研学实践教育研究 新进展
Jing Zhou (Author)
artificial intelligence education, technology research and study, scenario-based learning, Heilongjiang Kunpeng Ecological Innovation Center, deep learning
31-05-2026
In the era of rapid development of artificial intelligence (AI) technology and the nation's vigorous advocacy of technological self-reliance and self-improvement, cultivating future citizens with AI literacy has become the core mission of basic education. However, AI education in primary and secondary schools currently faces practical dilemmas such as content isolation, virtualized scenarios, and hollowed-out values. Research-based learning, with its authenticity, experiential nature, and interdisciplinarity, provides an ideal "second classroom" for AI education. This paper takes the Heilongjiang Kunpeng Ecological Innovation Center, a national-level research-based learning and educational base, as a typical case to deeply analyze its "cutting-edge leading" AI research-based learning model. By constructing a four-stage deep learning model of "scenario restoration - embodied experience - project creation - ethical speculation", and combining its hardware infrastructure, which includes a 370 million yuan investment, a building area of 13,000 square meters, and 14 AI experience scenarios, as well as a graded curriculum system covering primary and junior high schools, this paper systematically expounds how the Longjiang region transforms cutting-edge technological resources into inclusive educational momentum. This study aims to provide theoretical references and practical paradigms for promoting AI technology research-based learning in the region and building a new collaborative education ecosystem of "government-enterprise-school".
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