Affordances and challenges of artificial intelligence in K-12 education: a systematic review

Abstract

Artificial Intelligence in Education (AIEd) has experienced a rapid rise in the past decade. This systematic review is the first examining the use of AIEd in K-12 including 169 extant studies from 2011 to 2021. This study provides contextual information from the research, such as the educational disciplines, educational levels, research purposes, methodologies, year published and who the AI was intended to support. The grounded coding revealed affordances fit into three main themes of AIEd connecting to pedagogies (e.g., gaming, personalization), administration (e.g., diagnostic tools), and subject content. Challenges in AIEd K-12 included issues toward negative perceptions, lack of student and teacher technology skills, ethical concerns, and issues directly with the ease of use and design of the AI tools.

Keywords:

• Artificial intelligence
• AI
• K-12
• AIEd

Acknowledgments

The authors would like to thank Maram Aizaz for her support with the development of the data figures for this paper and Katherina Nako for her help with extracting some of the data from the articles for further examination.

Disclosure statement

No potential conflict of interest was reported by the authors.