16.11.23

What Learning to Program in the 1990s Taught Me About How Computers Work and Why Generative Artificial Intelligence Makes Sense to Me

It's circa 1991 — during my middle school years — I attended a small Catholic school where I enrolled in a computer science class. The computers ran on a slow-running operating system called MS-DOS that included a cool feature — a way to code in a basic programming language called QBasic, featuring a simple lime green blinking cursor on the screen. It ran Nibbles, a fun game to boot, but to play more advanced games, we used floppy disks, slightly larger than a postcard but smaller than a standard piece of paper, containing a metallic tape where data was stored.

Illustration of a classroom filled with old Commodore computers running on QBasic
I requested Dalle-3 to create an illustration depicting
my computer science classroom, vividly filled with
Commodore computers operating on QBasic.

The fun aspect of these classes involved playing games on these floppy disks. However, equally engaging was experimenting with QBasic. It's a simple, beginner-friendly programming language developed by Microsoft. It was quite popular in the late 1980s and early 1990s for teaching programming basics in an easy-to-understand way. QBasic is known for its simplicity, making it a good starting point for beginners in programming. We could create command lines and basic math problems. Our teacher introduced us to subroutines, enabling us to develop more complex programs like a quiz show. For instance, I programmed a game where the user would answer questions like "What is the capital of Washington State?". Correct answers led to more challenging questions, while wrong ones could end the game or reduce progress. By the way — the answer is Olympia.

Over time, I developed an advanced quiz bowl game with fifty unique questions embedded in different subroutine categories, enhancing my programming skills. My fascination with QBasic grew, prompting me to research more about it in the public library. I learned to replicate other programs, such as the classic snake game.

For illustrative purposes — here's a snippet of QBasic code.

SUB AskWashingtonCapital
    DIM answer AS STRING
    PRINT "What is the capital of Washington State? The answer is Olympia."
    INPUT answer
    IF LCASE$(answer) = "olympia" THEN
        PRINT "Correct! Now for a more difficult question."
        AskUSTerritory
    ELSE
        PRINT "That's not correct. Let's try an easier question."
        AskUSCapital
    END IF
END SUB
 


Fast forward to 2023, the world of generative AI is an evolution of my early programming experiences. When using a tool like ChatGPT, asking a question like the capital of Washington State, it processes the query using its neural network and provides an answer, similar to the if-then statements in my quiz game. However, the complexity and scale of these large language models (LLMs) are far beyond what we had back then.

These models, like ChatGPT, are based on vast amounts of data fed into them, enabling predictive text generation. Yet, unlike human cognition, these computers don't 'understand' in the same way we do. They process information based on input from human-made sources, creating an artificial neural network.

Looking ahead, these neural networks could eventually update themselves, especially if they gain access to the internet or large databases. This self-improvement capability in computer programs could lead to significant advancements in AI, potentially paving the way to what some refer to as 'the singularity.' The future of this technology is uncertain, but its potential is undoubtedly intriguing.

2.11.23

From Zero to 2,036: My Slow Burn Journey as a TpT Seller

I'm eager to share more about my side endeavor where I craft and vend educational digital content. My process involves considering what educators might need—be it customizable digital worksheets, interactive games featuring mythological characters, or innovative lesson plans that incorporate philosophy into the classroom. I'm dedicated to creating these resources with a special focus on enriching the teaching experience for middle and high school English and humanities instructors.


The chart shows visually how my store has grown bit by bit.

    Hello fellow educators and creators! I want to share my personal journey as a TpT (Teachers Pay Teachers) seller to offer encouragement to those just starting out and connect with my fellow middle and high school humanities and English content creators.

My Timeline on TpT

  • 2017: Took the plunge and opened my TpT store. However, I didn't manage to sell any units.
  • 2018: Still dipping my toes in, I sold a meager 4 units.
  • 2019: Finally began to take things a bit more seriously midway through the year, resulting in 107 units sold.
  • 2020 & 2021: This was when I really decided to commit, and it paid off. I sold 188 units in 2020 and a whopping 541 units in 2021.
  • 2022: Continued my upward trajectory with 603 units sold.
  • 2023 (as of November 1st): Already close to last year's total with 588 units sold.
  • All-Time Units Sold: 2,036 and counting!

A Closer Look

As I posted (see figure above), my TpT journey is visually a slow burn (maybe burning a wild camp fire, who knows?!). The quick snapshot of my journey is from the online tool TpT has created for sellers to see stats and stuff. 

My Style

I'd be the first to admit, I'm not what you'd call a "serious" seller. My store doesn't follow traditional marketing techniques, and let's just say, my cover designs are beautiful pieces of chaos. But the numbers speak for themselves — buyers, especially those in the middle and high school humanities and English sectors, appreciate what I bring to the table.

So, whether you're a newbie struggling to make your first sale or a veteran looking for some inspiration, remember that there's room for everyone in this marketplace. Just find your niche and stick with it!

Cheers to more learning and sharing ahead!