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Crossing the AI Era with Learning Science

A learning method that does not rely on AI. From developers to students and graduate students, learn how to turn your efforts into actual results through real-life coaching cases.

(5.0) 3 reviews

35 learners

Level Beginner

Course period Unlimited

AI
AI
Learning methods
Learning methods
Business Problem Solving
Business Problem Solving
AI
AI
Learning methods
Learning methods
Business Problem Solving
Business Problem Solving

What you will gain after the course

  • Deepen your learning in less time based on the science of learning.

  • Beyond simply relying on AI, actively collaborating with AI for learning.

  • Learning not just for studying for exams, but for solving complex life problems

Faster, yet more correctly

I am often asked if there are multiple versions of me. Although I was a non-major who graduated with a degree in physics, I now make a living as a web developer. I even received an award for writing the most code, faster and with fewer bugs, while using AI the least among my team members. I have also given presentations on accessibility, frontend testing, and functional programming at events such as Toss PDACL, Inflearn After-Work Meetup, and the functional programming conference LiftIO. Beyond coding, I recently attended the Department of Law at Korea National Open University and received a full scholarship.


It is true that I am trying to appeal to you. (After all, I am promoting my lecture.) Then, how was I able to learn so many things faster and more deeply?


The secret was the science of learning.


Learning science is not a mechanical memorization technique or a shortcut. It is the result of a long history of researching how ordinary people, not just geniuses, can learn better based on a scientific understanding of how our minds work.


Learning science proven through real-world coaching cases beyond mere experimentation


"Isn't it just because you're diligent? Isn't it because you're smart!" But I also struggled with ADHD, sleep disorders, and a childhood in poverty without ever attending a private academy. More importantly, this isn't just my story. Working as a coach for over six years, I have met and helped so many people.


Scientific learning methods are not just pleasant-sounding brain science theories. Learning science has transformed the lives of various people, including not only developers but also candidates for teacher certification exams, planners, and graphics designers. Learning science has been helpful to everyone. Some have moved to better companies, while others have passed their exams. But isn't the most rewarding feedback of all that they discovered the joy of studying?


"I discovered the joy of learning. And more than anything, I gained motivation! I used to be someone who lacked motivation in almost everything, but after the coaching, I became much more positive and motivated in many ways, making me want to live my life to the fullest." - Review from H


Learning methods in the era of Artificial Intelligence (AI)


Of course, some argue that in the AI era, humans no longer need to learn. They say we only need to give orders now, and design is no longer important. They claim humans don't need to memorize things or take exams anymore! It reminds me of the arguments that learning was no longer necessary because we could just search for everything.


However, even for humans to collaborate better with AI, learning is still important. This is because problem-solving skills are also developed through deep learning.


The image above is taken from the paper <How AI Impacts Skill Formation> published in 2026 by Judy Hanwen Shen and Alex Tamkin of Anthropic's Fellowship Program. Delegating everything to AI was the fastest method (19.5 minutes). However, these individuals not only showed a lower understanding of concepts but also struggled with reading or debugging the code afterward.


However, those who engaged in collaborative learning—such as asking the AI about the generated code and working together to understand the concepts—achieved high comprehension scores, and while it took slightly longer to complete, the difference was only about 3 to 4 minutes (22 to 24 minutes). This shows that even with the same AI, high levels of understanding can be achieved when humans use it as a "learning tool" through cognitive engagement.


Nevertheless, many people are swept away by false claims that AI will replace humans or that design and learning are no longer necessary in the AI era. Many still do not understand the science of learning. The market is flooded with learning method books, lectures, and apps that insist Ebbinghaus's 100-year-old forgetting curve is the latest cognitive science. Of course, even after hearing "practice retrieval" or "use spaced repetition" countless times, many people still feel lost on how to apply these to their own lives or to the AI era.


Beyond just listening to lectures, let's actually change our lives

Recently, a book titled "The Art of Stopping Learning" was also released. Your life won't change if you only learn how to learn without actually doing the learning.

In this course, the goal is to go beyond simply learning about the science of learning and actually apply it to your real-world studies. This is based on practical coaching cases ranging from coding, foreign languages, certifications, and attending lectures to reading thick books or English documents. Furthermore, rather than just relying on AI, I will show you how to collaborate with it through actual use cases and provide you with the necessary prompts.


Where will the lecture profits be used?

Lifelifter Coaching Center

The preliminary social cooperative Lifelifter is an organization formed by three coaches who want to transform the coaching industry. While coaching is highly beneficial, its high cost makes it a burden for young professionals starting their careers or vulnerable groups facing economic difficulties. On the other hand, volunteering often leads to "passion pay" for coaches, creating a contradiction as coaches also need to earn a living.


Coaching Sospeso Prepayment

Lifelifter is experimenting with a model called Coaching Sospeso. We are trying to create a structure where coaching fees are prepaid so that coaching can be provided for free to those in need, while coaches can also receive fair compensation. This leads to a virtuous cycle where those who received coaching get back on their feet and prepay the coaching fees for those who will come after them.


Coaching Sospeso allows you to designate beneficiaries. We deliver coaching to those who need support, such as "young women who are or will be caring for someone," "young 'slug' generation members worried about housing issues," and "full-time activists in non-profits and other social movements." You can read reviews on our blog.


Profit-making business

Since there isn't much pre-paid money yet, most of the operations are still running on "passion pay." Due to the ongoing job instability of the coaches, they have been facing continuous financial difficulties, which is why we have started offering lectures as a profit-making venture. The tuition fees you pay will go into Life Lifter's account and will be used as seed money for a virtuous cycle. In essence, you are making a pre-payment for someone else.


Sponsorship

Coach Taehee Kim has been providing coaching for free for the past two years without accepting any coaching fees. Any money received from those who insisted on paying was donated in full. Personal donations have also steadily increased, and she is currently donating nearly 800,000 won to various organizations. In 2025, she donated 7,735,533 won, and she wishes to continue this positive influence in 2026.


Lecture Plan

Approximately 10 hours in total planned


Section 1. Why we still learn in the AI era ✅

  1. Ordering AI to do something vs. Asking questions and collaborating

  2. AI learns common sense, not truth

  3. AI's capabilities vary depending on the context

  4. Quality still matters

  5. The areas where AI excels are uneven.

  6. In the era of AI, what am I trying to study, and why?



Section 2. From Familiarity to Novelty ✅

  1. Revisiting Metacognition

  2. Trying the metacognition scale for yourself

  3. Activating background knowledge familiar to me

  4. Humans are prediction machines - Predicting in advance

  5. Challenging yourself with things that are unfamiliar and difficult


Section 3. The Courage to Act (Upcoming)

  1. The reason why you should look for the answer key - Worked examples and demonstrations

  2. The Power of Active Retrieval

  3. "This time, I'll try getting it wrong" - Productive Failure

  4. Why don't office workers create mistake notes? - Mastery Learning

  5. Asking questions instead of giving explanations

  6. Learning Science WOOP: Writing and Imagining


Section 4. There are patterns even in a complex world (Planned)

  1. Memorizing the Table of Contents and Maps - Organization

  2. The brain loves stories, not mathematics

  3. 100 Years After Ebbinghaus - Spaced Repetition

  4. Divide and Conquer, an Idea of Human Civilization

  5. You must connect to remember - Retrieval cues

  6. Reflecting on my challenge


Section 5. Moving from Theory to Reality (Planned)

  1. Gradually reducing support - Scaffolding

  2. Why doesn't mathematical thinking transfer?

  3. How to increase your IQ - Sleep, exercise, and smartphones

  4. Surviving in a Multitasking World - Context Switching

  5. The world is diverse, so let's mix it up - Interleaving and Comparison

  6. Experimenting with and sharing my own learning methods


Section 6. Learning is Problem Solving (Coming Soon)

  1. How an LLM stuck in a valley takes a leap - Problem Space

  2. How to see the big picture and the system - Holism

  3. Do I want to change? - Motivation

  4. How can we verify what AI says? - Science

  5. Adapting to a Changing World - Creative Problem Solving

  6. Drawing my own system


Section 7. Things that cannot be solved through individual effort alone (Planned)

  1. Let's create a learning community

Recommended for
these people

Who is this course right for?

  • Those who blame their lack of talent when they can't seem to learn no matter how hard they study

  • Those who feel vague fear and anxiety in the age of AI

Hello
This is rabolution

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I graduated with a degree in physics because I loved the subject, but I now make a living through programming while also working as a coach. I am interested in and studying topics such as testing, functional programming, learning, agile, democracy, and the scientific method. Recently, I have been attending the Department of Law at Korea National Open University while studying to become a certified labor attorney and an electrical engineer.

Full member of FOSS for All. Member of A11yKr. Member of the Green Party Science and Technology Committee. Advisory member for Inclusive Technology at the Ministry of Gender Equality and Family. Academic Director of the Sinabro Study Group in the Department of Law at Korea National Open University.

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