Genghu Shi

Adult learners with low literacy skills compose a highly heterogeneous population in terms of demographic variables, educational backgrounds, knowledge and skills in reading, selfefficacy, motivation etc. They also face various difficulties in consistently attending offline literacy programs, such as unstable worktime, transportation difficulties, and childcare issues. AutoTutor for Adult Reading Comprehension (ATARC), as an online conversation-based intelligent tutoring system that incorporated a theoretical model of reading comprehension, was developed with great efforts to meet adult learners’ needs and be adaptive to their knowledge, skills, selfefficacy, and motivation. In this paper, we introduced the adaptive features of AT-ARC from four aspects: learning material selection, adaptive branching, trialogues, and interface, as well as the rationale behind these designs. In the end, we suggested further research on improving the adaptivity of AT-ARC.