Applied Learning vs. Theoretical Learning
Upskilling as a working professional is always challenging. Juggling deadlines, responsibilities, and the need to stay ahead in your field can make it hard to decide on the best approach to learning. I often find myself debating whether to learn a new skill by building a project or starting from theory, such as reading a book from scratch. Over time, I’ve realized that a bottom-up approach—prioritizing applied learning—helps me learn new skills faster than purely theoretical methods.
“Tell me and I forget, teach me and I may remember, involve me and I learn.” - Benjamin Franklin
Why Applied Learning Works
Applied learning, or “learning by doing,” focuses on solving real-world problems. For professionals, it means engaging with tasks, tools, and projects that reflect their daily work. This hands-on method helps in quickly acquiring job-ready skills and adapting to challenges.
For example, I started using Python scripts to automate repetitive ArcGIS workflows without fully understanding the underlying principles of programming. By applying concepts directly, I was able to achieve immediate results and gain valuable experience. As I progressed and sought to optimize my workflows further, I began exploring the theory behind algorithms and programming techniques. This deeper understanding allowed me to refine my approach and improve efficiency.
When to Embrace Theory
Once you’ve gained practical experience, delving into theory can solidify your knowledge. Understanding the “why” behind your actions builds confidence and prepares you for more complex challenges. For instance, while working with the ArcGIS Python API, I noticed significant performance issues (back when ArcMap was the standard). This led me to explore algorithms using GDAL utilities to speed up tasks. By combining theoretical knowledge with hands-on experience, I could innovate and solve problems effectively.
The Bottom-Up Advantage
This applied-first method allows professionals to:
Stay productive while learning.
Solve immediate problems in their domain.
Build a strong foundation for deeper theoretical exploration.
It’s not just a simple bottom-up approach—it involves constant iteration. You apply what you know, learn from the outcomes, and reapply with improvements. This dynamic cycle ensures relevance while fostering continuous growth, empowering professionals to excel in their fields.