Tackling Italian University Assessment Tests with Transformer-Based Language Models

Abstract

Cloze tests are a great tool to asses reading proficiency as well as analytical thinking, and are therefore employed in admission and assessment tests at various levels of the education system in multiple countries. In Italy, cloze tests are administered to incoming university students to ascertain their starting level. The goal of a cloze test is to determine several tokens that have been pre-deleted from a text; this is largely equivalent to the well-known NLP task of missing token prediction. In this paper, we show that cloze tests can be solved reasonably well with various Transformer-based pre-trained language models, whose performance often compares favorably to the one of incoming Italian university students.