Visualizing graphs can really help you understand topological sorting techniques. This is especially true when looking at Kahn's Algorithm and the Depth-First Search (DFS) method.

First, graph representation helps students see how different nodes are connected. For example, in Kahn’s Algorithm, visualizing a directed acyclic graph (DAG) helps you find nodes that have zero incoming edges. This is important for understanding how nodes are handled based on their relationships. You can imagine arrows pointing from one node (the prerequisite) to another (the dependent node). This makes it easier to understand what needs to come first.

Next, when you use the DFS method, seeing things visually makes it easier to understand the process of going back and forth. As you visit and mark nodes, you can actually see when you return to already visited nodes after going deeper. This backtracking shows how nodes get stacked up, and once you've checked all the nodes, you can see the topological order clearly.

Also, using color coding for the nodes during the visualization changes the game. Different colors can show the state of each node: unvisited, currently visiting, or visited. This helps you see how the DFS marks the nodes and reinforces how the algorithm works.

In the end, visualizing graphs does more than just explain theories. It helps students handle complex problems with topological sorting more confidently and clearly. In computer science, having strong visual tools can make confusing algorithms easier to understand.