Structuring Knowledge for 10,000 CS Students

The Content Organization Problem

Computer engineering students at the Islamic University of Gaza face a scattered landscape of learning materials. Resources are spread across YouTube channels, university portals, personal blogs, and outdated PDFs with no unified structure connecting them. A student trying to learn data structures might find a great video series, but have no way to know what prerequisite knowledge they're missing or what to study next.

The core challenge was not a lack of content - it was the absence of a navigable structure. Thousands of resources existed, but without a taxonomy that mapped them to both academic requirements and industry skill trees, students spent more time searching for materials than actually learning from them.

We needed to design a content architecture that could organize these resources into clear, prerequisite-aware pathways without becoming rigid or outdated as university curricula evolve and new technologies emerge in the industry.

Designing the Dual-Axis Taxonomy

We settled on a two-axis classification system where every resource is tagged along both an academic course axis and a practical skill domain axis. This means a single tutorial on REST API design can appear in both the 'Web Development' pathway and the 'Software Engineering 2' course track, without content duplication.

The prerequisite graph was the key technical decision. Rather than a flat list of resources per topic, we built a dependency graph that automatically suggests learning order. If a student jumps into a backend development pathway, the system surfaces the networking and database fundamentals they need first - mapped directly from the university's own course dependency chain.

• Dual-axis tagging: academic course mapping and industry skill-tree alignment.
• MDX-based content format for flexible, version-controlled resource pages.
• Prerequisite graph that automatically suggests learning order based on dependencies.