How AI is Transforming Personalized Education: Highlights from IJCAI 2021

IJCAI 2021 Education AI Symposium Overview

The International Joint Conference on Artificial Intelligence (IJCAI) 2021 hosted a special online symposium on AI in education, jointly organized by TAL, the University of Memphis, Michigan State University, and Squirrel AI. Global technology experts and industry leaders presented the latest research and explored how AI can empower the education sector.

AI‑Powered Personalized Teaching Directions

Speakers highlighted several AI‑driven approaches to personalized education, including precise recommendation of learning content to ensure quality and efficiency, automatic generation of teaching materials to boost teachers’ preparation speed, real‑time analysis of student behavior for immediate instructional guidance, modeling of learning processes for scientific evaluation, and the development of effective metrics to assess educational technology.

Case Study: Xueersi 1‑on‑1 “AI+” Learning System

In TAL’s Xueersi 1‑on‑1 system, AI analyzes classroom interactions between teachers and students, identifies learning states, and prompts high‑frequency positive feedback and guidance, helping maintain high learning efficiency. The technology also permeates board notes, teacher‑student interaction, and teaching techniques.

With AI support, the educational process is measured and recorded accurately, shifting classrooms from a one‑way input model to active student output, fostering habits of expression, writing, and summarization. After each class, the system automatically generates an intelligent learning report for the student.

AI + Cognitive Science: Quantifying Learning Progress

The “AI+” system integrates cognitive science with AI to make student progress quantifiable. The “Xueersi Assessment System” visualizes answer paths and thought processes, combines theoretical reflection and knowledge tracking, and analyzes why students with the same scores may have different abilities, uncovering learning potential.

Leveraging knowledge graphs and AI, the system precisely judges students’ foundational skills, visualizes weak points, and designs personalized teaching plans based on regional, school‑level progress and learning conditions.

Assessment System Aligned with Core Competencies

The assessment framework merges the core competencies required by compulsory education curriculum standards with Bloom’s taxonomy, making it widely applicable for measuring and evaluating K‑12 students’ cognitive abilities.

Future Teaching Scenarios

Experts anticipate that every teaching link will feature comprehensive student profiles and fine‑grained knowledge graphs. AI will enhance student engagement, help teachers monitor each learner’s ability model, pinpoint pain points in feedback, and enable truly personalized instruction.

TAL’s Broader AI Innovations in Education

Beyond personalized teaching, TAL has advanced AI in image and video understanding, machine learning, natural language understanding, speech synthesis, and evaluation. The company has released over 170 AI capabilities, more than 10 competition championships, published over 60 high‑level academic papers, and filed more than 100 patents.

This symposium marks TAL’s third time leading an IJCAI special session. Earlier in March 2021, TAL organized the AAAI “AI+ Education” spring symposium. As the builder of the “Smart Education National New‑Generation AI Open Innovation Platform,” TAL promotes open, win‑win collaboration, creating an international exchange platform for academia‑industry cooperation and enhancing the global influence of Chinese educational technology.

TAL continues to share its resources, partnering with academic and industry peers to accelerate smart classrooms, teacher assistance tools, intelligent learning companions, educational hardware, and adaptive learning solutions, driving equitable, high‑quality education.