"LIL": LLM-supported interdisciplinary learning in high school students

The integration of Generative Artificial Intelligence (GenAI) in education presents opportunities to enhance young learners' cognitive and problem-solving abilities, while fostering essential 21stcentury skills such as creativity, collaboration, and critical thinking. Despite some skepticism among educators, evidence shows growing adoption of large language models (LLMs) in education, indicating recognition of LLMs' potential to transform learning by enabling students to explore complex interdisciplinary topics. However, successful integration requires more than just access to these technologies; it necessitates a deep, critical investigation of the skills needed for effective and meaningful engagement with LLMs. This project aims to investigate how 16–18-year-old learners interact with LLMs while collaboratively addressing complex issues like climate change and misinformation. More specifically, our study seeks to explore the language, analytical and digital skills of students and their influence on learning outcomes when engaging in interdisciplinary LLM supported collaborative problem-solving. Using a mixed-methods approach, we will identify skills that influence effective LLM use in collaborative problem-solving tasks. The study will provide insights into the skills and interaction patterns that support critical and productive LLM engagement, guiding the development of instructional interventions to bridge the digital divide and enhance 21st-century skills among youth.