Abstract
Assessment Item Generation (AIG) aims at creating semi-automatically many items from a template. This type of approaches has been used in various domains, including language learning and mathematics to support adaptation of tests to learners or allow the item authoring process to scale through decreasing the cost of items. We illustrate in this paper the automatic creation of inline choice items for reading comprehension skills using state-of-the-art approaches. However we show how the AIG process can be implemented to support the creation of items in multiple languages (English, French, and German) and how it can be complemented by the creation of item quality metrics to improve the selection of the generated items.
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