Why gapping to run a meta-learning experiment?
On me, my meta-learning experiment structure, and learning in public
Who am I?
I am Amy Deng, a senior studying EECS at Berkeley. I used to be an APM @Google, SWE @Square, analyst @MiraclePlus (prev. Y Combinator China), scholar @Accel, fellow @UnshackledVC, and instructor of Intro to VC at Cal, … But I struggle to identify with these labels sometimes.
Let’s try again. I am Amy, a warm-hearted, genuine, and reflective individual who cares a lot about compassion, vulnerability, and creativity. I am constantly learning more about myself as I am figuring out what I want to believe and what life I want to live, and you will learn more about me through my meta-learning experiment :)
What is Meta-Learning and why?
Meta-learning means learning to learn. I want to learn how I learn best - away from structures and tests at school. Similar to other daily habits, I think learning how to learn is a lifelong investment that will have exponential returns for years to come.
My meta-learning experiment has three steps: design, learning, and evaluation. As students, we are only responsible for the learning step, while course design and outcome evaluation are directed by our professors and TAs. I think I’ve mastered the learning step in the past 15 years as a prudent student. However, I realized that deciding what to learn and defining personal goals are two more important parts of learning that I’ve ignored in the traditional education system.
I struggle with designing what to learn because, for the longest time, I thought I didn’t strive for freedom and agency. Many prominent features of my life were defined by others. I moved to America because my parents thought I should receive an international education although I was perfectly fine with being a test-taking machine in the Chinese traditional system. I studied engineering because it’s the easiest way to get a work visa, although I remember swearing never to become an engineer at age 17. I made good local decisions and I am incredible at execution, but I often find it hard to have ownership of my success because I am not sure if I want to be who I am. For my entire life, I was directed by what others thought I should do, but I realized that I have a lot more freedom than I thought I do. For once, I want to design my own life — do whatever the fuck I want to do and learn whatever the fuck I want to learn.
I listed all the knowledge spaces I am interested in and narrowed it down to 7 fields — health (nutrition & mental health), psychology (mathematical psychology & emotion theory), theatre (playwriting), web dev, UI design, philosophy (existentialism), ML (NLP) that I will each spend roughly 2 weeks on. I consulted friends and the internet for reading or tutorial recommendations, which you can find in my “syllabus.” Parallel to these two-week sprints, I will also be reviewing theatre at Theatrius and taking an acting class at Berkeley Rep Theatre.
Below is my temporary “syllabus” for Psychology. I will share my full syllabus soon in a separate post!
I also struggle with objective self-evaluation. Most of my work isn’t considered good enough by me and I often undersell my abilities. This perfectionism and insecurity prevent me from taking action and sharing in public. I fear being in this closed loop forever, so I am doing two things: 1) evaluating my learning based on my outputs, and 2) running this meta-learning experiment in public. I brainstormed a list of artifacts I want to generate for each subject area: writings, projects, and more. As an action-averse person, I am forcing myself to take action using what I learned! I will publicly share my artifacts every 1-2 weeks through this newsletter alongside my reflections on my meta-learning experiment.
Sounding like founders writing investment updates lol? By subscribing you are “investing” to be part of my social commitment and witness my success, failures, reflections, and vulnerabilities firsthand! Welcome aboard my meta-learning journey!!
Please email me at dengk@berkeley.edu or DM me on Twitter at @amydeng_ if you have any ideas, suggestions, or thoughts on my meta-learning experiment!