Research on Revolution Path of Deep-level Thinking Class Based on Large Language Models
The development of Large Language Model(LLM)technology is driving classroom teaching practice towards a three-player interaction model of"teacher-student-machine",transforming the role of teachers.With intelligent technologies,the traditional"Four Whys"questions begin to become"what"problems in the eyes of machines.Based on this,this study updates the"Four Whys"questions and utilizes them as the core driving task in the class.Using the"teacher-student-machine"model to create a transformation path to support the achievement of deep-level thinking class goals,this study was conducted in a"Learning Science"course from a university.The study results showed that learners have achieved high learning motivation,technology acceptance,and low cognitive load.At the same time,high groups have lower cognitive load compared to low groups,and can better handle the pressure brought by technology and complex tasks.Overall,this study provides reference for the implementation of deep-level thinking class supported by LLM.
intelligent eradeep-level thinking classstrategylarge language model
NETL
NSTL
万方数据
