Tracking Knowledge for Learning Japanese as a 2nd Language

Abstract

Most educational technologies for teaching language skills give students the same learning experience based on the assumption that every student learns at the same rate. In order to provide more individualized instruction we need to track student knowledge at a fine-grained level. This research explores how to add the ability to track knowledge in an existing educational technology system for Japanese second language learners. We explore several potential skill models based on the features available in the system and then apply a Bayesian knowledge tracing algorithm. We also make a large dataset for Japanese language learning available with no previous applied knowledge tracing.