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Towards Localization of Automated Tutors for Developing Countries

This paper describes localization issues in relation to AIED systems in the developing world, and analyzes the particular case of the successful immersion of learning technologies to schools in Pakistan. The paper analyzes the needs for personalized learning in the developing world in comparison to countries such as the United States. A model and a survey based on various types of localization dimensions like teacher, student, and cultural alignment was developed and deployed to conduct an evaluation of an AI tutor called the Wayang Outpost in Pakistan. The results are that teachers are likely to use such a system if available, and that their intention to use such a tutor in the future is strongly dependent on how well the tutor is aligned with their teaching practices, students’ learning habits, and whether the language in the tutor is understood by students. On average these teachers were also willing to allocate about two hours per week for such automated tutors.