Is there any difference between feature extraction and feature learning?
Yes I think so. Just by looking at Feature Learning and Feature extraction you can see it's a different problem.

Feature extraction is just transforming your raw data into a sequence of feature vectors (e.g. a dataframe) that you can work on. 

In feature learning, you don't know what feature you can extract from your data. In fact, you will probably apply machine learning techniques just to  discover what are good features to extract from your dataset. Then you can extract them them apply machine learning to the extracted features. Deep learning techniques are one example of this.

In the word2vec toolkit, for instance, you extract vectors from documents which can't be easily interpreted by a human, you can't look at it and tell what features have been extracted at all. It's just a mass of vectors which, for some reason, give good empirical results.