Including people in the automatic text adaptation process: empirical findings from students with intellectual disability.

Modern automatic text adaptation often fails to meet the specific needs of targeted readers. The TextAD project aimed to address this gap by creating tailored texts for students with intellectual disability (ID), focusing on their unique challenges. This exploratory study presents findings from three rounds of testing automatic adaptations at lexical, syntactic, and discourse levels in expository texts. Reading comprehension, self-reported ratings of comprehension, interest, and perceived difficulty, along with metacognitive insights were assessed with 27 students with ID, refining adaptations based on each iteration's results. While comprehension gains for the adapted versions were not significant overall, promising outcomes appeared with lexical and syntactic adaptations in the later rounds of testing, although group heterogeneity influenced results. Despite reporting high comprehension, students noted persistent difficulty understanding many expository concepts. Alongside evaluating the effects of text adaptations on comprehension and perceived understanding, this paper offers insights into assessment approaches for developing automatic adaptations tailored to this audience.