Identifying negative language transfer in learner writing: using syntactic information to model structural differences

• Author / Creator

  Farias Wanderley, Leticia

• Second language learners transfer rules from their native languages when trying to communicate in the new language. When the transferred rules do not match the second language grammar, this reuse results in errors. Although this phenomenon is well known and documented by linguists and language teachers, few computational methods have been applied to detect it in learner writing. Without the automatic detection of language transfer, it is harder to provide feedback that makes learners aware of the phenomenon. In this thesis,
  I introduce a new method to identify when learner errors are related to the negative language transfer phenomenon. Along with the method description, this thesis contains the results of applying it to a dataset of errors made by Chinese native speakers who were learning English. These results show that my method achieves high precision scores in detecting negative language transfer errors in the writing of Chinese native speakers. These results can be applied in informing error feedback that explains the negative language transfer causes of an error. Providing this type of feedback should help learners reflect on the differences between language rules and refrain from reusing native language rules in their English writing.

• Subjects / Keywords

  • language learning
  • natural language processing

• Graduation date

  Fall 2021

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/r3-rb0v-nt75

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.