LearningAssistant: A novel learning resource recommendation system

摘要: Reading online content for educational, learning, training or recreational purposes has become a very popular activity. While reading, people may have difficulty understanding passage wish to learn more about the topics covered by it, hence they naturally seek additional supplementary resources particular passage. These should be close both in terms of subject matter and reading level. However, using search engine find such interrupts flow. It is also an inefficient, trial-and-error process because existing web recommendation systems do not support large queries, understand semantic topics, take into account level original document person reading. In this demo, we present LearningAssistant, novel system that enables material smoothly enriched with can supplement explain any from reader on demand. The facilitates learning recommending (documents, videos, etc) selected text passages length. recommended are ranked based two criteria (a) how match different within passage, (b) where comes from. User feedback students who use our real pilots, one high school university, their courses suggest promising effective.