About the Workshop

The growing integration of Artificial Intelligence (AI) across various sectors, including education, is driving significant changes in teaching and learning processes. AI-powered tools and systems present unique opportunities to transform the educational landscape by enhancing the role of teachers and fostering deeper human-AI collaboration in classrooms. Central to this transformation is the concept of augmented educators—teachers who leverage AI to amplify their capabilities. This workshop addresses two fundamental aspects of this emerging paradigm: improving teachers' ability to deliver personalized feedback through AI and evolving AI systems to exhibit human-like qualities such as empathy, understanding, and adaptability in personalized learning environments.

The need for AI in education is becoming more urgent due to the increasing diversity in student needs, learning styles, and socio-economic backgrounds. Traditional teaching approaches that rely on standardized curricula and manual feedback are no longer sufficient to meet these varied demands. AI technologies, especially those powered by large language models (LLMs), offer a solution by enabling tailored feedback at scale and providing personalized learning experiences across a range of disciplines, from writing and debate to project-based activities. Additionally, AI's ability to process large amounts of data from student interactions enables real-time insights, allowing teachers to focus on high-impact tasks such as nurturing creativity, critical thinking, and problem-solving.

However, incorporating AI into education brings its own set of challenges. For AI to truly augment educators, it must move beyond simple automation and data analysis. Teachers need AI tools that not only support their instructional roles but also preserve the human connection in learning.

As AI becomes more embedded in classrooms, critical questions arise about how these systems can retain the human touch, especially in providing emotionally meaningful, context-aware feedback. The core issues of this workshop revolve around two key themes: designing AI systems that effectively support educational objectives and advancing AI to develop a more empathetic and human-like presence in learning settings.

This workshop will delve into these two core areas—AI for personalized feedback and AI systems with human-like empathy—to explore how AI can transform the role of teachers in reshaping education. By bringing together educators, AI researchers, and policymakers, the workshop will facilitate meaningful dialogue on designing AI systems that empower teachers and support students in an increasingly AI-driven educational landscape.

Theme 1: AI-Powered Tools for Personalized Feedback and Enhanced Teaching

The first theme will examine how AI-driven educational tools can help teachers deliver more effective and personalized feedback across diverse subject areas, such as writing, discussion-based courses, and project-based learning. Tools like ITS and LLMs can automate routine tasks such as grading and providing feedback, freeing up teachers to concentrate on higher-level instructional goals, including fostering creativity, critical thinking, and deeper student engagement.

Key discussion points will include:

• ​AI systems for personalized learning, including Intelligent Tutoring Systems (ITS) and adaptive assessment
  platforms

• The use of large language models (LLMs) to provide real-time, tailored feedback in areas such as writing and
  debate

• Improving teacher effectiveness through AI-generated insights into student performance

• Challenges related to scalability, accuracy, and maintaining human oversight in AI-driven feedback systems

Theme 2: Building Empathy and Emotional Awareness in AI Systems

The second theme will explore how AI systems can be designed to go beyond mimicking human cognitive abilities to also understanding and responding to the emotional and psychological states of students. For AI to effectively augment teachers, it must recognize and respond to students’ emotional cues, providing empathetic feedback that addresses their needs beyond academic achievement. Achieving this requires the integration of advanced emotion recognition and affective computing technologies into AI systems.

Key discussion points will include:

• Emotion recognition and sentiment analysis in AI-powered educational platforms

• Designing AI systems that exhibit empathy and human-like understanding

• Navigating ethical concerns related to AI’s impact on students’ emotional well-being

• Balancing AI’s capacity to mimic human empathy while maintaining the integrity of the teacher-student
  relationship