with Trixx, she transforms into Rena Rose

## External Links

* Official Wiki
* Instagram
* GlitterSparks
* MarsMagic
Cartoon All Stars To The Rescue The Movie 2: Goes To Mars (2014)

Cartoon All Stars To The Rescue The Movie 2: Goes To Mars Has Been Released In October 9th, 2014.And That DVD Has Been Released In January 1st, 2015.

## Synopsis

The Baby Has Been Coming To Mars, But The 9 Cartoons Is Going To Rescue The Baby From Mars And Meet Girl Black Circle.

## Cast

Harley Bird As Peppa Pig

Oliver And Alice May As George Pig

Tom Kenny As Spongebob Squarepants

Bill Fagerbakke As Patrick Star

Peter Browngardt As Uncle Grandpa

Eric Bauza As Belly Bag

Billy West as Ren Hoek and Stimpy

Kevin Michael Richardson As Mr. Gus

Adam Devine As Pizza Steve

Jack McBrayer As Wander

And April Winchell As Sylvia

## Cartoon All Stars

The characters, from different franchises are:

* Spongebob Squarepants And Patrick Star
* Peppa Pig: Peppa Pig And George Pig
* The Ren And Stimpy Show: Ren And Stimpy
* Wander Over Yonder: Wander And Sylvia
* Uncle Grandpa: Uncle Grandpa, Pizza Steve And Mr. Gus

## ​International Releases

* United Kingdom - October 10th, 2014
* German - May 5th, 2015
* Asia- April 30th, 2015
* Bulgarian - April 26th, 2015
* Icelandic - April 5th, 2015
* Norwegian - March 27th, 2015
* Australia - March 23th, 2015
* Polish - March 18th, 2015
* Hebrew - March 5th, 2015
* Hungarian - February 19th, 2015
* Brazilian Portuguese - February 6th, 2015
* Finnish - February 1st, 2015
* Dutch - January 29th, 2015
* Swedish - January 19th, 2015
* Russian - December 29th, 2014
* Danish - December 16th, 2014
* Italian - December 12th, 2014
* Czech - December 6th, 2014
* Japanese - December 1st, 2014
* French - November 21st, 2014
* Spanish - November 3rd, 2014
Cache hierarchy

**Main article**: https://en.wikipedia.org/wiki/Cache\_hierarchy

1. A "human" example of a cache hierarchy is: internet > human brain > working memory
2. mental models usually reside in a relatively high cache hierarchy
3. cache hierarchies → context switching
	1. different tasks that are brought up a higher cache hierarchy might require other components (from lower cache hierarchies) as well (that might have to be brought up a higher cache hierarchy as well), which increases computational/time complexity
4. construal level theory → cache hierarchy
	1. usually, the higher the cache hierarchy, the higher the CLT
		1. it's also usually more optimal this way e.g. metacognition (higher-level construal) above cognition (**see also**: adaptive replacement cache)

## Utilizes

1. "pooling (ANN)"
2. compactification (physics)

## References

1. ↑ Algorithms to Live By: The Computer Science of Human Decisions, p. 129–130
Joey

Joey is a famous celebrity in the AumSum universe. He is potrayed as a famous actor who hosts live stages and act in movies.

## Physical appearance

Joey is a white man with orange hair. He is dressed in a red shirt, blue jacket, and black jeans.

## Personality

As a famous actor, he mostly plays roles in films and plays. As he is famous, he is shown to be a happy, free-spirited, and energetic man.

## Appearances

* What if Parking Lots Disappeared? (Name debut)
* What is Oscars Disappeared?
* What if The Rock (Dwayne Johnson) Disappeared?
Self-determination theory and learning

## The Problem With Being Performance-Oriented: Focusing Too Much on Grades

Another thing that undermines students’ learning efficiency is being too performance-oriented i.e. focusing too much on grades.

> Too Smart to Fail?
>
>

Why does focusing too much on one’s grade result in worse learning? Because learning no longer becomes **intrinsically rewarding.**
According to Wikipedia:

> Intrinsic motivation refers to initiating an activity for its own sake because it is interesting and satisfying in itself, as opposed to doing an activity to obtain an external goal (extrinsic motivation).
>
>

Essentially, research says that by adding an **external reward**, task-performance decreases. This, however, only accounts for **cognitive** tasks, and making homework and learning pretty much are cognitive tasks:

Lastly, tasks that are intrinsically rewarding usually **give energy** while tasks that don’t immediately (or within a short time) give their extrinsic reward **take energy.** One, then, can imagine how students try to minimize their energy output which, again, leads to worse performance. You can imagine this concept like how some people feel like they have more energy left than before going into the gym, while others feel like they have less energy left.

Now, it is of course not possible to remove the grade system even though, in my personal opinion, education focuses way too much on standardized testing.

## Learning based on curiosity

I actually learn very intuitively, whenever I feel like I am learning a lot, I will continue reading or listening to whatever gives me the information. I do, however, try to invoke a feeling of curiosity and then continue learning, but if that feeling keeps fading away no matter how hard I try to spark that feeling, then I will just stop.

It is only recently that I learned how important the feeling of curiosity is during learning, how that feeling can accelerate learning tremendously. I recommend these articles on research about curiosity enhancing learning:

https://www.sciencedaily.com/releases/2014/10/141002123631.htm — *How curiosity changes the brain to enhance learning*

And this one going extremely in-depth: https://supermemo.guru/wiki/Pleasure\_of\_learning — *Pleasure of learning, SuperMemo Guru*
Nootropics (smart drugs)

I also tend to use certain smart drugs not only to enhance my learning and creativity, but also to give me energy throughout the day, and enhance my gym workouts. The stuff I really like foremost is creatine. This substance seems to be really well researched to enhance muscle growth, energy, and even cognitive power.

Another smart drug that I tend to use, that maybe is less well researched, is aniracetam. This one seems to really enhance your creativity, learning, and memory, but also appears to be anxiolytic (to a certain extent). I have a lot of anxieties and this one certainly prevents me from bursting out in tears randomly in a supermarket.

I am thinking of trying out other smart drugs soon, with my particular interest on phenylpiracetam (which is apparently banned from use in sports competition) and adrafinil. I don’t care if it’s unethical or immoral, whatever works, works.
Animation errors

Every mistake ever.

Video Links: https://youtu.be/907f1vOp1UI | https://youtu.be/EmegVUctMgg

Playlist: https://www.youtube.com/playlist?list=PLQaHemounmYXSmUq-4uOgl6LWHijxx4dT

arm and leg not attacharm and leg not attach to bodyArms not attach to bodyasset of tv not workingcoloring hand not finishedtrivia mistakes not attach arm and legtrivia mistakes not attachtwo arms and leg not attach to body!Why arm to his headWhy arms and legs not attachWhy body shrink and head is big and Why hands are same is big and little legsWhy arms and legs not attachWhy hands are bigWhy head movingWhy leg is grayWhy there leg in spaceArm not connecting to body Why arm in HeadTrivia Mistakes 3Why Arm not connecting to body Why arm in HeadWhy Head are movingWhy is transformWhy neck shorterAumSum arm are missing - CopyWhy Hand is behidWhy is thumb behidAumSum move behid thumbAumSum Arm behidAumSum arm missingOne Arm AumSumWhy AumSum arm not attach to bodyWhy AumSum Arm behid bodyWhy head moving to armTrivia Mistakes 4cattles and chicken transform backgroundWhy AumSum Shoe is grayAumSum had no handsAumSum Arm MistakesAumSum in JungleMonkey arm not to bodyA Flying MonkeyMonkey arms and leg not attachAumSum Dog Hand Not Attach to ArmAumSum Hand On Camera Not Attach To ArmAumSum See AnimalsWhy Dog Changeing Color TailWhy AumSum Hands GrayTrivia Mistakes 5Monkey Tail MistakeDog Behind gorillaTrivia Mistakes 6Lion no limbsTrivia Mistakes 7He No NoseWhy Guy Had No NoseNo Nose!Why He had Nose DisappearedAumSum Trivia 8 MistakesGuy No NoseAumSum Trivia 9 MistakesGuy Neck ShorterWhy Arm Not Attach Why Head Shorter NeckArm Not Connecting to bodyWhy Arm to NeckHe One Leg ShorterWhy AumSum Had Large EyeAumSum Trivia 10 MistakesNo Mouth!Arm to HeadAumSum Trivia 12 MistakesDog Light Brown Back DisappearedAumSum Trivia 13 MistakesAumSum Trivia 14 MistakesAumSum Trivia 15 MistakesAumSum Trivia 16 MistakesAumSum PowerAumSum Trivia 18 MistakesAumSum Trivia 18 MistakesLeg Not Attach to BodyAumSum Trivia 19 MistakesAumSum Trivia 20 MistakesArm MissingArm Mistakes in NeckMistakesAumSum Trivia 21 MistakesOne Leg MissingAumSum Trivia 22 MistakesAumSum Trivia 23 MistakesAumSum Trivia 24 MistakesNo EyeBrowsAumSum Trivia 30 MistakesAumSum Trivia 31 MistakesAumSum Trivia 32 MistakesAumSum Trivia 33 MistakesAumSum Trivia 34 MistakesWhy AumSum Hair Turn GrayHand Turn Gray AumSum AgainAumSum Trivia 29 MistakesAumSum Trivia 28 MistakesAumSum Trivia 35 MistakesAumSum Trivia 36 MistakesAumSum Trivia 39 MistakesAumSum Trivia 40 MistakesAumSum Trivia 42 MistakesAumSum Trivia 43 MistakesAumSum Trivia 50 MistakesFlowers Not DisappearedOther Flower Not DisappearedNose in FlowerNo Nose AgainWhy EyeBrow GrayAumSum Trivia 53 MistakesHand turn Gray Again AgainNo Nose Again AgainHow Many MistakesNo Nose MistakesTube DisappearedIt DisappearedRight Arm MissingAumSum Trivia 54 MistakesAumSum Trivia 55 MistakesMany Peoples ArmLessFlying LandAumSum Head MovingAumSum Trivia 56 MistakesAumSum No ArmOne Missing ArmAumSum Trivia 57 MistakesAumSum Trivia 58 MistakesAumSum Trivia 59 Mistakesno arms.
Mental exercises and learning

## Mindfulness

I do certain exercises that seems to improve cognitive power. Mindfulness appears to cause gray matter neurogenesis in the hippocampus, see this article for more information: https://news.harvard.edu/gazette/story/2011/01/eight-weeks-to-a-better-brain/ — Eight weeks to a better brain

## Wakeful resting

Another thing I do is so-called ‘wakeful resting’, placing yourself in a sensory-deprived environment and simply ‘doing nothing’, or at least, your conscious mind / focused mode is doing nothing, a lot is still running in the background, namely your subconsciousness or diffuse mode. This exercise appears to be so powerful that it increases retention with a whopping 40% after a week. These things really start to make sense when you read this article and book:

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0109542 — Boosting Long-Term Memory via Wakeful Rest: Intentional Rehearsal Is Not Necessary, Consolidation Is Sufficient

A Mind for Numbers: How to Excel at Math and Science (Even If You Flunked Algebra) by Barbara Oakley
Memory

## Possible advantages of "natural" forgetting (as opposed to a perfect memory)

1. A perfect memory would have to manually remove memories to keep things more organized (and reducing e.g. search time), which requires energy and time *itself*.
	1. cache hierarchies → organization ⇒ if organization has to be regulated from higher cache hierarchies, it might require more resources (e.g. energy) due to a disproportional increase in resources → higher cache hierarchies usually have fewer slots

### Flat vs. adaptive forgetting rate

If (in the future) one is able to choose one's forgetting rate, care must be taken to find the optimum between a standardized flat forgetting rate and an adaptive forgetting rate that's based on e.g. estimated future utilization. The latter, which might require more time and energy (trade-off).

The problem might be not one of storage, but of organization.

The mind has essentially infinite capacity for memories, but we have only a finite amount of time in which to search for them.

### See also

1. How can one decide what cards to suspend? (Anki)

## Size

1. the more memories, the more difficult it becomes to retrieve some (usually)
	1. things that can speed it up (**see also**: Algorithms to Live By: The Computer Science of Human Decisions, p. 107):
		* myelination (via e.g. SRS)
		* organization (e.g. decreasing semantic distances)
		* compressing memories (e.g. decreasing complexity of synaptic patterns)

## Procedural memory

1. Suddenly forgetting something you do everyday is related to procedural memory.
	1. E.g. tying shoes
	2. It also means that when we do have a failure, we really don’t know how to deal with it. A conscious mental search is not going to retrieve the needed information, because the information we want is not in our accessible database.
2. Procedural memory → subconscious (implicit memory)

# References

1. ↑ Algorithms to Live By: The Computer Science of Human Decisions, p. 107
2. ↑ Algorithms to Live By: The Computer Science of Human Decisions, p. 107
3. ↑ http://www.mempowered.com/problems/forgetting-skill
Compactification

From: Compactification (physics) - Wikipedia

## Pretraining Data Set Size ↔ Relative Performance

1. Figure 1: Overall learning curves for the four probing methods. For each method, we compute overall performance for each RoBERTa model tested as the macro average over sub-task’s performance after normalization. **We fit a logistic curve which we scale to have a maximum value of 1.**
	1. Is analogous to "compactification".
2. At around ~10k spaced repetition items, I started to notice the concept network growing on its own e.g. learning new things via concepts already stored 99% of the time or combining concepts.
	1. No longer requiring (as much) activation energy.

## References

1. ↑ https://github.com/nyu-mll/pretraining-learning-curves/blob/main/When%20Do%20You%20Need%20Billions%20of%20Words%20of%20Pretraining%20Data.pdf
2. ↑ https://fs.blog/2017/06/activation-energy/
Overlearning

**Overlearning** is characterized by **low return on investment** (**ROI**). An example of when applying this definition is solving the same **type** of math problems over and over again within a short **relative** time period.

What do we mean by “relative”? If you are **new** at math or a certain branch of math, “relative” in an overlearning- and time-sense could mean solving the same type of math problems within an hour (they can differ, but still belong to the same “type” or “branch” in math). As one becomes better at the same branch of math, however, “relative” in terms of time and overlearning **becomes longer** i.e. that hour now “becomes” a week. It is similar, and caused by, the spaced repetition effect.

So if you learned how to solve the problem 1+1 a day ago, it is **less likely** that solving the same “type” of problem such as 3+2 **two days** later will constitute as overlearning, than if you solve similar problems one day later. Leaving too much time between each repetition, however, and you will forget more than you are learning, and may end up not being able to solve the same math problems anymore. So the art is finding the right timings: not too less, not too much.

Second, overlearning is characterized by a very short forgetting curve, because of massed repetition.

If you forget 50% of the recently acquired knowledge within 1 week, then one can imagine how you will forget a lot more “items” if you learn 200 (foreign) words in an hour as opposed to only 100 words.

Third, there is this so-called Einstellung effect, which says that we can get “stuck” at using the same methods of solution, that may or may not work, but are less efficient. See the Luchins water jar experiment for an example of the Einstellung effect.

So how do we avoid the Einstellung effect? By backing off, letting our subconscious take over, and allowing more room for (new) neural circuits to form that are more efficient.
Context switch

1. context switch → computational complexity
	1. "context switch" is generally heavily computationally complex

## Related

1. preemption (computing)
2. Cache hierarchy → e.g. long-term memory is sometimes resumed later (moved to a higher cache hierarchy (temporarily))

1. ↑ Algorithms to Live By: The Computer Science of Human Decisions, p. 127
Main components of learning

There are essentially three components when it comes to learning new things:

> Cognition, metacognition, and motivation
>
>

Let’s review their definitions one by one as well as how to make improvements in each component.

## Cognition

Cognition is your ability to solve things. You could have high cognition for mathematics but not for music for example.

Cognition can be improved through exercise, meditation or mindfulness, good nutrition, and so on:

My Learning Trajectory, Chapter Two: Things That Increase The Quality of My Learning

## Metacognition

This one is commonly defined as “thinking about thinking” i.e. analyzing your own cognition.

If you don’t “naturally” possess a certain degree of cognition, this is the one you should focus on to improve:

People who learn how to learn can outperform those with very high IQs. Much of it comes down to “metacognition,” paying close attention to how you are thinking, writes Center for American Progress’ Ulrich Boser.

Or this quote showing the importance of metacognition:

I recommend reading the Wikipedia article on metacognition, and especially its components (metacognitive knowledge, regulation, experiences etc.) to understand how to make improvements in each component:

https://en.wikipedia.org/wiki/Metacognition#Components

A second important component of metacognition is metamemory i.e. knowing how your memory works and how to improve it. This can be done via techniques like the method of loci:

### Are Metacognitive Skills Domain-Specific?

from Wikipedia:

> There is no distinction between domain-general and domain-specific metacognitive skills. This means that metacognitive skills are domain-general in nature and there are no specific skills for certain subject areas. The metacognitive skills that are used to review an essay are the same as those that are used to verify an answer to a math question.
>
>

## Motivation

The last important component of learning is motivation. It doesn’t matter how good your cognition or metacognition is if you don’t have the motivation to learn at all.

(There does seem to be a positive correlation between metacognition and motivation, namely that those with better metacognitive skills learn things more easily and thus are more motivated to learn more).

Changing your environment in such a way that it promotes motivation to learn is much more effective than trying to fight and combat your “laziness”:

Why Willpower Doesn’t Work

You can imagine how it’s difficult to make homework with your phone next to you while receiving hundreds of text messages. Trying to combat that via willpower doesn’t work. Instead, just placing your phone elsewhere is much more effective. Read the article linked above to find out more behind this concept.
Spaced repetition

## Repetition suppression

### Spaced repetition → repetition suppression

A (too) short interval might induce repetition suppression and possibly reduce levels-of-processing effect.

Contradiction? → there exists a negative correlation between IQ and neural activity (i.e. during learning tasks) → compensation for better "hardware"?

## Spaced Repetition Software

### Anki

1. What could be more effective than reading the whole note?
	1. Trying to recall the whole note.
2. How could it be a good phenomenon to add something to Anki that's "obvious"?
	1. Probably higher intervals.
	2. Could aid to the proof that you already know the elements well required for understanding it

### Other

1. more successful students tend to have a lower relative retention percentage (SRS)
	1. The interpretation of this paradoxical finding is that good students are by far more critical in the judgment of their own progress.

## Images → spaced repetition

1. Adding images to items can help with ordering knowledge (and make you feel like you haven't learned nothing)

### e-learning (theory)

1. Improving germane cognitive load (encoding and decoding of memories)

1. ↑ https://supermemo.guru/wiki/IQ\_is\_a\_dismal\_measure\_of\_intelligence#Intelligence\_cannot\_be\_separated\_from\_knowledge:~:text=However%2C%20the%20true%20intelligence%20of%20computers%20is%20in%20their%20software
2. ↑ http://www.super-memory.com/english/ol/analysis30.htm
Cognitive reserve

1. how could "cognitive reserve" work?
	1. higher probability of remembering higher-priority items?
		1. e.g. when seeing the word "bank" your brain could activate both "money bank" and "beach bank" → higher probability of maintaining "money bank" after cognitive reserve reduced and less real-life impairments?

# References

1. ↑ Consciousness and the Brain: Deciphering How the Brain Codes Our Thoughts
Miko Iino

**Miko Iino** is the fifth member of the student council.

## Personality

Miko is serious, well-behaved girl who hates bullies. She has a sense a justice and always wants to justify anyone who did something wrong. She's also timid when someone bullied her and often hides herself in the restroom and cries. Miko also loves to eat. She has once eaten all of Kaguya's and Shirogane's fried rice.

## Relationships

### Gabriel

Desppite being voiced by the same VA, Gabriel despises Miko because Gabriel had enough of VA association, since there are already four character to be voiced by Miyu Tomita. Gabriel often bullies her and beats her up with her trumpet. Miko's personlity also made their conflict worsen. However in near end of Season 3, their conflict has been toned down.

### Maika Sakuranomiya

Maika seems to dislike Miko, as she has same hairstyle with her. Maika also dislikes Miko's personality as well.

## Trivia

* Miko is the fourth character to be voiced by Miyu Tomita, the others being Gabriel, Sophie Twilight and Crimvael.
	+ Out of the four, she's the only one to be a human.
	+ She's the first and currently only one in the group that Gabriel does not get along with. However, she later has better friendship with Gabriel.
* Miko has similar hairstyle with Maika's, except she has brown hair rather than black.
Optimizing Studying for 5 Week Class

16/07/2020 21:19

I think it somewhat depends on what you want your workload to be.

If you don't care how long you want to do Anki each day, just do your note-taking in Anki and create as many as possible. Suspend (don't delete, you might need them later) those that you think you don't need and recreate cards while reviewing them (rather than trying to create the perfect cards first try).

Here's a nice article how to formulate your knowledge (e.g. cards):

Effective learning: Twenty rules of formulating knowledge

It's written by Dr. Piotr Wozniak, the creator of SuperMemo which is the precursor of Anki.

I personally think you should make questions instead of clozing / copying things without much thought. It forces you to think questions like:

1. What do I want to know?
2. What do I have to know?
3. What is the probability this question will appear in a test? (the higher, the better)

...while also reducing workload.

Don't use basic cards. Every basic card can essentially be turned into a clozed card, which can be modified much more easily later on (e.g. adding / removing clozes of the same card).

If you are interested, I recently made a comment about effective study techniques that I personally use:

What are some study techniques which I could use?

For Anki addons to reduce workload and increase learning efficiency, I suggest the following:

Anki Killstreaks (for motivation)

Autosync 2.1 (to not accidently lose your data)

Load balancer (to reduce workload)

These are all my other addons (mostly optional for small gains):

https://photos.app.goo.gl/8xVWD1tRpsuVEXjE6

Source: https://www.reddit.com/r/GetStudying/comments/hsegxw/optimizing\_studying\_for\_5\_week\_class/fya6p81?utm\_source=share&utm\_medium=web2x
The First Trumpet of Apocalypse

**The First Trumpet of Apocalypse** is Gabriel's trademark weapon. It often appears in original Gabriel DropOut.

## Appearance

The First Trumpet of Apocalypse looks nothing like an ordinary trumpet. It, however resemble a horn.

## Usage

As its name implies, it's the trumpet that can destroy the entire world when played. In the fan-made series, Gabriel uses it as a battering weapon. If Gabriel's nearly dead, the trumpet is the last resort.

## In Original Gabriel DropOut

When Gabriel is angered, crazy or terrified. She will take it out and attempt to play it, but she will always give up.

## Trivia

* If not counting two Isekai genre episodes, this is one of the only weapons that never properly used. If properly used, the series will immediately ends.
Procrastination

## This Will Make You a More Productive Procrastinator

Now, the title sounds a little bit ironic, namely the part about “Doing other stuff”, but I am dead serious.

It has been shown by research that just *thinking* about an activity you don’t want to do raises the activity in the insular cortex, a brain region involved in pain.

Now, in order to use procrastination in our advantage, we can try to set up a less “painful” task that is still productive. Instead of procrastinating and doing nothing productive, now we at least do something productive.

A very simple example of mine revolves around writing and reading. I like to write and read, but I absolutely dread to **start** such a process. Writing, however, seems to be more “dreadful” than reading, probably because it requires a lot more thinking and energy. So what do I do? I allow myself to procrastinate by doing something else: reading. Maybe not exactly what I have planned, but it’s still productive.

Again to clarify, starting a process usually is the most “painful” part. After a minute or so, the pain usually goes away.

> What are some things giving you the feeling of procrastination? And how can you use that to your advantage to do something else that’s also productive?
>
>

## Related

1. "procrastination" is related to "DDoS"
	1. Putting off work on a major project by attending instead to various trivial matters can likewise be seen as “the hastening of subgoal completion”—which is another way of saying that procrastinators are acting (optimally!) to reduce as quickly as possible the number of outstanding tasks on their minds. It’s not that they have a bad strategy for getting things done; they have a great strategy for the wrong metric.

1. ↑ Algorithms to Live By: The Computer Science of Human Decisions, p. 120
Superintelligence Wiki

**Welcome to the Superintelligence Wiki!**This Wikia is based on the idea that intelligence can be increased, as is the case with the following trying to formulize intelligence:
### F = T ∇ Sτ

Eclipse and Java Blog by Michael Scharf: A new Equation for Intelligence F = T ∇ Sτ - a Force that Maximises the Future Freedom of Action

Causal Entropic Forces

Suggested read (as well as his site): [- supermemo.guru]

## To-do pages

1. Self-Reflection: How To Make It More Effective
Reflection

It was a really simple yet thought-provoking way of defining “reflection” that I read on the internet.

The article, which I can’t find anymore, didn’t really *reflect* further on their definition of reflection.

They just noted it down and moved on with the subject about metacognition. Perhaps it was a that simple definition.

Enough talking, this is their definition that I can recall:

> **Reflection means: Bringing experience and theory together.**
>
>

Really that simple yet thought-provoking (at least for me).

So go ahead and recall an experience you had. Now, reflect on it by consciously trying to bring theory into that experience i.e. the main principles, rules, mental models, etc.
Learning compression score

> **Learning compression score = Quality / Size reduction**
>
>

### Calculating Learning Compression Score

This method, which I will call “Learning compression score”, is a (futuristic) method that I can imagine will accelerate learning.

Essentially, this “score” says how efficiently you learn things from a particular source in terms of time e.g. two similar articles may talk about the same idea, but one of them explains it in half the time required to read it.

So how can we “calculate” the compression score of a source? Let’s say you are aware of a book containing 70,000 words but, instead, there’s an article summarizing the book in only 1,000 words. In other words, the source has been compressed by ~99%. This, however, is just a component for calculating the learning compression score.

In order to calculate the compression score, we have to “calculate” how much (subjective) “quality” we have retained from the original source. Often, the quality goes down when summarizing sources, but in rare cases, it might even go up.

Let’s say we have retained 80% of the “quality”. Now, in order to calculate the compression score, we have to divide 0.8 with 0.01 = 80.

> This number essentially means that every second you spend on reading the summary, you learn things 80x faster than when reading the original source.
>
>

### Futuristic Method To Enhance Learning?

I think we can become more and more precise and efficient in calculating things like how much calories, proteins, and vitamins certain food contains. In fact, we might even be able to do such things in the future via brain augmentation by simply staring at food.

Perhaps it might even be possible to calculate more precisely how valuable and efficient a certain source would be to read for us. I mean, we already are doing that (subconsciously) based on our feelings of curiosity, joy, and so on.
Learning session

**Notice:** This article is being worked on incrementally.

## Pomodoro technique

Most people are probably familiar with the Pomodoro technique: A learning session of approximately 25 minutes followed by a 5 minute break, and so on.

The main idea why that works so well, is that by being process-oriented (i.e. time-based) is much more effective than being goal-oriented (e.g. I have to finish at least 10 pages).

Why? Because saying to yourself “I will study for 25 minutes” seems to increase the activity in the insular cortex less than saying “I have to finish at least 2 pages of homework”.

The insular cortex seems to be involved in pain i.e. saying “I have to finish at least 2 pages” causes more “pain”. Again, that’s why the Pomodoro technique is so effective.

## Items-dependent learning sessions

If you use particular spaced repetition software like Quizlet, Anki, or SuperMemo, this method will especially become effective.

It’s really simple:

> **You keep studying until you have at least X “items” (e.g. 30)**
>
>

What do I mean with “items”? Simply the quantity of (flash)cards like these:

1. **Question:** Where is spatial working memory located?
**Answer:** Thought to be in the dorsolateral prefrontal cortex.
2. **Question:** Where is non-spatial working memory located?
**Answer:** Thought to be in the ventrolateral prefrontal cortex.

In this example, we have 2 different flashcards i.e. 2 items. I also recommend reading this article by SuperMemo for effectively formulating your flashcards to maximize learning:

Effective learning: Twenty rules of formulating knowledge

### Reasoning Behind Effectiveness of Items-Dependent Learning

Why do I think this method is more effective than time-based learning? Because the quantity of items you learn or get exposed to within X time differs. The introduction of some Wikipedia articles are sometimes enough for 20 items within 10 minutes, while other sources are less information dense.

Personally, I like to limit myself to a maximum of 30 items per source. Once I got and memorized my 30 items, I will move on to a different source (interleaved practice) after a short break (approximately 10 minutes).

As an example, 30 items over 3 different sources, 90 a day, makes it quickly jump up to 33k items per year if everything goes alright.

**One should definitely not underestimate long-term (compounding) growth!**
Planned redundancy

A thing I do when learning new things is to invent multiple questions (or cloze deletions) about the same concept. This increases the probability of recall in any given (real life) situation. By “attacking” the same concept from different angles, I increase the amount of cues (synaptic pattern extractions) leading to the activation of the same concept i.e. retrieval strength (the other component is storage strength). Dr. Piotr Woźniak calls this “planned redundancy”.
Emilia

Emilia is an half elf in Re:Zero − Starting Life in Another World. She first appears in Season 4. She's Aqua's good friend.

## Emilia

### Appearance

Re:Zero − Starting Life in Another World (episode)

## Appearance

Emilia has silver long hair and purple eyes. She also has two pointed ears like and elf.

## History

### Gabriel DropKiss

Crimvael jokingly replies to Gabriel that Crim loves Emilia in the end of the Season 3, confusing Gabriel.

### Re:Zero − Starting Life in Another World

After Gabriel unknowingly enter a strange world, she was attacked by some rogues. Emilia showed up and "saved" Gabriel.

## Trivia

* Again, the Isekai world has been destroyed by Gabriel, making Emilia hold grudge against her.
Quotes related to intelligence

“If you want to think like a genius, you first have to LEARN like a genius.” — Superintelligence Wikia creator

“Actively self-reflecting on the approaches that you are taking fosters a strategic stance that is really important in life. Strategic thinking distinguishes between people of comparable ability and effort. This can make the difference between people who achieve and people who have the potential to achieve, but don’t.” — Patricia Chen.
Construal level theory

## Applying Construal Level Theory to Enhance Learning

> How to learn faster and easier while promoting creativity
>
>

From Wikipedia:

> **Construal level theory** (**CLT**) is a theory in social psychology that describes the relation between psychological distance and the extent to which people’s thinking (e.g., about objects and events) is abstract or concrete.
>
>

Now, what the Wikipedia article doesn't teach you, is that this theory can be perfectly used to learn faster **and** promote creativity in a top-down kind-of-approach.

The "levels" in CTL are essentially divided into two categories: low and high level construal. Let's review some examples of each.

### Low-Level Construal

This one is characterized by focusing on **concrete details** of a particular event, object, concept, etc.

Thinking about the **type** and **brand** of phone you want to buy is an example of low-level construal.

A general characteristic of low-level construals, is that they cover, link to, etc. to **less** other concepts e.g. the concept "Samsung phone" only covers and links to other phones of the same brand, Samsung.

### High-Level Construal

This one, on the other hand, is characterized by focusing on the **big and abstract picture**.

The concept of "phone" is an example of a high-level construal in comparison to the concept "Samsung phone".

The general characteristic of high-level construals, then, is that they cover and link to **more** other concepts e.g. the concept "phone" covers all kinds of brands "Samsung", "Huawei", "Sony", etc.

### High-Level > Low-Level Construal

In order to enhance one's learning and creativity, it is best to start learning a source by understanding the **big and abstract picture** first before the concrete details.

You can, for example, try to understand the introduction and summary of a book first before digging yourself in every page. SuperMemo creator Piotr Woźniak applies this concept to incremental learning.

One can imagine how learning the concept of "phone" is a lot more applicable to other things **and** speeds up your learning when engaging in low-level construal learning e.g. "Samsung phone".

It is much easier to learn knowledge that you can relate to other knowledge you already know well (semantic learning) than it is to enter a completely unknown branch of learning.

Now that I have taught you the concept of construal level theory in a "high-level construal" manner, I invite you to proceed in a "low-level construal" manner by reading the Wikipedia article:

Construal level theory, Wikipedia
Algorithms

Algorithms can be used to improve your software (e.g. metacognition).

## Bucket sort

### Bucket sort → explore/exploit tradeoff

The beginning stages are more analogous to explore and the (optional) following iterations are more analogous to exploit.

#### Intraclass correlation

Can be faster/sped-up via e.g. merge sort/bucket sort?

## Comparison sort

Comparison sort is related to "ordinal scale".

## Algorithmic efficiency

### Noise

1. The less noise increases loss, the more efficient.
2. The more it can make use of noise, the more efficient.
	1. (Analogs) Neuronal/Synaptic noise.

### Computer performance

1. A higher algorithmic efficiency would lead to a higher computer performance.

### Metacognition

1. Metacognition is an example of increasing algorithmic efficiency.

### Degrees of separation

1. A lower degrees of separation could lead to a higher algorithmic efficiency.

### Learning rate

1. A higher algorithmic efficiency would lead to a higher learning rate e.g. less steps per iteration.

### Cognitive load

1. A higher algorithmic efficiency would lead to one or a combination of:
	1. Extraneous cognitive load requires less neural resources (per unit/on average) e.g. better filtering;
	2. Less steps per iteration could lead to a lower intrinsic cognitive load;
	3. Less neural resources required for germane cognitive load (e.g. encoding/decoding long-term memories) e.g. less semantic distances.

## References

1. ↑ https://supermemo.guru/wiki/IQ\_is\_a\_dismal\_measure\_of\_intelligence#Intelligence\_cannot\_be\_separated\_from\_knowledge:~:text=However%2C%20the%20true%20intelligence%20of%20computers%20is%20in%20their%20software.
2. ↑ https://en.wikipedia.org/wiki/Bucket\_sort
3. ↑ https://en.wikipedia.org/wiki/Multi-armed\_bandit
4. ↑ https://en.wikipedia.org/wiki/Intraclass\_correlation
Learning formula

Have you ever thought about a simple formula you can always rely on to **maximize** your learning?

I have and according to me, it’s as simple as follows:

> Learning = Knowledge Acquisition Rate - Rate of Forgetting
>
>

> Where priority of Rate of Forgetting > Knowledge Acquisition Rate
>
>

### Knowledge Acquisition Rate

Simply said, knowledge acquisition rate is the speed at which you acquire new knowledge. This can be measured in various ways, but I personally like to measure it according to “items per time” e.g. 10 items per hour.

You can simply hold account of these items in all kinds of programs like Anki or Quizlet.

Maximizing the knowledge acquisition rate can be done through various ways, like reading a good high-rated non-fiction book. Or my favorite: Wikipedia seems to usually contain the most dense and compact forms of knowledge.

You can usually also sense and feel whether the knowledge acquisition rate is high or not.

### Rate of Forgetting

Now, it doesn’t matter how high your knowledge acquisition rate is if you forget everything within a week. This is why I added a second part to the learning formula: **rate of forgetting.**

This simply means how many items you forget per time, usually denoted in percentages for simplicity and practicability e.g. forgetting 50% of the acquired knowledge from 7 days ago.

Minimizing the rate of forgetting can be done through spaced repetition.

### Priority of Rate of Forgetting > Knowledge Acquisition Rate

The last part of the formula is giving the rate of forgetting a higher priority than the knowledge acquisition rate. Why? Because it’s more efficient to do so thanks to the spaced repetition effect i.e. acts of revision should be spaced in gradually increasing intervals, roughly intervals of one day, two days, four days, eight days, and so on.

One can imagine, then, how this requires less and less time and energy the more acts of revision have already taken place. This, in contrast to the knowledge acquisition rate that doesn’t necessarily grow exponentially in terms of efficiency.

Simply said, if you have limited time and have to choose between an act of revision through programs like Quizlet or reading a book, choose for spaced repetition.

### You Don’t Have To Choose When Combining Both

Now, it is possible to create a situation where you don’t have to choose between “spaced repetition” and “acquiring new knowledge”.

For example, if you previously read a book about metacognition or learning how to learn, and you now decide to read the Wikipedia page on metacognition, you are essentially applying both spaced repetition and acquiring new knowledge.
Formula To Calculate a Knowledge's Worth

What is a possible metric one can use to estimate the value of particular information or knowledge? I personally believe, if nothing else is known (see principle of indifference), it should be based on time, hence the following formula:

> Value of Knowledge = Time Utilized/Time Spent Learning
>
>

E.g. if you spend 1 hour learning something and only use it for another hour in your whole life, the value of that knowledge = 1.

If you learn a new habit that took you 100 hours to learn, yet you use it every day (let's say 1 hour a day), then over a span of 5 years its value = 43800/100 = 438!

Another well-known example is how many modern students/people tend to learn stuff that they may never use in their life. But let's say they learn a bunch of stuff they only use for a total of 1 hour in a span of 1 year and it also took them 0.5 hours to learn each of that knowledge. This would give us a value of "2" (1/0.5) accumulating every day.

In a span of 1 year, their pool of knowledge at the end of that year would equal 2x365 = 730.

Now, let's say you choose to learn somewhat more relevant knowledge you use for 1 hour every week (52 per year) and also takes you 0.5 hours to learn (value = 104/year). In order to beat the value of their knowledge, you'd only need to learn 7 things as opposed to their 365! (730/104) E.g. learning 7 new habits (as opposed to random knowledge).

Again, because nothing else or nothing much is really known (beforehand) determining a knowledge's value, we base it on time (again, see principle of indifference). We could also base it on money or something else. Even something subjective such as happiness. I used time for this example, however.

These examples also serve more as an insight to how big of a difference it can make to learn stuff that's more relevant.

The image is an example of how, the closer you get to "wisdom", the more you should multiply a particular knowledge's value, again stressing that value depends on much more than e.g. time.

What do you think of this? Or how do you estimate the value of something?
Metamemory

## Enhance Learning via Usage and Development of Metamemory

Metamemory, a component of metacognition, simply means the knowledge you possess of how your (or in general a human) memory works e.g. knowing the difference between short-term and long-term memory as well as knowing how to store things as long-term memories.

The problem with most students, is that they believe highlighting and rereading text causes short-term memories to become long-term memories. This is completely false, see this article:

Highlighting and rereading ineffective study methods

Instead, the best way of learning is to apply strategies like spaced repetition. Programs like Anki, SuperMemo or Quizlet are excellent tools to help with creating and maintaining long-term memories.

It is, then, advisable as a student, teacher, or anyone else to teach this concept to anyone else, and of course themselves, to enhance learning.

Other ways to make more use and develop metamemory are using mnemonics and the method of loci.

See this interesting video about a memory champion called Dominic O’Brien:

Another interesting story showing how powerful a developed metamemory can be:

> Ed Cooke, a Grand Master of Memory, graduated at the age of 22 with a first class degree in psychology and philosophy from Oxford University in 2004 and completing a Master’s degree in Cognitive Science at Paris Descartes University under the supervision of J. Kevin O’Regan in 2005. From: Ed Cooke (author), Wikipedia
>
>

Imagine that, following degrees at prestigious universities with pretty much ease thanks to a well-developed metamemory!
Bias (metacognition)

According to this research paper: Neural correlates of metacognitive ability and of feeling confident: a large-scale fMRI study, there exists a **negative** correlation between feelings of confidence on one’s task-performance and metacognitive abilities. That is, the more confident one feels about one’s task-performance, the less developed a person’s metacognitive abilities are.

Here’s a video explaining how **being underconfident can be *beneficial*:**