From Visualisation to Hypothesis Construction for Second Language Acquisition
Shervin Malmasi, Mark Dras · 2014
One research goal in Second Language Acqui-sition (SLA) is to formulate and test hypothe-ses about errors and the environments in which they are made, a process which often involves substantial effort; large amounts of data and computational visualisation techniques promise help here. In this paper we have defined a new task for finding contexts for errors that vary with the native language of the speaker that are potentially useful for SLA research. We pro-pose four models for approaching this task, and find that one based only on error-feature co-occurrence and another based on determining maximum weight cliques in a feature associ-ation graph discover strongly distinguishing contexts, with an apparent trade-off between false positives and very specific contexts. 1