Understanding time complexity can be tough for students learning about sorting algorithms. Here are a few reasons why it can be challenging:

1. Different Scenarios: Sorting algorithms work differently depending on the situation. They can perform well in the best case, okay in the average case, or poorly in the worst case. Figuring all this out can be confusing.

2. Math Requirements: Looking at time complexity often involves some tricky math. Students need to understand things like $O(n \log n)$ or $O(n^2)$, which can sound complicated and hard to grasp.

3. Real-Life Use: It’s not always easy to connect the math to real-life use. Just because an algorithm looks good on paper doesn't mean it will always work well with certain types of data.

To help with these challenges, students can:

• Use visuals and simulations to help make things clearer.
• Try out different sorting algorithms through coding exercises.
• Work together in study groups to share ideas and ask questions.

With practice, students can get a better handle on time complexity, leading to a clearer understanding of sorting algorithms.