Abstract:

[Purpose/Significance] The rapid development of generative artificial intelligence (GenAI) has led to a growing demand for AI literacy in various fields. However, current AI literacy courses often fail to adequately address the diverse needs of students with different academic backgrounds, expertise, and learning levels. This research aims to design an AI literacy curriculum that balances knowledge dissemination with skill development, ensuring that students can not only understand basic concepts but also apply them in practice. [Method/Process] This study is based on the design of Nanjing University's "Exploration of Frontier Applications of Generative Artificial Intelligence" course, which adopts the "knowledge-skills" navigation framework. The course is divided into four progressively advanced levels: foundational cognition, core understanding, tool application, and innovative development. The foundational cognition level systematically organizes the four key knowledge modules involved in generative artificial intelligence: Machine Learning, Neural Networks, Deep Learning, and Natural Language Processing, helping students to build an initial cognitive framework for GenAI. The core understanding level explores advanced topics in GenAI, covering four main modules: basic model pre-training, downstream task adaptation, human-AI value alignment, and AI agents. This aims to enhance students' comprehensive understanding of the technical principles, application methods, and ethical considerations, providing the necessary technical support and conceptual tools for real-world applications. The tool application level consists of three modules: classification of intelligent tools, tool acquisition and use, and derived applications. It gradually guides students from analyzing the characteristics of tools and their use to exploring state-of-the-art applications in multi-modal, multi-scenario, and integrated contexts. Finally, the innovative development level is the final practical stage of the GenAI learning system and includes environment configuration, basic processes, and frontier development. This includes configuration of hardware and software environments, basic steps for development tasks, and advanced practices for complex functions, forming a complete chain from basic support to high-end applications. Following the "knowledge-skills" navigation, the course will also include teaching designs such as concept cognition modules, multi-modal generation and application skill modules, advanced generative AI knowledge and skill modules, and generative AI governance modules, along with the development of corresponding online open courses, open educational resources, and experimental equipment resources. [Results/Conclusions] The "knowledge-skills" navigation framework effectively enhances students' AI literacy by successfully bridging the gap between theoretical knowledge and practical application. The modular structure of the course, combined with multi-modal learning and hands-on practice, effectively meets the diverse learning needs of students. The course allows students to gradually build a knowledge system from basic concepts to advanced skills, fostering a comprehensive understanding of AI technologies.

Key words: generative artificial intelligence, AI literacy, general education, curriculum design, digital literacy education