The Future of Cine-Education: An AI-Enhanced Project-Based Learning Model for Modern Filmmakers

Abstract

Artificial intelligence is increasingly influencing creative media production and higher education. However, undergraduate filmmaking education still lacks a structured approach for integrating AI into project-based learning across the full production workflow. This study investigates the first phase of a broader doctoral research project and aims to identify the core components of an AI-enhanced project-based learning model for undergraduate filmmaking education in China. A mixed-methods developmental research design was employed. Data were collected through document analysis, stakeholder questionnaires, open-ended responses, and expert evaluation. A total of 350 student questionnaires were distributed, and 291 valid responses were retained for analysis. Additional data were obtained from 80 film instructors, 60 film employers or industry representatives, and 15 model review experts. The findings revealed five cross-group themes: authentic project experience, integrated filmmaking skill development, AI-supported process assistance, collaboration and role-based participation, and continuous feedback and revision. These themes were translated into design requirements and then organized into a four-layer instructional framework consisting of input, process, support, and outcome layers. Expert evaluation indicated that the preliminary model components were appropriate, relevant, and suitable for further development. The study contributes a stakeholder-informed framework for integrating AI into project-based filmmaking education and provides a foundation for subsequent classroom implementation and empirical validation.