DEEP KNOWLEDGE TRACING WITH TRANSFORMERS

摘要

Digital learning or tutoring systems as described herein embed, by a trained machine learning knowledge tracing engine, an array for learner interactions X into a static representation ej corresponding to a prior learner interaction xj and determine a contextualized interaction representation hj based on this. Digital tutoring systems described herein calculate, by a masked attention layer of the trained machine learning knowledge tracing engine, an attention weight Aij based on a time gap between two learner interactions with the system, and can calculate a contextualized interaction representation hj, wherein the contextualized interaction representation hj is proportional to the attention weight Aij. The systems can provide for display at the GUI a second question item based on the contextualized interaction representation hj, the second question item corresponding to a recommended learner recommendation.