  We conduct a preliminary study of the effect of GPT's temperature parameter
on the diversity of GPT4-generated questions. We find that using higher
temperature values leads to significantly higher diversity, with different
temperatures exposing different types of similarity between generated sets of
questions. We also demonstrate that diverse question generation is especially
difficult for questions targeting lower levels of Bloom's Taxonomy.
