Learning Content Generation by Extracting Lecture Slides Based on Word Importance and Difficulty

This work aims to generate new learning contents from the original slides of one on-demand online lecture for preparation or review. They are related to users’ knowledge levels based on the importance and difficulty of the feature words in the original slides. For this purpose, we first extract feature words from the original slides and calculate their degrees of importance and difficulty. Then, we classify feature words into three groups based on knowledge level to generate learning contents. Finally, we evaluated and discussed the usefulness of our generated learning contents. And we also confirmed their effectiveness in preparation and review.