This paper summarises the level of knowledge held by educators in the United States on the use of artificial intelligence and machine learning in the classroom. The education industry seems to have reaped little benefits from the AI & ML industry's growth thus far. In any event, the creation of new ML & AI-based systems is mostly aimed towards areas with higher societal needs, such as medical diagnostics and individual transportation, rather than institutions of higher education. With this analysis, we want to shed some light on the mysterious state of application development in the US education industry. The report was written using a triangulation of research approaches to achieve this objective. First, we surveyed the current state-of-the-art reports from other countries and reviewed the relevant literature on AI & ML applications in the field of education. In the second phase, we analysed, to the extent possible, official documents from the United States education sector that dealt with AI and ML based on fuzzy digitalization initiatives. Third, in order to corroborate and expand upon the impressions received from the relevant literature and the document analysis, 15 guideline-based expert interviews were undertaken. Based on this data, we provide a selection of the AI & ML systems in use in universities and colleges now, analyse the benefits and drawbacks of implementing them, and speculate on their potential future evolution. While it would be a stretch to say that this paper presents a comprehensive overview of the subject, it does provide light on key areas of application and potential future research directions for AI and ML.
Keywords: Artificial intelligence; Data analysis; Educational sector; Fuzzy classifier; Learning analytics; Machine learning.
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