Customized Robot-Assisted Language Learning to Support Immigrants at Work: Findings and Insights from a Qualitative User Experience Study

Abstract

There is a strong societal pressure for the immigrants to learn the local language to be able to properly enter the work-life and social life in the new culture. The limit of resources in second language teaching and the challenges related to language practicing with native people, encourages us to search for alternative options for the second language learning. Robot-assisted language learning (RALL) provides one potential option. In this article, we focus on exploring the potentials of customized language robots for immigrants to support their professional development and adaptation to the local work contexts. We describe our qualitative and exploratory user study with 10 immigrants as participants, focusing on their user experience (UX) of the customized RALL solution for language learning at work settings. We collected data through 1) field observations of the authentic RALL sessions in a user pilot, and 2) user interviews in the end of the pilot. The research shows that customization of several aspects of RALL is needed to support immigrants? language learning at work. These include, e.g. the vocabulary and tasks, the level, the speed of language, and the timing of the RALL. The optimal customization can be achieved by co-designing the RALL within the multidisciplinary team including the workplace representatives, language trainer and programmer. The RALL provides a lot of potential for immigrants? language learning as it offers unique learning experiences and many possibilities to keep up the learner?s attention and motivation. However, there are also challenging aspects, which need further consideration.