深度知识追踪在适应性学习系统的应用  

Application of Deep Knowledge Tracking in the Adaptive Learning System

作　　者：李蓬 LI Peng(School of Electrical and Information Engineering,Beijing University of Civil Engineering and Architecture,Beijing 100044)

机构地区：[1]北京建筑大学电气与信息工程学院,北京100044

出　　处：《现代计算机》2021年第16期27-31,共5页Modern Computer

摘　　要：目前,适应性学习已成为在线教育智能化的一个发展趋势。适应性学习系统根据学习者的能力和需求提供合适的学习材料和学习干预,以优化学习过程。深度知识追踪采用深度学习技术分析学习者的知识水平,是构建适应性学习系统的基础。本文首先介绍深度知识追踪的基本模型和发展,然后描述适应性学习系统的基本结构,最后探讨深度知识追踪在适应性学习系统的应用,使学习者能够进行个性化学习。At present,adaptive learning has become a development trend of intelligent online education. The adaptive learning system can provide suitable learning materials and learning interventions according to the learners’ abilities and needs to optimize the learning process. Deep knowledge tracking uses deep learning technology to analyze the knowledge level of learners,which is the basis for constructing an adaptive learning system. First basic models and development of deep knowledge tracking are introduced,and then the basic structure of adaptive learning system is described,finally the application of deep knowledge tracking in the adaptive learning system is discussed,so as to enable learners to conduct personalized learning.

关 键 词：适应性学习系统 深度知识追踪 个性化学习 学习者模型 

分 类 号：G434[文化科学—教育学]