# Proactive and Reactive Engagement of Artificial Intelligence Methods for Education: A Review

**Authors:** Sruti Mallik, Ahana Gangopadhyay  
**arXiv:** [2301.10231](https://arxiv.org/abs/2301.10231)  
**Date:** 2023-01-23  
**Summary page:** https://www.summarizepaper.com/en/paper/2301.10231v1/

## Key points

- Quality education as a sustainable development goal
- Increasing research and development efforts in AI for education
- Categorization approach to investigate AI, machine learning, and deep learning methods in education
- Analysis of 194 research articles on proactive and reactive engagement of AI in education
- Paradigm shifts in solution approaches over time
- Impact of COVID-19 pandemic on educational practices and role of AI
- Existing limitations in adopting AI for education
- Potential pathways forward to enhance educational processes with AI

## Summary

In their review article titled "Proactive and Reactive Engagement of Artificial Intelligence Methods for Education: A Review," authors Sruti Mallik and Ahana Gangopadhyay explore the potential benefits of adopting artificial intelligence (AI) driven tools and technologies in the field of education. They highlight that quality education can greatly benefit from AI advancements as it is one of the seventeen sustainable development goals identified by the United Nations General Assembly. The authors note that with the increasing availability of necessary infrastructure, digitized data, and growing social awareness, significant research and development efforts have been made in the artificial intelligence for education (AIEd) sector. To investigate how AI, machine learning, and deep learning methods are being utilized to support students, educators, and administrative staff, they employ a novel categorization approach. The review encompasses various aspects of the education process <KD> starting from proactive planning activities such as student admissions and course scheduling to reactive execution tasks like knowledge delivery and performance assessment.</KD> By analyzing 194 original research articles published between 2003 and 2022, Mallik and Gangopadhyay outline major research directions under both proactive and reactive engagement of AI in education. They also discuss paradigm shifts in solution approaches over time <KD>, including changes in data usage and algorithm selection.</KD> Additionally, the authors delve into how the COVID-19 pandemic has posed challenges to the education landscape towards the end of this period. They examine how AI has played a role in reshaping educational practices during this crisis. Finally <KD>, Mallik and Gangopadhyay identify existing limitations in adopting AI for education while reflecting on potential pathways forward.</KD> Their comprehensive review provides insights into how AI-driven tools can enhance educational processes while addressing current challenges faced by educators worldwide.