A Model-Based Method for Content Validation of Automatically Generated Test Items

• Author / Creator

  Zhang,Xinxin

• The purpose of this study is to describe a methodology to recover the model (cognitive and item models) from generated test items using a novel graph theory approach. Beginning with the generated test items and working backward to recover the original model (cognitive and item models) using a systematic process with graph theory serves as model-based method for validating automatically generated test items. The methodology is demonstrated using generated items from the medical education domain. The proposed methodology was found to be systematic and generalizable using three different datasets.

• Subjects / Keywords

  • AIG
  • Cognitive model
  • Graph theory

• Graduation date

  Fall 2016

• Type of Item

  Thesis

• Degree

  Master of Education

• DOI

  https://doi.org/10.7939/R34Q7QV97

• 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.