Vasiliy Znamenskiy, Rafael Niyazov and Joel Hernandez, The City University of New York, USA

This study investigates the educational potential of generative artificial intelligence (GenAI) platforms based on large language models (LLMs), such as ChatGPT, Claude, and Gemini, as tools for student-centred learning. Recognizing the current limitations of GenAI, particularly its propensity for generating inaccurate or misleading information—the paper proposes a novel instructional strategy: an interdisciplinary laboratory designed to foster critical evaluation of GenAI-generated outputs. In this pedagogical model, students engage with GenAI systems by posing questions or solving problems drawn from topics they have already studied and understand. Equipped with correct answers, students are positioned to assess the accuracy and relevance of AI-generated responses across multiple modalities, including text, images, and video. Students design challenging prompts and tasks that help compare the intellectual performance of various GenAI. This approach was implemented for a specially designed lab session within a general astronomy course for non-science majors. Multiple student groups completed the lab, demonstrating high levels of engagement, initiative, and critical thinking. Findings suggest that such activities not only deepen students’ comprehension of the scientific content of learning courses but also cultivate essential skills in digital literacy and critical interaction with AI technologies.

Generative Artificial Intelligence, GenAI, Large Language Models, LLMs, Critical Thinking, Digital Literacy, AI in Education, ChatGPT, Claude, Gemini, AI-augmented Learning, Interdisciplinary Education