Application, Risks, and Prospects of Generative Artificial Intelligence in Education: A Case Study of DeepSeek

The generative AI (GAI) technology represented by DeepSeek is developing rapidly and gradually entering the field of education. However, systematic examination of its applicability in education remains limited. Drawing on risk theory and human-computer collaboration theory, this study conducts a systematic review of the literature on DeepSeek's current educational applications. It analyzes the positive effects of DeepSeek in three dimensions: students, teachers, and classrooms, including supporting cognitive training, reducing teachers' repetitive workload, and facilitating contextualized knowledge construction. At the same time, its application entails potential risks such as educational data leakage, misinformation caused by algorithmic hallucination, the digital divide, threats to academic integrity, and weakened teacher roles. The study concludes that DeepSeek should be positioned as an auxiliary cognitive tool in education rather than a replacement for human teaching. Accordingly, recommendations are proposed at three levels: institutional data governance and privacy protection, technical improvement of algorithmic transparency, and educational evaluation reform and critical digital literacy cultivation.