language learning

AI-assisted language learning: Assessing learners who memorize and reason by analogy

Vocabulary learning applications like Duolingo have millions of users around the world, but yet are based on very simple heuristics to choose teaching material to provide to their users. In this presentation, we will discuss the possibility to develop more advanced artificial teachers, which would be based on modeling of the learner’s inner characteristics. In the case of teaching vocabulary, understanding how the learner memorizes is enough. When it comes to picking grammar exercises, it becomes essential to assess how the learner reasons, in particular by analogy. This second application will illustrate how analogical and case-based reasoning can be employed in an alternative way in education: not as the teaching algorithm, but as a part of the learner’s model.

Surprising generalizations in the neural implementation of Hebrew and English word reading

The N400 as a neurophysiological marker of second-language learning

Passive learning of speech sounds associated with microstructure of fronto-temporo-parietal but not fronto-striatal white matter tracts: possible implications for implicit language learning tasks