What question did this study set out to answer?

The aim is to systematically review the landscape of artificial intelligence in higher education from 2016 to 2022.

Artificial intelligence in higher education: the state of the field

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Systematic review examines trends and usage of AI in higher education, highlighting shifts in research focus and publication rates.

The aim is to systematically review the landscape of artificial intelligence in higher education from 2016 to 2022.
Conducted a systematic review following PRISMA principles on 138 articles.
Employed a priori and grounded coding to analyze and categorize findings.
Examined publication trends and researcher affiliations in higher education.
Publications on AI in higher education rose two to three times in 2021 and 2022 compared to earlier years.
Most research focused on undergraduate students (72%), with language learning as the primary domain.
Five key usage codes emerged: Assessment/Evaluation, Predicting, AI Assistant, Intelligent Tutoring System, and Managing Student Learning.

Crompton et al. (2023) studied this question.

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