Sentence Selection for Cloze Item Creation: A Standardized Task and Preliminary Results
Cloze items are commonly used for both assessing learning and as a learning activity. This paper investigates the selection of sentences for cloze item creation by comparing methods ranging from simple heuristics to deep learning summarization models. An evaluation using human-generated cloze items from three different science texts indicates that simple heuristics substantially outperform summarization models, including state-of-the-art deep learning models. These results suggest that sentence selection for cloze item generation should be considered a distinct task from summarization and that continued advances on this task will require large datasets of human-generated cloze items.
CEUR Workshop Proceedings
Olney, A. (2021). Sentence Selection for Cloze Item Creation: A Standardized Task and Preliminary Results. CEUR Workshop Proceedings, 3051 Retrieved from https://digitalcommons.memphis.edu/facpubs/8579