Four Interactions Between AI and Education: The AIxEd Framework

Sina Rismanchian • Shayan Doroudi
University of California, Irvine

Welcome to the interactive visualization of our research paper. This paper presents a new framework (AIxEd) to categorize the various kinds of relationships between artificial intelligence (AI) and education in terms of two axes. Using this framework, we examine the evolution of the field of Artificial Intelligence in Education over four decades by examining papers published in AIED proceedings (1985, 1993, 2021, and 2024) and the International Journal of Artificial Intelligence in Education (2004, 2014, and 2021). We argue that AI's role in education extends beyond its use as a practical tool for solving educational problems. AI also serves as a conceptual analogy for understanding human intelligence and learning. However, we show that this way of thinking about AI and education, which was once prevalent, has received much less focus in recent years. We suggest that the growing enthusiasm among researchers for using generative AI, as evidenced by papers in AIED 2024, offers opportunities to deepen our insights into student knowledge and learning processes. Finally, we propose new directions for future AIED research that span the different kinds of research in AIxEd.

For more details, please refer to the full paper by clicking the link below:

Full Paper

The AIxEd Framework

The AIxEd framework uses two axes to interpret the position of research projects in the field of Artificial Intelligence in Education:

AIxEd Framework Diagram
Figure 1: The AIxEd Framework showing the four quadrants of AI and Education interaction

X-Axis: The Role of AI ranges from AI as an Applied Tool (top) to AI as an Analogy to Human Intelligence (bottom). Applied tools use AI practically to solve educational problems, while the analogy approach explores parallels between AI and human cognition.

Y-Axis: The End User ranges from Learners (right) to Researchers (left). The learner end focuses on direct educational benefits to students, while the researcher end involves using AI to improve our understanding of learning and educational systems.

The intersection of these axes creates four quadrants of research:
1. Upper Left: Researchers using AI tools to study educational problems (e.g., Learning Analytics)
2. Upper Right: Learners using applied AI tools like intelligent tutoring systems
3. Lower Left: Researchers using AI models to understand human learning (e.g., Cognitive Models)
4. Lower Right: Learners using AI to reflect on their own learning

Citations

Rismanchian, S., & Doroudi, S. (2023). Four interactions between AI and education: Broadening our perspective on what AI can offer education. In International Conference on Artificial Intelligence in Education (pp. 1-12). Springer. 

@inproceedings{rismanchian2023four,
  title={Four interactions between AI and education: Broadening our perspective on what AI can offer education},
  author={Rismanchian, Sina and Doroudi, Shayan},
  booktitle={International Conference on Artificial Intelligence in Education},
  pages={1--12},
  year={2023},
  organization={Springer}
}