A Selection Strategy to Improve Cloze Question Quality

We present a strategy to improve the quality of automatically generated cloze and open cloze questions which are used by the REAP tutoring system for assessment in the ill-defined domain of English as a Second Language vocabulary learning. Cloze and open cloze questions are fill-in-the-blank questions with and without multiple choice, respectively. The REAP intelligent tutoring system [1] uses cloze questions as part of its assessment and practice module. First we describe a baseline technique to generate cloze questions which uses sample sentences from WordNet [2]. We then show how we can refine this technique with linguistically motivated features to generate better cloze and open cloze questions. A group of English as a Second Language teachers evaluated the quality of the cloze questions generated by both techniques. They also evaluated how well-defined the context of the open cloze questions was. The baseline technique produced high quality cloze questions 40% of the time, while the new strategy produced high quality cloze questions 66% of the time. We also compared our approach to manually authored open cloze questions.