人工智能环境下的学习发生机制

Learning Mechanism Under Artificial Intelligence Environment

人工智能正在从外置性技术辅助走向内融性技术渗透,促使学习者所使用的规则、方法、技巧及调控形式发生变化,对学习条件、学习过程、知识获得、迁移与问题解决等带来影响,尤其对学习过程中信息输入、加工处理、信息输出和反馈四个基本环节产生较大的影响,因此需要重新认识人工智能环境下的学习发生机制。人工智能的发展使得学习环境设计从工具性思维转向人工智能思维,人工智能提供的逼真、丰富的学习环境,促使学习从知识学习走向知识应用场景的学习;人机协同智能结构的形成将分担原本全部由学习者大脑完成的认知活动,形成融合智能,改变信息加工过程;人工智能延展了效应器官与外部信息交流的可达性,支持多路径的信息输入,诱发多重学习表现,全方位、全过程采集学习者在体验、实践、交互中的过程数据,促进学习者自我认知发展,提供实时的个性化反馈与评估。人工智能应用于学习不能仅停留在知识获取、技能习得上,还需要聚焦问题解决、反思、批判性和创新等能力的培养,避免学习者过度依赖人工智能而丧失自主学习与思考的能力。

Artificial intelligence is moving from external technology assistance to intrinsic technology penetration, which changes the rules, methods, techniques and control forms used by learners, and brings impacts on learning conditions, learning process, knowledge acquisition, knowledge migration and problem solving, especially on the four basic links of the learning process including information input, information processing, information output and feedback. Therefore, it is necessary to get a new understanding of the learning mechanism under the artificial intelligence environment. The development of artificial intelligence has changed the design of learning environment from instrumental thinking to artificial intelligence thinking. The realistic and rich learning environment provided by artificial intelligence has promoted the shift of learning from knowledge learning to knowledge application scenarios. The formation of human-computer collaborative intelligent structure will divide the cognitive activities originally all completed by the learners’brain to form a fusion of intelligence and change the information processing process. Artificial intelligence extends the accessibility of the effector and external information exchange, supports multi-path information input, induces multiple learning performance, and comprehensively collects the leaners’data in the whole process of experience, practice and interaction, which promote the learners’self-cognitive development and provide them real-time personalized feedback and evaluation. The application of artificial intelligence to learning can not only remain on knowledge acquisition and skill acquisition, but also should focus on the cultivation of problem solving, reflection, critical ability and innovation to avoid the learners’over-dependence on artificial intelligence which will make learners lose the ability to learn and to think independently.