Read the input as well as the exception
Keep the final exception line, locate the relevant frame in your own code and record the input. The Python tutorial explains that the exception message identifies its type while the traceback gives context.
For a university tutorial, supply the Python version, smallest reproducing input, expected output and actual output. A copyable example is easier to diagnose than an isolated screenshot.
Worked exercise: one function, two failures
Consider a function whose body is return sum(values) / len(values). For [3, 5], calculate 4.0 yourself. For [], the denominator is zero and the exception is ZeroDivisionError: the contract for an empty input needs attention.
For [3, "5"], summing attempts incompatible addition and raises TypeError before division. This is a different failure and requires a decision about accepted input types.
Choose a contract before a repair
If the function accepts only non-empty numeric lists, it can explicitly reject an empty input with an informative ValueError. If data arrives as text, decide at the input boundary how conversion failures should be reported.
Catching every exception and returning zero hides the distinction between valid zero and failure. Replacing missing data with zero also changes the meaning of the calculation.
Check both successful and failing cases
Create a table for [3, 5], [-2, 2], [] and [3, "5"]. The first two results should be 4.0 and 0.0. Define the expected rejection or conversion policy for the other two before running them.
A useful tutorial outcome is being able to explain both your diagnosis and your tests. Students must independently produce assessed code under their module rules.
References
Your next step
For a module-support enquiry, describe the module, learning goal and what you have tried. Appropriate teaching availability requires confirmation; assessed work remains your own.