基于教育大数据的学习习惯动力学研究框架
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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.
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.
引文
[1]陈丽,王志军,郑勤华.“互联网+时代”教育技术学的学科定位与人才培养方向反思[J].电化教育研究,2017,38(10):5-11.
[2]吴刚.大数据时代的个性化教育:策略与实践[J].南京社会科学,2015,(7):104-110.
[3]托马斯·库恩.科学革命的结构[M].北京:北京大学出版社,2003.
[4]殷宝媛,陈丽.在线教育自组织系统的科学原理与趋势分析[J].电化教育研究,2018,39(3):56-61.
[5]叶圣陶.如果我当教师[M].北京:教育科学出版社,2012.56.
[6][美]Marc Prensky,胡智标,王凯.数字土著数字移民[J].远程教育杂志,2009,(2):48-50.
[7]佟士凡.重视学法面向未来--语文教学面临的一个重要课题[J].语文教学通讯,1992,(1):39-41.
[8]白文飞.应用激励性评价方法促进中小学生学习习惯的养成[J].教育理论与实践,2014,(7):45-46.
[9]赵丽霞.小学生学习习惯培养研究[J].教育探索,2009,(5):58-59.
[10]Verplanken,B.,&Aarts,H..Habit,attitude,and planned behavior:Is habit an empty construct or an interesting case of goal-directed automaticity?[J].European Review of Social Psychology,1999,(10):101-134.
[11]Aarts H,Paulussen T,Schaalma H.Physical exercise habit:on the conceptualization and formation of habitual health behaviours[J].Health Education Research,1997,12(3):363-374.
[12]Neal D T,Wood W,Quinn J M.Habits:A Repeat Performance[J].Current Directions in Psychological Science,2006,15(4):198-202.
[13]田澜.小学生学习习惯问卷的编制[J].心理学探新,2010,(5):90-94.
[14]Mc Dermott PA.National scales of differential learning behaviors among American children and adolescents[J].School Psychology Review,1999,28(2):280-291.
[15]?akiroglu,ünal.Analyzing the Effect of Learning Styles and Study Habits of Distance Learners on Learning Performances:A Case of an Introductory Programming Course[J].International Review of Research in Open&Distance Learning,2014,15(4):161-185.
[16]牟智佳,武法提.教育大数据背景下学习结果预测研究的内容解析与设计取向[J].中国电化教育,2017,(7):26-32.
[17]李彤彤,黄洛颖等.基于教育大数据的学习干预模型构建[J].中国电化教育,2016,(6):16-20.
[2]吴刚.大数据时代的个性化教育:策略与实践[J].南京社会科学,2015,(7):104-110.
[3]托马斯·库恩.科学革命的结构[M].北京:北京大学出版社,2003.
[4]殷宝媛,陈丽.在线教育自组织系统的科学原理与趋势分析[J].电化教育研究,2018,39(3):56-61.
[5]叶圣陶.如果我当教师[M].北京:教育科学出版社,2012.56.
[6][美]Marc Prensky,胡智标,王凯.数字土著数字移民[J].远程教育杂志,2009,(2):48-50.
[7]佟士凡.重视学法面向未来--语文教学面临的一个重要课题[J].语文教学通讯,1992,(1):39-41.
[8]白文飞.应用激励性评价方法促进中小学生学习习惯的养成[J].教育理论与实践,2014,(7):45-46.
[9]赵丽霞.小学生学习习惯培养研究[J].教育探索,2009,(5):58-59.
[10]Verplanken,B.,&Aarts,H..Habit,attitude,and planned behavior:Is habit an empty construct or an interesting case of goal-directed automaticity?[J].European Review of Social Psychology,1999,(10):101-134.
[11]Aarts H,Paulussen T,Schaalma H.Physical exercise habit:on the conceptualization and formation of habitual health behaviours[J].Health Education Research,1997,12(3):363-374.
[12]Neal D T,Wood W,Quinn J M.Habits:A Repeat Performance[J].Current Directions in Psychological Science,2006,15(4):198-202.
[13]田澜.小学生学习习惯问卷的编制[J].心理学探新,2010,(5):90-94.
[14]Mc Dermott PA.National scales of differential learning behaviors among American children and adolescents[J].School Psychology Review,1999,28(2):280-291.
[15]?akiroglu,ünal.Analyzing the Effect of Learning Styles and Study Habits of Distance Learners on Learning Performances:A Case of an Introductory Programming Course[J].International Review of Research in Open&Distance Learning,2014,15(4):161-185.
[16]牟智佳,武法提.教育大数据背景下学习结果预测研究的内容解析与设计取向[J].中国电化教育,2017,(7):26-32.
[17]李彤彤,黄洛颖等.基于教育大数据的学习干预模型构建[J].中国电化教育,2016,(6):16-20.