The field of education is witnessing a significant shift towards human-AI collaboration, with a focus on developing innovative approaches to integrate AI into learning environments. Recent studies have explored the potential of AI to support student learning, improve academic outcomes, and enhance the overall educational experience. Notably, researchers are investigating the use of large language models (LLMs) to provide personalized feedback, facilitate collaborative learning, and promote critical thinking. Furthermore, there is a growing emphasis on developing AI literacy programs that equip students with the skills to effectively use and evaluate AI tools. The development of frameworks and models, such as the Ethical AI Integration Model and the PIPE Model, aim to guide the responsible integration of AI in education. Overall, the field is moving towards a more nuanced understanding of the complex interplay between human and AI agents in educational settings, with a focus on fostering equitable, transparent, and effective learning environments. Noteworthy papers include 'Beyond the Hype: Critical Analysis of Student Motivations and Ethical Boundaries in Educational AI Use in Higher Education', which highlights the need for comprehensive AI literacy programs, and 'Scaling Equitable Reflection Assessment in Education via Large Language Models and Role-Based Feedback Agents', which presents a theory-grounded system for equitable feedback assessment.
Advancements in Human-AI Collaboration in Education
Sources
From Framework to Reliable Practice: End-User Perspectives on Social Robots in Public Spaces
Sabi\'a: Um Chatbot de Intelig\^encia Artificial Generativa para Suporte no Dia a Dia do Ensino Superior
Surveillance and Disability in Online Proctored Exams: Student Perspectives and Design Implications
Beyond the Hype: Critical Analysis of Student Motivations and Ethical Boundaries in Educational AI Use in Higher Education
AI as a component in the action research tradition of learning-by-doing
On the Influence of Artificial Intelligence on Human Problem-Solving: Empirical Insights for the Third Wave in a Multinational Longitudinal Pilot Study
Demystify, Use, Reflect: Preparing students to be informed LLM-users
Scaling Equitable Reflection Assessment in Education via Large Language Models and Role-Based Feedback Agents
Bridging the Skills Gap: A Course Model for Modern Generative AI Education
CollaClassroom: An AI-Augmented Collaborative Learning Platform with LLM Support in the Context of Bangladeshi University Students
Educators on the Frontline: Philosophical and Realistic Perspectives on Integrating ChatGPT into the Learning Space
Impact of UK Postgraduate Student Experiences on Academic Performance in Blended Learning: A Data Analytics Approach
The Unspoken Crisis of Learning: The Surging Zone of No Development
Knowing Ourselves Through Others: Reflecting with AI in Digital Human Debates
Examining the Usage of Generative AI Models in Student Learning Activities for Software Programming
The Quick Red Fox gets the best Data Driven Classroom Interviews: A manual for an interview app and its associated methodology
Exploring the Use of ChatGPT by Computer Science Students in Software Development: Applications, Ethical Considerations, and Insights for Engineering Education
Evaluating Generative AI for CS1 Code Grading: Direct vs Reverse Methods
Writing With Machines and Peers: Designing for Critical Engagement with Generative AI
Tracking financial crime through code and law: a review of regtech applications in anti-money laundering and terrorism financing
Navigating the Ethical and Societal Impacts of Generative AI in Higher Computing Education
Artificial Intelligence and Accounting Research: A Framework and Agenda
The Future of Development Environments with AI Foundation Models: NII Shonan Meeting 222 Report