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作 者:孙如卿 刘丹[1] SUN Ruqing;LIU Dan(School of Computer and Information Technology,Liaoning Normal University,Dalian Liaoning 116081)
机构地区:[1]辽宁师范大学计算机与信息技术学院,辽宁大连116081
出 处:《软件》2020年第12期224-229,共6页Software
基 金:国家社会科学基金“十三五”规划2016年度教育学一般课题“网络学习空间的内涵及其应用模式研究”(BCA160048);辽宁省教育厅科学研究项目“基于教育视频的学习者情感建模研究”(WJ2019010)。
摘 要:在线学习作为一种新型学习模式在“互联网+教育”时代下应运而生。如何利用数据挖掘技术分析学习者行为数据,已成为重要的研究热点。本研究以某高校“大学摄影基础”在线课程学习者为研究对象,基于大五人格量表获取学习者人格特质类型,提出人格特质类型与在线学习行为的相关分析;探索机器分类算法对在线学习者人格特质识别;采用数据挖掘工具对不同人格特质学习群体进行聚类分析。结果发现:人工神经网络算法对人格特质的识别准确率优于其他几种算法,在人格特质的综合识别效果也最佳;人格特质五个维度的识别准确率不同,其中尽责性人格特质识别准确率最高,神经质人格特质识别准确率最差;学习者主要划分为四种不同的人格特质群体,针对不同人格特质群体,教师可实施不同的干预策略。Online learning has emerged as a new learning model in the"Internet+education"era.How to use data mining technology to analyze learner behavior data has become an important research hotspot.This study takes the learners of"University Photography Fundamentals"online course in a university as the research object,and obtains the personality trait types of learners based on the Big Five Personality Scale,and proposes a correlation analysis between personality trait types and online learning behaviors;explores machine classification algorithms for online learning Personality traits identification;data mining tools were used to perform cluster analysis on different personality trait learning groups.The results show that the artificial neural network algorithm has a better recognition rate for personality traits than other algorithms,and has the best comprehensive recognition effect on personality traits.The recognition accuracy rates of the five dimensions of personality traits are different,including conscientious personality trait recognition.The highest accuracy rate and the lowest accuracy rate for identifying neurotic personality traits.Learners are mainly divided into four different personality trait groups.Teachers can implement different intervention strategies for different personality trait groups.
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