The Flipped Classroom model for teaching Conditional Random Fields in an NLP course
This is an incremental improvement in teaching methods for NLP education, addressing student engagement and learning outcomes.
The authors applied the flipped classroom model to teach Conditional Random Fields in an NLP course, finding that students learned the topic and some found the method rewarding based on evaluations.
In this article, we show and discuss our experience in applying the flipped classroom method for teaching Conditional Random Fields in a Natural Language Processing course. We present the activities that we developed together with their relationship to a cognitive complexity model (Bloom's taxonomy). After this, we provide our own reflections and expectations of the model itself. Based on the evaluation got from students, it seems that students learn about the topic and also that the method is rewarding for some students. Additionally, we discuss some shortcomings and we propose possible solutions to them. We conclude the paper with some possible future work.