Beyond Awareness: Using Generative Artificial Intelligence (AI) to Bridge the Career Interest Gap in Agricultural Education—A Conceptual Framework Based on a Systematic Scoping Review

บทคัดย่อ

This study aimed to: (1) explore how generative artificial intelligence (AI) can be leveraged to create engaging educational content that modernizes the image of agriculture, and (2) identify narrative-based strategies to reframe student perceptions of the field from a traditional practice to a high-tech “Agri-Tech” sector. A systematic scoping review was conducted, synthesizing foundational literature to establish a robust proof-of-concept. The analysis highlights a critical perception gap, reflecting trends in the Thai context, such as a documented 90% lack of career interest among students at Benchama Maharat School despite moderate awareness. Generative AI was characterized as a pedagogical tool capable of producing personalized learning pathways and immersive simulations. Thematic analysis underscored Narrative Transportation Theory as a key persuasive framework for shifting beliefs by reducing counterargument and fostering emotional engagement. Synthesizing these insights, the study proposes a conceptual framework that positions generative AI as a “machine of narrative transportation,” capable of immersing students in authentic Agri-Tech case studies. These findings support a transformative model for agricultural education and recommend the implementation of pilot programs, curriculum reform, and strategic policy support.