  We show a method to auto-select reading passages in English assessment tests
and share some key insights that can be helpful in related fields. In
specifics, we prove that finding a similar passage (to a passage that already
appeared in the test) can give a suitable passage for test development. In the
process, we create a simple database-tagger-filter algorithm and perform a
human evaluation. However, 1. the textual features, that we analyzed, lack
coverage, and 2. we fail to find meaningful correlations between each feature
and suitability score. Lastly, we describe the future developments to improve
automated reading passage selection.
