[1]涂冬波,张 咏*.基于认知诊断的自适应学习材料智能推送算法研究[J].江西师范大学学报(自然科学版),2020,(01):20-27.[doi:10.16357/j.cnki.issn1000-5862.2020.01.05]
　TU Dongbo,ZHANG Yong*.The Material Recommendation System for Adaptive Learning Based on Cognitive Diagnosis[J].Journal of Jiangxi Normal University:Natural Science Edition,2020,(01):20-27.[doi:10.16357/j.cnki.issn1000-5862.2020.01.05]
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基于认知诊断的自适应学习材料智能推送算法研究()
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《江西师范大学学报》（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2020年01期
页码:
20-27
栏目:
心理与教育测量
出版日期:
2020-02-10

文章信息/Info

Title:
The Material Recommendation System for Adaptive Learning Based on Cognitive Diagnosis
文章编号:
1000-5862(2020)01-0020-08
作者:
涂冬波; 张 咏*
江西师范大学心理学院,江西 南昌 330022
Author(s):
TU Dongbo; ZHANG Yong*
College of Psychology,Jiangxi Normal University,Nanchang Jiangxi 330022,China
关键词:
认知诊断;  自适应学习;  材料推送;  遗传算法;  多岛遗传算法
Keywords:
cognitive diagnosis;  adaptive learning;  material recommendation;  genetic algorithms;  multi-island genetic algorithm
分类号:
B 841
DOI:
10.16357/j.cnki.issn1000-5862.2020.01.05
文献标志码:
A
摘要:
将认知诊断和自适应学习相结合,利用认知诊断方法先诊断学习者对知识的掌握情况,然后依据遗传算法和多岛遗传算法为每个学习者智能化提供合适的学习材料,提出了基于认知诊断框架下的自适应学习材料智能推送算法.通过Monte Carlo模拟实验考察了新算法的科学性及其效果,研究结果表明:(i)基于认知诊断框架下的自适应学习材料智能推送算法具有较理想的效果;(ii)遗传算法和多岛遗传算法选取的学习材料具有低惩罚函数值和高学习材料匹配的正确率;(iii)遗传算法和多岛遗传算法选取的材料比随机算法更加适合学习者.
Abstract:
Cognitive diagnosis and adaptive learning are combined,cognitive diagnosis method is used to diagnose learners' knowledge mastery,and then genetic algorithm or multi-island genetic algorithm is used to provide appropriate learning materials for each learner.The material recommendation system for adaptive learning based on cognitive diagnosis is built.In this paper,the Monte Carlo simulation experiment is used to investigate the effect of adaptive algorithm based on cognitive diagnosis.The research results show that the adaptive material recommendation algorithm based on cognitive diagnosis has an ideal effect.Learning materials selected by genetic algorithm and multi-island genetic algorithm have low penalty function value and high success rate.The selected materials based on genetic algorithm and multi-island genetic algorithm are more suitable for learners than the random algorithm.

参考文献/References:

[1] Yang Xiangdong,Embretson S E.Construct validity and cognitive diagnostic assessment[EB/OL].[2019-06-16].https://smartech.gatech.edu/handle/1853/34250.
[2] 廖轶.面向基础教育的自适应学习服务系统研究与应用[D].北京:北京交通大学,2017.
[3] 汪文义,张华华.统计测量视角下考试公平推动教育公平的对策[J].江西师范大学学报:自然科学版,2017,41(4):383-393.
[4] Chen Nianshing,Kinshuk,Wei Chunwan,et al.Mining e-learning domain concept map from academic articles[J].Computers and Education,2008,50(3):1000-1021.
[5] 杨现民,余胜泉.学习元平台的语义技术架构及其应用[J].现代远程教育研究,2014(1):89-99.
[6] Peter Brusilovsky.Methods and techniques of adaptive hypermedia[J].User Modeling and User-Adapted Interaction,1996,6(2/3):87-129.
[7] Zuo Xingquan,Zhang Guoxiang,Tan Wei.Self-adaptive learning PSO-based deadline constrained task scheduling for hybrid IaaS cloud[J].IEEE Transactions on Automation Science and Engineering,2014,11(2):564-573.
[8] Ritz H,Nassar M R,Frank M J,et al.A control theoretic model of adaptive learning in dynamic environments[J].Journal of Cognitive Neuroscience,2018,30(10):1-17.
[9] Wan Shanshan,Niu Zhendong.A learner oriented learning recommendation approach based on mixed concept mapping and immune algorithm[J].Knowledge-Based Systems,2016,103:28-40.
[10] 涂冬波,蔡艳,戴海崎,等.现代测量理论下4大认知诊断模型述评[J].心理学探新,2008,28(2):64-68.
[11] 原志强,赵春艳.2种改进的模拟退火算法求解大值域约束满足问题[J].计算机应用研究,2017,34(12):3611-3616.
[12] 王兴华.惩罚函数法的改进算法及应用研究[D].秦皇岛:燕山大学,2009.
[13] 李邈.基于遗传规划和遗传算法的跨单元调度方法[D].北京:北京理工大学,2016.
[14] 张芳.基于改进GA的模糊神经网络参数学习算法及其应用的研究[D].长沙:中南大学,2007.
[15] 潘福成,郝博,梁英,等.基于动态岛屿群体模型的并行遗传算法[J].计算机工程,2002,28(10):72-73.
[16] Jimmy de la Torre.The generalized DINA modelframework[J].Psychometrika,2011,76(2):179-199.
[17] Torre J D L.The generalized DINA model framework[J].Psychometrika,2011,76(2):179-199.
[18] Ma Wenchao,Jimmy Torre.A sequential cognitive diagnosis model for polytomousresponses[J].British Journal of Mathematical and Statistical Psychology,2016,69(3):253-275.
[19] Bian Cunling,Dong Shijun,Li Chunrong,et al.Generation of adaptive learning path based on concept map and immune algorithm[EB/OL].[2019-06-16].10.1109/ICCSE.2017.8085526.
[20] Scrucca L.GA:a package for genetic algorithms in R[J].Journal of Statistical Software,2013,53(4):1-37.
[21] 韩红桂,卢薇,乔俊飞.一种基于种群多样性的粒子群优化算法设计及应用[J].信息与控制,2017,46(6):677-684.
[22] 汤伟,胡祥满.基于模拟退火算法的PID参数优化研究[J].组合机床与自动化加工技术,2018(4):92-96,101.

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　ZHAN Peida,DING Shuliang,WANG Lijun.The Ideal Mastery Pattern for Polytomous Attributes with Hierarchical Structure Incorporating Mastery Level Restriction[J].Journal of Jiangxi Normal University:Natural Science Edition,2017,(01):289.

备注/Memo

备注/Memo:
收稿日期:2019-09-28
基金项目:国家自然科学基金(31660278,31760288,31960186)和江西省教育厅人文社科重点(重大)课题(JD17077)资助项目.
作者简介:涂冬波(1978-),男,江西南昌人,教授,博士,博士生导师,主要从事心理统计与测量的研究.E-mail:tudongbo@aliyun.com
通信作者:张 咏(1993-),男,安徽芜湖人,硕士研究生,主要从事心理测量与评价方面的研究.E-mail:799349507@qq.com
更新日期/Last Update: 2020-02-10