人工智能技术赋能个性化学习:意蕴、机制与路径

Artificial Intelligence Enabling Personalized Learning: Implications,Mechanisms and Pathways

基于人工智能技术的个性化学习是适应未来社会和促进个人发展的时代诉求。基于学习者个性特征的学习行为数据,运用海量数据分析和模型算法推荐,进行智能化选择、决策和服务,为学习者规划学习路径、供给学习资源、创设交互情境、提供实时反馈,并通过学习数据的二次供给同步调整和优化,实现个性化学习目标,是人工智能技术赋能个性化学习的闭环运行机制。从学习者基础数据、智能决策与个性服务、学习模型建构的动态层级关系看,人工智能技术赋能个性化学习的实践路径为:以数据挖掘精确绘制学习者个体数字画像,引导量化自我与量化学习;以人工智能的推荐算法与学习适应管理系统,实现智能决策与个性化服务;通过机器学习构建深度学习的人本生态系统,促进学习从浅表走向纵深。

Personalized learning based on artificial intelligence technology is the demand of the times to adapt to the future society and promote individual development.Based on the learning behavior data of learners’personality characteristics,it applies massive data analysis and model algorithm recommendation to carry out intelligent choice,decision and service so as to set learning path,provide learning resources,create interactive situation and give real-time feedback for learners;it realizes personalized learning objectives through synchronous adjustment and optimization of secondary supply of learning data.Such is the closed-loop operating mechanism of artificial intelligence technology enabling personalized learning.By combing the dynamic hierarchical relationship of learners’basic data,intelligent decision making and personalized service,and learning model construction,this paper proposes the practical approaches ofits enabling personalized learning:1)to accurately draw the digital portrait of learners by data mining,and guide quantitative self and quantitative learning;2)to adapt management system through the recommendation algorithm and the learning of artificial intelligence for intelligent decision-making and personalized service;3)to build a humanistic ecosystem of deep learning through machine learning for a shift from superficial to deep.