ChinesePod currently uses a coarse tiering system for difficulty levels. I see logic in how it works, but it is not always easy to know the actual difficulty relative to my learning path. As an example, I may know many words in an intermediate lesson, but not very many in an easy lesson. In that situation, the intermediate lesson may actually be easier for me. Also, because an individuals learned vocabulary can vary a lot, a specific lessons relative difficulty can vary tremendously between different individuals.
A solution could be to just track all the vocabulary from studied lessons and then add a “relative difficulty” tailored to each user which ranks a lesson’s difficulty based on, for example, a ratio of new and learned words. It’d be super informative to know that a lesson has x% new content and/or y number of new words based on a users “studied” vocabulary (i.e., the collective vocabulary from all lessons marked as studied.). It’s not a perfect solution, but I think it would help guide a learners progression immensely.
This would simultaneously solve another issue I have with ChinesePod, which is the lack of guided progression. Studying N number of lessons before moving on, again, is too generalized. Depending on content overlap, the amount actually learned can vary a lot based on which courses a person selects for their N lessons.
Edit: I just noticed this suggested in the April Update thread. Feel free to delete this (I don’t know how); I will repost this there.