Unpacking My Learning Journey: Hello EDCI 335!
Hi everyone,
My name is Dharun, and I’m a third-year computer science student. My path here started with a simple curiosity about how video games work, which grew into a real passion for building software. I’ve always loved the logic and creativity of coding, but I’m excited for this course to explore the other side of the coin: how we actually learn these complex skills. I’m looking forward to explore how I build an application and how my brain builds understanding.
What Learning Is to Me
For me, learning isn’t about memorizing facts for a test. It’s about truly understanding something so you can use it to solve a new problem. It’s the process of an idea moving from an abstract concept in a lecture slide to a tool you can actually use.
The best example I have of this is when I taught myself the programming language Python. I didn’t just read a book; I jumped right in and started building things. Most of my first attempts were a complete mess, but seeing my code work or break in real-time was the best teacher. That cycle of trying, failing, and figuring out why I failed is what made the knowledge stick. It’s like learning to ride a bike – you can’t just read about it. You have to get on, feel wobbly, and maybe fall once or twice before it clicks.
How I Learn Best: Building My Knowledge
After reading about the different learning theories, I realized I strongly lean towards constructivism. The core idea is that we learn best by actively doing and experiencing things for ourselves. This is the heart and soul of computer science. You can’t just listen to someone talk about code; you have to write it, test it, and fix it when it breaks.
This is why I’ve always preferred hands-on projects to just studying textbooks. It’s less about the pressure of studying for a grade (which feels more like behaviorism) and more about chasing that “aha!” moment when a difficult concept finally makes sense. That feeling of building a real understanding is what drives me.
What Keeps Me Motivated
The ARCS Model provides a great framework for what drives us. For me, one element stands out as the most important.
| Component | Description | My Take |
| Attention | Grabbing and holding interest. | Important, but can fade if the topic feels pointless. |
| Relevance | Connecting the content to personal goals or needs. | This is everything. If I can’t see the “why,” I struggle to engage. |
| Confidence | Helping the learner believe they can succeed. | Crucial, and it usually grows when I can see the relevance. |
| Satisfaction | Providing a sense of accomplishment or reward. | A great feeling, but it’s the result of being motivated, not the cause. |
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As you can see, Relevance is the key for me. I remember struggling through a tough math course that felt completely abstract. Later, in my algorithms class, I saw how those exact math principles were critical for writing efficient, powerful code. Suddenly, the topic wasn’t a chore anymore—it was an essential tool I needed. That connection to a real-world use case was the switch that flipped my motivation on.
Using What I Already Know
We don’t learn in a vacuum. Everything we already know acts as a foundation for new ideas. This is especially true in a field like computer science, where every new topic is built on top of earlier ones.
For example, learning a concept called recursion was a huge challenge. It’s a tricky way of solving problems by having a function call itself. It felt confusing until I realized it was just a new way of thinking about something I already knew well: loops. By connecting the new, scary idea to the familiar foundation of loops, it became much more manageable. It showed me that my past experience is my most valuable asset when tackling something new.
Final Thoughts
Ultimately, I see learning as an active, hands-on process. It’s about building an understanding piece by piece, fueled by seeing the relevance in what I’m doing. I look forward to exploring these ideas more with all of you this semester.