在线学习行为分析评价及其应用研究

发布时间：2018-05-19 13:19

本文选题：在线学习行为 + 学习行为模型　；参考：《华中师范大学》2011年硕士论文

【摘要】：20世纪80年代以来,计算机和网络技术的发展极大的促进了在线学习的发展应用。在线学习的蓬勃发展主要表现在各种成熟的在线学习平台的出现,如LAMS、Moodle、Sakai等和各种网络学习资源成指数的增加。这些在线学习平台虽然关注了各种学习工具的功能实现,注重了对知识内容的合理组织,也考虑到了对各种学习活动的支持,然而,这些在线学习平台都没有解决在线学习中的一个重大难题——在线学习中教师和学生在时空上处于分离状态,教师很难像传统课堂教学一样通过直接观察学习者的学习行为来发现其存在的问题并给予及时合理的帮助指导。要解决这一问题,必须对学习者的各种在线学习行为进行实时采集、分析、评价,从中挖掘出学习者的学习问题、学习模式和行为特征。虽然对各种在线学习行为进行分析评价的重要性早就得到了人们的认可,然而,由于问题的复杂性和条件的限制性,直到近年来才得到人们的关注。在国内,彭文辉等人组成的团队从理论上对在线学习行为的含义、组成和模型上做了比较深入的研究,然而其注重对所有的学习行为的分析建模,不具有针对性,在具体的应用时不具有可行性。在国外,Karin Anna Hummel、Jia-Jiunn Lo、Chen等则从微观的、具体的某一方面的学习行为入手,注重于对分析评价方法的应用研究上,这种研究方法最大的优点就是可行性较高,然而,由于其没有对学习行为在理论上做深入探讨,不便于对学习行为的深入分析。本文通过对现有在线学习行为分析评价研究成果的分析,结合在线学习行为的理论成果和应用目标,提出了面向分析评价目标的在线学习行为评价指标,该评价指标针对具体的三个分析评价目标,即在线学习结果评价、在线学习方式评价和在线平台使用评价,在此基础之上,进一步研究了在线学习行为分析评价的过程原理,介绍了现有的在线学习行为采集方法、分析评价方法,为在线学习行为分析评价提供了方法论依据。最后,将在线学习行为评价指标体系和在线学习行为分析评价模型应用于华中师范大学“研究生课程在线”学习平台,以“生物教学实验研究”网络课程作为实验对象,运用加权平均法从测试、作业和考试三个方面来计算学习者的学习结果,根据学习者的学习结果对学习者进行相对评价和绝对评价,使学习者清楚自己在班级里的学习情况和与预定目标的差距；运用weka平台的分类技术,根据采集到的数据,将学习者分为资源为主的自主学习方式、以讨论为主的探究式学习和混合式学习三种学习方式,就此作为学习者个性化学习推荐的依据。对学习平台使用的评价为在线学习平台的建设提出指导性的建议。通过对在线学习结果的评价、在线学习者学习方式的评价和在线学习平台的评价,为下一步智能学习推荐做了准备。
[Abstract]:Since 1980's, the development of computer and network technology has greatly promoted the development and application of online learning. The vigorous development of online learning is mainly reflected in the emergence of various mature online learning platforms such as LAMS Moodle Sakai and the exponential increase of various e-learning resources. Although these online learning platforms focus on the functional realization of various learning tools, the rational organization of knowledge content, and the support for various learning activities, however, None of these online learning platforms can solve one of the major problems in online learning: teachers and students are separated from each other in time and space. It is very difficult for teachers to find out the existing problems and give timely and reasonable guidance by observing learners' learning behaviors directly as in traditional classroom teaching. In order to solve this problem, it is necessary to collect, analyze and evaluate the learners' online learning behaviors in real time, so as to find out the learners' learning problems, learning patterns and behavior characteristics. Although the importance of analyzing and evaluating all kinds of online learning behaviors has been recognized for a long time, due to the complexity of the problem and the limitation of the conditions, it has not been paid much attention until recently. In China, the team composed by Peng Wenhui and others have done more in-depth research on the meaning, composition and model of online learning behavior in theory, but its emphasis on the analysis and modeling of all learning behaviors is not targeted. It is not feasible in specific application. In foreign countries, Karin Anna Hummeli Jia-Jiunn Loan Chen and so on focus on the research on the application of analytical and evaluation methods from the microcosmic and specific aspects of learning behavior. The greatest advantage of this research method is its high feasibility. However, It is not convenient to analyze the learning behavior because it does not make a thorough study on the learning behavior in theory. Based on the analysis of the existing research results of online learning behavior analysis and evaluation, combined with the theoretical results and application goals of online learning behavior, this paper puts forward the evaluation index of online learning behavior oriented to the analysis and evaluation goals. The evaluation index aims at three specific objectives of analysis and evaluation, that is, the evaluation of online learning results, the evaluation of online learning methods and the evaluation of the use of online platforms. On the basis of this, the process principle of online learning behavior analysis and evaluation is further studied. This paper introduces the existing online learning behavior collection methods and analysis and evaluation methods, which provides a methodological basis for online learning behavior analysis and evaluation. Finally, the online learning behavior evaluation index system and the online learning behavior analysis and evaluation model are applied to the "Graduate course online" learning platform of Central China normal University. The online course of "Biology Teaching experiment Research" is taken as the experimental object. The weighted average method is used to calculate the learners' learning results from three aspects: test, homework and examination. According to the learners' learning results, the relative and absolute evaluation of the learners is carried out. To make learners clear about their learning situation in class and the gap between them and their predetermined goals; to use the classification technology of the weka platform, according to the collected data, to divide the learners into resource-based autonomous learning methods. Discussion-based inquiry learning and mixed learning are the basis for learners' individualized learning recommendation. The evaluation of the use of the learning platform provides guiding suggestions for the construction of the online learning platform. Through the evaluation of the online learning results, the evaluation of the online learners' learning style and the evaluation of the online learning platform, it is prepared for the next step of the intelligent learning recommendation.
【学位授予单位】：华中师范大学
【学位级别】：硕士
【学位授予年份】：2011
【分类号】：G434

【引证文献】