On The Role of Machine Learning in A Human Learning Process

Breakout Room B

This study aims to explore the role of machine learning in a human learning process. In particular, we use word embedding and basic recurrent neural network methodologies in the teaching of terminology and specialized knowledge acquisition for translation students. Results show that word distribution in vector space trained on a relevant corpus can provide useful insights for learners to understand the terms and their associated concepts. We also build term recognition models for different levels of learners, which help instructors predict terms for these learners, while incorporating their previous knowledge and skills, so as to better communicate with the students in their teaching.