You only really know something if you can teach it well. You only gain confidence once you are convinced you can teach it to yourself. These beliefs led to my first forays into teaching; helping out fellow students (mostly friends) who struggled with math. Most thought there was no way math and related fields could possibly be fun—otherwise smart people were bogged down by the (false) notion that they were "no good at math". My goal became to help people gain the confidence to teach themselves anything, starting with mathematics. After a few successful tutoring sessions I gave informal and formal lectures in linguistics and mathematics to try to expose people to the diversity of thinking surrounding these fields—math isn't just crunching numbers, it's ideas and intuition, an amazingly powerful lens with which to see the world.
The following summer, while doing research at McGill University, I was asked to teach a half dozen computer science undergrads some advanced mathematics related to Machine Learning. Since then I have had a passion for not only teaching, but teaching how to teach oneself, in other words, providing the student with a path towards becoming an autodidact. This leads me to some of the major goals that surround my lessons—I try to teach very deliberately, adapting my methods to each student, but always in service to the larger goals below:
Help the student learn to be an autodidact:
Within a couple months you should get to the point where you no longer need me—I am all for having more students, but a good teacher teaches you not only the material, but how to master any new skill or subject that comes your way.
Use material and resources readily available to the student:
If you have an internet connection I encourage the use of online exercise and learning frameworks like Khanacademy, codeacademy, and others. Most methods I teach require nothing but a pencil and paper, you will learn new ways of approaching a problem and how to break down large questions and ideas into smaller more manageable, tangible chunks. There are no special books or resources needed but anything you have, we can use!
Show subject relevancy and relationships between fields:
Why are any of the things you are learning useful? What problems are actually being solved with them? How does your physics homework relate to your computer science homework? How can your love of writing possibly relate to your math homework? These are the questions I get a kick out of answering: you'd be surprised how many amazing and nuanced intersections are out there!
A major goal is to make it so what ever you have learned with my guidance has been internalized deeply. We can start from addition and go all the way to proof theory, but only when every step in between is learned deeply—gaps and holes in knowledge make a bumpy path for learning, unfortunately a strict, lock step curriculum often leaves much to be desired in this department, we will start by understanding where you are and where you want to be.
While my methods will change rather radically depending on the age, previous experience, and goals of the student here is a bulleted guide to my method:
1. Understand the goals of the student.
2. Provide clear structured approaches to learning new material.
3. Create constant opportunities to review previous material.
4. Expose student to real, interesting and exciting questions and problems.
5. Provide (and receive) constant constructive feedback for (and from) the student.
Graduated from McGill University in 2013 with a BA in Computer Science with a minor Mathematics
Taught advanced mathematics tutorial to undergraduates in Mcgill Machine Learning Lab (Summer 2011)
Lectured extensively as part of Undergraduate mathematics research conferences. (2009-2013)
Won award for best presentation in graduate level
Program Manager at Microsoft Corperation in Natural Language Processing 2013
Three years at Camp George as a head counselor (2008-2009), and Assistant Unit head (2010)
Free Consultation: Meet with me for an hour to discuss your goals, constraints, my methods, and to make sure there is a good personality fit!
Group Tutoring: Bring a friend or ten! Meet or contact me to discuss alternate rates and locations for multiple student tutorials and classes. It's cheaper for you and promotes different types of learning and opens up the potential for peer-teaching—the best way to know you've mastered something.
Khan Academy Coaching Included: If you have been working with me either in person or online I am always happy to continue coaching on Khan Academy or other related sites. Whether you're a new student or haven't worked with me in months, I'm happy to help.
Multiple Subject Tutoring: Want a tutor for multiple subjects? I would be happy to incorporate multiple subjects into a (preferably longer) tutorial session: you'd be surprised how helpful learning things in a holistic, interleaved way can help you avoid frustration and boredom while also increasing retention and depth of learning.
Project Advisement: Have a project in writing, coding, math, physics or other projects that you want help structuring? Projects are a great way to learn new fields or connect ones you feel confident in.
Digital Open Door Policy: If you have a question or concern, just shoot me an email! I'll try to get back to you within 24 hours, if you put URGENT in the subject, ASAP!
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