Change or Crisis:Large Language Model Empowering University Teaching and Its Limits—A Case Study Based on Stanford University
Generative artificial intelligence,represented by large language models,is rapidly changing the production method of"human"and their education in university teaching,shaping a new model of talent training in the global higher education field.Based on the case of Stanford University,it is found that the key to empowering teaching with large language models lies in the computing power of large data sets to accelerate precise teaching,the symbolic language system to support full-time services,the neural network model to promote personalized guidance,and the intelligent emotional technology to achieve humanized evaluation,resulting in the teaching transformation impact characterized by intelligent emergence,boundless exploration,generative interaction and affective feedback.But at the same time,the limits of model application such as the"illusion"of artificial intelligence,the"cognitive bias"of machines,and the"out-of-control"of artificial intelligence may lead to multiple risks of distorted teaching content,ideological crisis and alienation of subject relations,giving rise to a new teaching crisis under the technological revolution.Based on this,universities in the era of artificial intelligence should build a systematic path from the four-dimensional relationship of"subject-goal-system-mechanism",promote generative teaching innovation and exploration,improve the credit rating of teaching models,and build a diversified collaborative teaching ecology,so as to change university teaching from human-computer collaboration to human-computer integration,thereby demonstrating the technological progressivism value of university teaching empowered by the large language models.
Large Language ModelUniversity TeachingGenerative Artificial IntelligenceTeaching EcologyHuman-Machine Integration
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