This submission explores the implications of robot embodiment in language learning. Through various innovative studies, it investigates how factors tied to robot usage, such as personality characteristics and learning settings, influence learner outcomes. It incorporates advancements in artificial intelligence by utilizing large language models and further contributes to pivotal understanding through a planned longitudinal study in the migrant context. Lastly, an intensive speech analysis further examines the specifics of human-robot interaction.