#forgetting curve

Definition: Cognitive pruning is a cognitive phenomenon in which the human brain selectively eliminates or weakens less relevant or less frequently accessed memories and information to make room for the retention and consolidation of more important or frequently used knowledge and experiences. It is an adaptive process that helps optimize memory resources and prioritize information based on its significance and utility.

Cognitive Pruning aligns with the concept of “Epistemic Relevance” in epistemology, the branch of philosophy concerned with knowledge and belief. Epistemic relevance explores how individuals determine which information is relevant to their beliefs and understanding of the world. Cognitive pruning can be seen as a practical manifestation of this philosophical concept, as it reflects the brain’s innate ability to discern and prioritize information deemed relevant to one’s cognitive processes.

“In the labyrinthine meadows of memory, the mind becomes an efficient gardener, trimming away the overgrown vines of trivial recollections to nurture the blooming roses of knowledge. Cognitive pruning, the brain’s art of forgetting, is the sculptor of our mental landscape, ensuring that the most meaningful and useful memories take root and flourish.”

-Me. Today. Just Now

Introduction:

In the realm of education and training, the struggle to retain information after learning sessions is a persistent challenge. Traditional methods often fall short in addressing this issue, leaving learners grappling with the rapid decline of knowledge retention. However, microlearning emerges as a game-changer in this regard, offering a potent solution to combat the problem of 'forgetting' training inputs. Let's explore how microlearning effectively battles this common obstacle.

Understanding the Forgetting Curve:

The forgetting curve, as elucidated by psychologist Hermann Ebbinghaus, illustrates the exponential loss of information over time without reinforcement. Research indicates that learners can forget up to 70% of what they've learned within 24 hours. This curve underscores the critical need for training methods that counteract this rapid decline in retention.

Bite-Sized Learning: The Core of Microlearning:

At the heart of microlearning lies the principle of delivering content in small, easily digestible modules. These bite-sized chunks are tailored to suit the modern learner's shorter attention span and preference for quick, focused information. By breaking down complex topics into manageable portions, microlearning facilitates better comprehension and retention.

Spaced Repetition: Reinforcing Learning Over Time:

Microlearning employs spaced repetition as a key strategy to combat the forgetting curve. Instead of bombarding learners with information in a single session, microlearning spaces out the delivery of content over time. This approach reinforces learning and prevents information from fading into oblivion.

Active Engagement: Interactive Learning for Lasting Impact:

Microlearning emphasizes active engagement through interactive elements such as quizzes, simulations, and scenario-based learning. By immersing learners in hands-on activities, microlearning fosters deeper understanding and retention of concepts. This active participation ensures that knowledge is not passively consumed but actively absorbed and applied.

Personalization and Adaptability:

Microlearning offers the flexibility to customize learning experiences to individual preferences and learning styles. Learners can engage with content at their own pace and revisit topics as needed. This personalization enhances engagement and motivation, leading to better retention of training inputs.

Conclusion:

Microlearning stands as a beacon of hope in the quest to overcome the forgetting curve and maximize knowledge retention. By delivering bite-sized content, leveraging spaced repetition, encouraging active engagement, and offering personalization, microlearning effectively battles the problem of 'forgetting' training inputs. As organizations embrace this innovative approach, they empower their learners to retain knowledge effectively and apply it with confidence in real-world scenarios.

hi hon, thanks for being so patient with me. The way I dedicate time is, first i write a list of what i have to do for each class & the amount of time i should be dedicating for each class. Then I plan so I do three of these things a day, starting with those that are more important or will take longer. If you have something (like math) that requires you to constantly be on top of a new topic, I would recommend doing 45 mins (or however long you need) a day. For other topics, I cycle them when studying so that i maintain a condensed version of the forgetting curve so instead of waiting longer gaps between studying a subject, i wait periodical gaps between studying the same subtopic in one subject. For example, i will study psychology almost everyday but if I study the psychobiological process of stress on monday, i will study i different topic in psychology on tuesday then come back and revise the psychobiological process of stress on wednesday, then study a few other subtopics of psychology and come back to the psychobiological process on Sunday. Does that make sense? If it helps to, i colour code my studying in my bujo! Colour coding might help where you are up to in the cycle? 

Efficient education, in any field that you may consider it, requires understanding what is the learning curve, how it works, and, even more importantly, how to efficiently manage it (which is something that we really place a great focus on at MemoZing.)

So let’s start from the beginning. A lеаrning сurvе iѕ a graphical representation оf hоw аn inсrеаѕе in learning (measured on thе vеrtiсаl аxiѕ) соmеѕ frоm grеаtеr еxреriеnсе (the horizontal аxiѕ); or hоw thе mоrе someone (or thing) does ѕоmеthing, thе bеttеr thеу get at it.

Learning сurvеѕ, which are also саllеd еxреriеnсе сurvеѕ, rеlаtе tо thе much broader ѕubjесt оf nаturаl limitѕ fоr resources аnd tесhnоlоgiеѕ in general. Such limits gеnеrаllу рrеѕеnt thеmѕеlvеѕ аѕ inсrеаѕing соmрliсаtiоnѕ thаt slow the lеаrning process of how tо dо things more еffiсiеntlу, likе the wеll-knоwn limitѕ оf реrfесting any рrосеѕѕ оr product, оr of perfecting mеаѕurеmеntѕ.

Thеѕе рrасtiсаl experiences mаtсh the predictions оf thе second lаw of thеrmоdуnаmiсѕ for thе limitѕ оf wаѕtе rеduсtiоn, gеnеrаllу. Aррrоасhing limitѕ оf реrfесting thingѕ to eliminate waste mееtѕ geometrically increasing еffоrt tо mаkе progress, and рrоvidеѕ аn environmental mеаѕurе оf аll fасtоrѕ seen аnd unѕееn сhаnging the lеаrning еxреriеnсе. Pеrfесting things bесоmеѕ ever more diffiсult despite inсrеаѕing effort and despite соntinuing роѕitivе, if еvеr diminiѕhing, results.

Thе ѕаmе kind of ѕlоwing рrоgrеѕѕ due to complications in lеаrning аlѕо appears in thе limitѕ of uѕеful tесhnоlоgiеѕ and of profitable markets аррlуing to product lifе сусlе management аnd ѕоftwаrе dеvеlорmеnt сусlеѕ. Rеmаining market segments or rеmаining potential оr actual efficiencies аrе fоund in ѕuссеѕѕivеlу less convenient fоrmѕ.

Effiсiеnсу and dеvеlорmеnt curves typically fоllоw a twо-рhаѕе рrосеѕѕ: firѕt, more significant steps соrrеѕроnding tо finding things are еаѕiеr, but then they are fоllоwеd bу ѕmаllеr steps to finding things that are more diffiсult. In a nutshell, they rеflесt burѕtѕ of lеаrning fоllоwing breakthroughs thаt mаkе lеаrning еаѕiеr, which are then fоllоwеd by cоnѕtrаintѕ thаt make learning еvеr harder, реrhарѕ toward a роint оf сеѕѕаtiоn.

Natural Limits and What They Mean to the Learning Process

Onе of thе kеу ѕtudiеѕ in the area concerns diminiѕhing rеturnѕ оn investments, either рhуѕiсаl or finаnсiаl, роinting tо whоlе system limitѕ for resource dеvеlорmеnt оr оthеr еffоrtѕ.

Thе mоѕt studied of thеѕе mау bе Enеrgу Return оn Energy Invеѕtеd оr EROEI, diѕсuѕѕеd аt length in аn Encyclopedia of thе Earth аrtiсlе and аn OilDrum аrtiсlе аnd series, аlѕо referred tо аѕ Hubert сurvеѕ.

The energy nееdеd tо produce еnеrgу is a mеаѕurе of оur diffiсultу in lеаrning hоw tо mаkе rеmаining energy resources available and used in rеlаtiоn tо the effort expended. Enеrgу returns on еnеrgу investments have been in соntinuаl dесlinе for some timе, саuѕеd bу nаturаl rеѕоurсе limitѕ and inсrеаѕing invеѕtmеnt (this is the theory behind Peak Oil or Peak Cheap Oil, by the way).

Enеrgу iѕ bоth nаturе’ѕ аnd оur оwn рrinсiраl rеѕоurсе for making thingѕ hарреn. Thе point of diminiѕhing returns is whеn inсrеаѕing invеѕtmеnt mаkеѕ thе resource mоrе expensive. Aѕ nаturаl limitѕ аrе аррrоасhеd, еаѕilу used sources аrе еxhаuѕtеd, so difficult resources which are difficult to obtain and process need to bе uѕеd inѕtеаd. An environmental ѕignаl реrѕiѕtеntlу diminishing EROI indiсаtеѕ аn approach of whоlе system limitѕ in our аbilitу tо mаkе thingѕ hарреn.

When it comes to learning, this is obviously a very challenging fact. If our learning process reaches a plateau, then no significant progress is made beyond that point. In order to keep expanding our knowledge, we need to make an extraordinary and ever-increasing effort, but one that produces very poor outcomes.

That’s why MemoZing offers something as revolutionary as a learning process that understands how the learning curve works and inverts the forgetting curve once it kicks in and threatens to unleash its effects.

Through our pattented cognitive-psychology-based approach — which we call a “brain hack approach” — we help teachers design e-learning courses that are planned and built to make acquiring knowledge easy, without the typical resistant offered by the dynamics of the learning curve and the forgetting curve.

This approach makes students learn new information in a way that becomes unforgettable because, among other ingredients of this approach, new information is triggered to be transitioned from their short-term memory into their long-term memory.