I can't believe it's August already. It's been a wild month. I'm in the midst of my first academic teaching experience and I have to say, it's been extremely rewarding. Seeing students' faces light up when they finally understand a concept is a feeling I don't think you get anywhere else outside of teaching.
I met a middle school teacher at a wedding this past weekend. He said the exact same thing. It's funny how innately human the act of teaching can be. The experience of knowledge transfer and the subsequent response encapsulated in a "eureka!" moment is the epitome of teaching success. I'd bet the best teachers in the world agree that this is what it's all about. After all, no one teaches for the money.
Putting together a curriculum from scratch has been a challenge though. Not only did I build an entire syllabus and all of the coursework, but I'm teaching from a book I've only just read this year. It's well within my domain though, so I didn't have a hard time picking it up. But the whole act of coming up with intelligent ways to challenge students thinking and engage them in the learning process is much harder than anyone makes it out to be. Teachers are way underappreciated.
Here is what's new from me this month: What makes a scientist?
Now onto the discoveries...
Carl Jung and the Lion King
I had a conversation with a friend recently that led us to Carl Jung. It occurred to me that over my 6 years of education in psychology, I had little exposure to Jung. This was definitely a miss on my end [even though I'd like to blame it on my professors], so I decided I would fill the gap. One of the best explanations of Jungian psychology I found was through Dr. Jordan B. Peterson, who uses the Lion King to explain him. It's a wonderful analogy of a fantastic film with a plethora of subliminal messaging and archetypes that make it the perfect crash course. You can find part 1 here. Next, I'll be reading The Red Book.
The future of code work
The recent collab between Git-hub and OpenAI is going to change the world of coding forever. The project, dubbed Git-hub Co-pilot, is an AI assistant code generator that will autocomplete your code with astounding results. The implications for productivity in the world of software engineering, data science, and all things code are still being discovered, but I think it's safe to say this is going to be huge. See it for yourself.
Empath is a Python library for analyzing text data, something I've been working a lot with lately. It's a tool that can generate and validate new lexical categories on demand through deep learning and a corpus of more than 1.8 billion words. What's cool about it is that it was built to be a reverse-engineered version of the Linguistic Inquiry and Word Count [LIWC], which has been used for psychometric applications and research. You can read more about LIWC here, and the Empath whitepaper can also be found here.
Learning styles are a myth
I don't know who needs to hear this, but I'll just leave this here...