计算机与现代化

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在线教学中影响学习者学习效果的因素分析与实证研究

  

  1. 陕西师范大学计算机科学学院,陕西  西安  710062
  • 收稿日期:2016-12-28 出版日期:2017-09-20 发布日期:2017-09-19
  • 作者简介:陈国心(1991-),男,陕西西安人,陕西师范大学计算机科学学院硕士研究生,研究方向:大数据分析; 郝选文,男,讲师,博士,研究方向:ICT支撑教学; 裘国永,男,副教授,硕士生导师,博士,研究方向:信息技术教育; 吴振强,男,教授,博士生导师,博士,研究方向:ICT支撑教学。
  • 基金资助:
    中央高校基本科研业务费专项资金资助项目(GK201501008,GK261001236); 陕西省重点科技创新团队项目(2014KTC-18)

Factor Analysis and Empirical Study on Effect of Learner’s Learning in Online Teaching

  1. School of Computer Science, Shaanxi Normal University, Xi’an 710062, China
  • Received:2016-12-28 Online:2017-09-20 Published:2017-09-19

摘要: 在教育信息化、全球化的大环境下,如MOOC、可汗学院、高校精品课程等在线教育平台应运而生,这些平台每年都会产生海量的学习活动和教学管理数据,如何有效地利用这些数据提升学生的学习效率已经成为在线教育面临的挑战之一。目前,对在线学习过程中影响学习效果的因素,研究者持有不同的态度。本文利用某高校在线教育平台数据,探索与验证在线教学过程中影响学习者学习效率的相关因素。首先对目前在线教育情况与分析技术进行说明,再结合统计与关联规则挖掘算法的特点,将数据预处理后,通过统计与Apriori关联分析算法进行分析,并将结果可视化呈现。分析发现,教师批阅作业所给出的平均成绩与教师批阅的作业量负相关;学生完成在线作业普遍具有“延迟性”;学习效果与登录次数、在线时间和在线讨论次数正相关。最后通过分析结果,给出在线学习过程中提高学生学习效果的建议。

关键词: 教育现代化, 大数据, 数据挖掘, 可视化

Abstract: In the educational environment of informatization and globalization, online education platforms such as MOOC, Khan Academy, and Higher Quality Courses emerge. Improving the efficiency of student learning has become one of the challenges facing online education.At present, the researchers have different attitudes towards the factors that influence the learning effect in the online learning process. This paper explores and validates the factors that influence learners’ learning efficiency in the process of online teaching by using the online education platform data of a university. After analyzing the characteristics of statistical and association rules mining algorithm, the data are preprocessed, analyzed by statistical and Apriori correlation analysis algorithm, and the results are presented by visualization.The results show that the average scores of teachers’ marking work are negatively correlated with the workload of teachers’ marking. The students’ online work is generally “delayed”; the learning effect is positively correlated with the number of login, online time and online discussion. Finally, the results of the analysis are given to improve the learning effect of the online learning process.

Key words: education modernization, big data, data mining, visualization

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