中国电化教育

“量化自主学习”是量化自我理念在人工智能技术发展与深度媒介化学习语境下的新形态,表明了青年群体在技术赋能下对学习过程的系统性自我管理。该研究基于驯化理论框架和自我调节学习理论,通过质性研究方法,系统考察青年群体如何通过技术驯化、空间融入、惯例整合、社群勾连与内化建构五个维度完成量化技术的日常化融入。研究发现,青年在技术实践中既发展出数据驱动的自主学习能力,也面临技术逻辑对学习本质的“反向驯化”风险。据此,从自我管理与AI素养培育两个维度提出建议:青年群体需实现由数据服从到技术驯化的行为转向,强化时空边界与社群互动策略,以促进自主学习能力持续优化;发展“认知—技能—价值”相统一的AI素养进阶框架,在技术使用中保持人的主体性与价值判断,以实现技术与学习的良性共生。

“Quantified autonomous learning” is a new form of the quantified self concept in the context of the development of artificial intelligence technology and deep media-based learning, indicating that the youth group is systematically self-managing the learning process with the empowerment of technology. This study, based on the framework of the domestication theory and the theory of self-regulated learning, uses qualitative research methods to systematically investigate how the youth group completes the daily integration of quantified technology through five dimensions: technological domestication, spatial integration, routine integration, community connection, and internalization construction. The research finds that while the youth develop data-driven autonomous learning abilities in technological practice, they also face the risk of “reverse domestication” of the essence of learning by the technological logic. Based on this, recommendations are proposed from two dimensions—selfmanagement and AI literacy development: Young people need to shift their behavior from passive compliance with data to active technological domestication, strengthen strategies for spatial-temporal boundaries and community interaction, and thereby continuously enhance autonomous learning capabilities. Furthermore, an advanced framework for AI literacy should be developed that integrates cognition, skills, and values, ensuring human agency and value judgment in technology use to achieve a positive symbiosis between technology and learning.