Imagine you are developing a large language model designed to act as a tutor for advanced physics problems. You have two potential training strategies for providing feedback to the model:

Strategy A (Outcome-Based): The model generates a complete, multi-step solution to a physics problem. It receives a positive reward only if its final numerical answer is correct.

Strategy B (Process-Based): The model generates the solution one step at a time. It receives a positive reward for each individual step that is conceptually sound and logically follows from the previous one, even if a minor calculation error later leads to an incorrect final answer.

Evaluate these two strategies. Argue which strategy is more likely to produce a reliable and effective physics tutor. In your evaluation, consider the potential long-term effects of each strategy on the model's ability to generalize its reasoning to new and varied problems.