Recommender systems provide users with content they might be interested in. Conventionally, recommender systems are evaluated mostly by using prediction accuracy metrics only. But, the ultimate goal of a recommender system is to increase user satisfaction.
Now that the “the only constant is change” in society, our capacity to engage with novel challenges is of first order importance. What are the personal dispositions that authentic learning needs to cultivate, and can we make these assessable and visible to learners and educators?
An interesting question arose at a recent xAPI Camp hosted by The eLearning Guild: “What happened to objectives in xAPI?” We should be able to use xAPI to document successful completion of eLearning, but without statements of learning objectives in the content, this is not possible.
J. Choi, A. Khlif, и E. Epure. Proceedings of the 1st Workshop on NLP for Music and Audio (NLP4MusA), стр. 23--27. Online, Association for Computational Linguistics, (2020)
J. Choi, A. Khlif, и E. Epure. Proceedings of the 1st Workshop on NLP for Music and Audio (NLP4MusA), стр. 23--27. Online, Association for Computational Linguistics, (2020)