Requirements and challenges for hybrid intelligence: A case-study in education

Area of Science:

• Educational Technology
• Artificial Intelligence in Education
• Human-Computer Interaction

Background:

• The widespread potential of Artificial Intelligence (AI) is recognized, yet its practical application in everyday educational settings remains limited.
• Current autonomous systems struggle with the complexity of professional teaching, highlighting the need for specialized AI capabilities.
• Dedicated AI excels in specific tasks, suggesting a collaborative human-AI model for educational advancement.

Purpose of the Study:

• To investigate the practical implementation of a hybrid approach combining human educators and AI in secondary education.
• To explore the development of AI systems that can effectively support the learning process by interacting knowledgeably with students.
• To define the specific roles and tasks suitable for AI and human teachers within a collaborative educational framework.

Main Methods:

• Case study focusing on secondary education students acquiring systems thinking skills.
• Development and application of a novel pedagogical approach integrating AI.
• Analysis of AI capabilities and limitations in supporting specific learning objectives.

Main Results:

• Identified specific types of AI suitable for educational collaboration.
• Delineated tasks where AI can effectively support learning, such as specific skill acquisition.
• Highlighted tasks that remain uniquely suited for human teachers, emphasizing the irreplaceable role of educators.

Conclusions:

• A hybrid approach is feasible and beneficial for integrating AI into secondary education.
• AI can effectively augment teaching by handling specific tasks, freeing teachers for more complex pedagogical roles.
• Careful consideration of AI capabilities and limitations is crucial for successful human-AI collaboration in education.