  Quality education, one of the seventeen sustainable development goals (SDGs)
identified by the United Nations General Assembly, stands to benefit enormously
from the adoption of artificial intelligence (AI) driven tools and
technologies. The concurrent boom of necessary infrastructure, digitized data
and general social awareness has propelled massive research and development
efforts in the artificial intelligence for education (AIEd) sector. In this
review article, we investigate how artificial intelligence, machine learning
and deep learning methods are being utilized to support students, educators and
administrative staff. We do this through the lens of a novel categorization
approach. We consider the involvement of AI-driven methods in the education
process in its entirety - from students admissions, course scheduling etc. in
the proactive planning phase to knowledge delivery, performance assessment etc.
in the reactive execution phase. We outline and analyze the major research
directions under proactive and reactive engagement of AI in education using a
representative group of 194 original research articles published in the past
two decades i.e., 2003 - 2022. We discuss the paradigm shifts in the solution
approaches proposed, i.e., in the choice of data and algorithms used over this
time. We further dive into how the COVID-19 pandemic challenged and reshaped
the education landscape at the fag end of this time period. Finally, we
pinpoint existing limitations in adopting artificial intelligence for education
and reflect on the path forward.
