## 5 Limitations of and Optimization Strategies for AI-Driven High School Geography Research Design
### Optimization Strategy  
In view of the above limitations, we propose the following optimization strategies to further improve the application effect of AI in geographical research design. 1. Improve data quality and technology platforms  
To ensure the integrity and real-time nature of the data, a regional ecological data sharing platform can be established to cooperate with scientific research institutions and government departments. For example, cooperation with the Yellow (Bohai) Sea Bird Conservation Organization to obtain more accurate migratory bird data. This will not only help improve the accuracy of the AI model, but also promote the coordinated development of ecological protection and scientific research. At the same time, in order to support the smooth progress of research and study activities, it is necessary to provide a stable internet environment and high-performance equipment, especially in remote areas. Considering the special conditions in these areas, the application of portable devices and offline functions is particularly important, can effectively ensure the smooth development of research and study activities, and can continue to collect and analyze data even in an unstable network environment. 2. Strengthen students' technical training  
During the pre-trip thinking stage, special training on the use of AI should be introduced to ensure that students master basic data processing and model operation skills. This will help students use AI more confidently in research and study activities, thereby improving learning efficiency and task completion. At the same time, in order to adapt to the differences in the abilities of different students, tiered teaching can be designed to provide basic and challenging task options. In this way, students can choose appropriate tasks to participate in according to their ability levels, which can ensure that students with weaker basic abilities can also obtain an effective learning experience, and sufficient challenges for students with higher abilities can be provided, stimulating their innovative thinking and interest in in-depth exploration. This tiered design helps to enhance each student's sense of participation and accomplishment. 3. Improve teachers' AI application capabilities  
In order to improve teachers' AI application capabilities, systematic AI technology application training can be provided to teachers, covering GIS operations, ecological model construction, dynamic data analysis, and other aspects. This will help teachers better master the use of AI and improve their technical application capabilities in teaching. At the same time, in order to reduce the technical burden on teachers, an AI teaching assistant system can be introduced to assist teachers in task assignment, data analysis, and feedback report generation. With the support of AI teaching assistants, teachers can focus more on teaching design and student guidance, improve teaching efficiency and effectiveness, and ensure the smooth application of AI technology in the classroom. 4. Enrich AI functions and teaching scenarios  
In order to stimulate students' interest in learning, personalized learning resource recommendation options can be provided to students. For example, relevant case studies and the latest scientific research results in the field of ecological protection can be provided so that students can be exposed to richer and more cutting-edge knowledge. This can not only enhance students' interest in the subject, but can also help them better understand practical applications and scientific research trends. At the same time, AI technology can be combined with other disciplines (such as biology, environmental science, etc.) to design interdisciplinary tasks. This interdisciplinary integration approach helps to improve students' comprehensive literacy and cultivate their systematic thinking and ability to solve complex problems.