Computer-aided generation of multiple-choice tests 论文

摘要

This paper describes a novel computer-aided procedure for generating multiple-choice tests from electronic instructional documents. In addition to employing various NLP techniques including term extraction and shallow parsing, the program makes use of language resources such as a corpus and WordNet. The system generates test questions and distractors, offering the user the option to post-edit the test items.