智能技术赋能自我调节学习的内涵转型、制约瓶颈与发展路径

Research on Connotation Transformation,Bottlenecks and Development Paths of Self-regulated Learning Empowered by Intelligent Technology

以大数据、人工智能为代表的智能技术,已成为推动教与学变革的强大动力,也使自我调节学习发生的条件产生巨大的变化。为此,智能时代自我调节学习的内涵,应向“自我决定”“自我监控”“自我认同”与“自我调整”的方向转型。根据智能技术由“计算智能”到“感知智能”再到“认知智能”的三个发展阶段,智能技术赋能自我调节学习的功能框架,可划分为“计算智能+自我调节学习”“感知智能+自我调节学习”“认知智能+自我调节学习”三个层次。从其带来的风险因素出发,智能技术赋能自我调节学习的发展,应注重技术与学习者之间的良性互动,建立知识联结,激发学习者的学习内驱力;以过程性数据帮助学习者自知,以数据素养帮助学习者自省;通过自定义规则,促进人机协同智慧决策达成。对智能技术赋能自我调节学习的研究,可引导学习者适应环境变化,以实现更高层次的自我调节学习。

The intelligent technology represented by big data and artificial intelligence has become a powerful driving force for the reform of teaching and learning,which has greatly changed the conditions of self-regulated learning.Therefore,the connotation of self-regulation learning in the age of intelligence should be transformed to the direction of“self-determination”,“self-monitoring”,“self-identification”and“self-adjustment”.According to the three development stages of intelligent technology from computational intelligence to perceptual intelligence and then to cognitive intelligence,the functional framework of self-regulated learning empowered by intelligent technology can be divided into three levels:“computational intelligence+self-regulated learning”,“perceptual intelligence+self-regulated learning”,and“cognitive intelligence+self-regulated learning”.Starting from the risk factors,intelligent technology empowers the development of self-regulated learning should focus on the positive interaction between technology and learners,establish knowledge connection and stimulate learners’internal driving force;using process data to help learners’self-knowledge and data literacy to help learners to reflect;promote the man-machine collaborative intelligent decision-making through self-defined rules.This research can guide learners to adapt to environmental changes and achieve a higher level of self-regulated learning.