Over the years, language technology has become a valuable asset for foreign language learners. In this work, we introduce pronunciation feedback scoring systems for 6-12 year old children. The scoring systems were embedded in second-language (L2) English learning games that were designed to prompt children to repeat words. Speech and phone recognition models were used to validate utterances and extract phoneme-wise statistics, which were used to compute feedback scores of 0-5 stars. The scoring systems were trained to mimic the preferences of a single expert who evaluated all the training data. Our automatic scoring system reached a correlation of 0.59 to the human annotation. This system was also tested in a learning experiment, where EEG measurements indicated that children who played our learning game with our scoring engine for pronunciation feedback improved their perception of speech sounds. We release the game codes and the speech data used to train the scoring system.