摘要
学习习惯是学习者的个性化标签,是影响个性化学习服务精准化的重要因素。揭示数字环境下学习者个体学习习惯和群体学习习惯的新规律,对于实现教育向规模个性化教育转变具有重要意义。深层次挖掘学习习惯的新规律可以分解为构建科学有效的学习习惯测量模型以描述学习习惯的动态变化和探索学习习惯进化的动力学机制以发现学习习惯形成的规律等两个关键问题。为破解这两个关键问题,该文将学习分析和大数据分析方法融合到学习习惯的研究,从学习者的学习行为分析出发,通过采集海量的学习行为轨迹数据,构建可重用的多粒度数据共享模型。在此基础上,深层次分析数据的统计规律,构建学习习惯的测量模型,并基于该模型设计精准化的学习习惯干预模型,探索基于教育大数据的学习习惯动力学机制,溯源学生"互联网+教育"背景下的学习习惯发展规律。
Learning habit is a personalized label of the learner’s model and an important factor of affecting personalized learning service. It is of great significance to reveal the new rules of individual learning habits and group learning habits in the digital environment, so as to achieve the transformation from traditional education to large-scale individualized education. Deep mining the new rules of learning habits can be divided into two key scientific problems. One is building a scientific and effective measurement model to describe the dynamic changes of learning habits. The other is exploring the dynamic mechanism of learning habit evolution to discover the rules of learning habit formation. In order to solve these two key scientific problems, we combine the learning analytics and the large data analysis method into the study of learning habits, and put forward four research contents. The first is to construct a reusable and multi granularity data sharing model by collecting mass of learning behavior trajectory data. The second is to construct a six-dimension learning habit measurement model by analyzing the statistical laws of the data. The third is to design a precise learning habit intervention model based on the learning habit measurement model. The fourth is to explore the dynamic mechanism of learning habits based on big data, tracing the learning rules in the digital age.
作者
武法提
殷宝媛
黄石华
Wu Fati;Yin Baoyuan;Huang Shihua(School of Educational Technology,Beijing Normal University,Beijing 100875)
出处
《中国电化教育》
CSSCI
北大核心
2019年第1期70-76,共7页
China Educational Technology
基金
全国教育科学"十二五"规划教育部重点课题项目"基于教育大数据的学习分析工具设计与应用研究"(项目编号:DCA140230)
教育部人文社会科学研究规划青年基金项目"互联网+教育"背景下学生学习习惯的测评模型研究"(项目编号:18YJC880109)研究成果
关键词
学习习惯
动力学
大数据
学习分析
规模个性化教育
Learning Habits
Dynamics
Big Data
Learning Analysis
Large-scale Personalized Education
