AI+X: Guiding students to apply AI for cross-domain development through competitions

Professor Lin introduced "competition-based learning" into the 110-year teaching practice research project, which effectively improved students' "AI practical ability" and "competition-related abilities." However, Professor Lin found that most of the students chose to participate in the "Online Problem Solving Competition," which is relatively easy to achieve. Only two or three groups of students participated in the "Product Competition." Although the competition strengthens students’ AI practical ability, improving "competition-related abilities" is very limited. In addition, most students solve the online problem from the perspective of "data analysis" instead of understanding data and extracting data features from a cross-field perspective. Students do not have the opportunity to understand real industry problems and communicate with experts in this field. If students do not understand the real problems in this field and blindly improve the accuracy of the model. Will the target users accept this AI model? Can the AI model work in the industry? Based on the above problems, Professor Lin will extend the concept of "competition-based learning" this year. In the course, she will mainly introduce "industry problem-solving X talent problem-solving competition," leading students to connect with companies, understand the real request of industries, , solve real problems, and assist manufacturers in implementing AI technology. By "industry problem-solving X talent problem-solving competition," we want to cultivate the “AI+X cross-domain ability" of students and improve "AI implementation ability" and "expression ability" at the same time. We will carry out an "Industry Problem-Solving X Talent Problem-Solving Competition Effectiveness Analysis of AI+X Cross-domain Ability Cultivation Research."