Offline Artificial Intelligence for Education: a path to a more inclusive field.

The field of Artificial Intelligence (AI) has the potential to improve teaching and learning, for example, by analyzing data produced in educational environments. Furthermore, it can also worsen inequality, as it requires students and instructors to have access to the infrastructure (smartphones or computers) required by the majority of those tools to generate and analyse data. However, access to such infrastructure is not a reality for many students around the world. To shine a light on this problem, this paper investigates, through a Systematic Mapping Study (SMS), initiatives that enable a more inclusive data analysis using AI in education, especially in scenarios with few connectivity resources. We identified that these initiatives are scarce and they are focused in the first phase of the data analysis task: the data collection. Based on the SMS results, we propose a set of recommendations for researchers to offer directions toward a more inclusive analysis of educational data using AI. [ABSTRACT FROM AUTHOR]