混合式教学模式下学生个人大数据的应用研究
发布时间：2018-11-12 12:45
【摘要】：混合式教学模式已逐步在国内普通高校推广和开展,成为课程教学模式改革的主要方向。随着信息技术的发展,大数据的概念和价值理念逐步被大众所接受,并且,已经渗透到医学、建筑、金融、教育等各个领域。在整个教育活动过程中产生的,可用于发展教育、创新教育、优化教育,拥有无法衡量的潜在价值的所有教育数据,都是大数据的子集,都是教育大数据。教育大数据分为广义的教育大数据和狭义的教育大数据。广义的教育大数据是指一切与教育相关的或教育过程中产生的所有数据:主要包括教育活动过程中的数据、在教育管理活动中采集到的数据、在科学研究活动中采集到的数据、在校园生活中产生的数据等所有来源于教育活动中学生的行为数据;狭义的教育大数据则可以是与学生学习相关的一切数据,即学生个人大数据:主要包括线上操作日志,线上业务数据;线下的课堂实录、纸质资料(获奖证书、请假条、小纸条)等。本文的研究数据就是狭义的教育大数据。目前,教育领域大数据应用的大体状况为:教师教学评价、决策绝大多数都是以教学者单方面的主观判断作为依据,学生反思的依据也仅仅只有成绩。针对上述状况,本文尝试探索混合式教学模式下学生个人大数据的应用。本文主要在混合式教学模式下,从教师学生评价、教学反馈、学生反思三个方面对学生个人大数据在教和学的应用展开研究。本文第一部分提出了在混合式教学模式研究学生个人大数据的意义;第二部分阐述了混合式教学模式的特征,并对混合式教学支撑平台——云课堂的功能进行了介绍;第三部分主要介绍学生个人大数据的应用模型,重点说明了存储模型和分析模型;第四部分详细讨论了学生个人大数据在教师对学生的评价、教师利用数据进行教学反思,调整教学策略及学生利用综合性数据以及过程性数据进行学习反思、学习计划调整三个方面的具体的应用。
[Abstract]:The mixed teaching mode has been popularized and carried out gradually in the domestic universities and colleges, and has become the main direction of the reform of the curriculum teaching mode. With the development of information technology, big data's concept and value concept are gradually accepted by the public, and have penetrated into the fields of medicine, architecture, finance, education and so on. All the educational data, which can be used to develop education, innovate education, optimize education and have unmeasurable potential value, are a subset of big data and all of them are educational big data. Educational big data is divided into the broad sense of educational big data and the narrow sense of educational big data. In a broad sense, educational big data refers to all the data related to education or produced in the process of education: mainly including the data in the course of educational activities, the data collected in educational management activities, and the data collected in scientific research activities. The data generated in the campus life are all derived from the behavior data of the middle school students in the educational activities; In a narrow sense, big data can be all the data related to the students' study, that is, the student individual big data: mainly includes the online operation log, the on-line business data; Below-line classroom record, paper materials (award-winning certificate, note, note) and so on. The research data of this paper is educational big data in narrow sense. At present, the general situation of big data's application in the field of education is as follows: teachers' teaching evaluation and decision-making are mostly based on the unilateral subjective judgment of the teacher, and the students' reflection is based on only achievements. In view of the above situation, this paper tries to explore the application of individual big data in the mixed teaching mode. In this paper, the application of individual big data in teaching and learning is studied from three aspects: teacher and student evaluation, teaching feedback and student reflection under the mixed teaching mode. The first part of this paper puts forward the significance of studying individual big data in the mixed teaching mode, the second part expounds the characteristics of the mixed teaching model, and introduces the function of cloud classroom, which is the supporting platform of hybrid teaching. The third part mainly introduces the application model of student individual big data, focusing on the storage model and analysis model; The fourth part discusses the students' individual big data's evaluation of students in detail, teachers use data to reflect on teaching, adjust teaching strategies, and students use comprehensive data and process data to reflect on learning. The specific application of learning plan adjustment in three aspects.
【学位授予单位】：华中师范大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：G434
本文编号：2327144
[Abstract]:The mixed teaching mode has been popularized and carried out gradually in the domestic universities and colleges, and has become the main direction of the reform of the curriculum teaching mode. With the development of information technology, big data's concept and value concept are gradually accepted by the public, and have penetrated into the fields of medicine, architecture, finance, education and so on. All the educational data, which can be used to develop education, innovate education, optimize education and have unmeasurable potential value, are a subset of big data and all of them are educational big data. Educational big data is divided into the broad sense of educational big data and the narrow sense of educational big data. In a broad sense, educational big data refers to all the data related to education or produced in the process of education: mainly including the data in the course of educational activities, the data collected in educational management activities, and the data collected in scientific research activities. The data generated in the campus life are all derived from the behavior data of the middle school students in the educational activities; In a narrow sense, big data can be all the data related to the students' study, that is, the student individual big data: mainly includes the online operation log, the on-line business data; Below-line classroom record, paper materials (award-winning certificate, note, note) and so on. The research data of this paper is educational big data in narrow sense. At present, the general situation of big data's application in the field of education is as follows: teachers' teaching evaluation and decision-making are mostly based on the unilateral subjective judgment of the teacher, and the students' reflection is based on only achievements. In view of the above situation, this paper tries to explore the application of individual big data in the mixed teaching mode. In this paper, the application of individual big data in teaching and learning is studied from three aspects: teacher and student evaluation, teaching feedback and student reflection under the mixed teaching mode. The first part of this paper puts forward the significance of studying individual big data in the mixed teaching mode, the second part expounds the characteristics of the mixed teaching model, and introduces the function of cloud classroom, which is the supporting platform of hybrid teaching. The third part mainly introduces the application model of student individual big data, focusing on the storage model and analysis model; The fourth part discusses the students' individual big data's evaluation of students in detail, teachers use data to reflect on teaching, adjust teaching strategies, and students use comprehensive data and process data to reflect on learning. The specific application of learning plan adjustment in three aspects.
【学位授予单位】：华中师范大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：G434
【参考文献】
相关期刊论文 前10条
1 钟婉娟;侯浩翔;;大数据视角下教育决策机制优化及实现路径[J];教育发展研究;2016年03期
2 杨现民;唐斯斯;李冀红;;发展教育大数据:内涵、价值和挑战[J];现代远程教育研究;2016年01期
3 胥文勋;;大数据时代高校学生管理工作信息化建设现状与对策[J];绵阳师范学院学报;2016年01期
4 顾小清;薛耀锋;孙妍妍;;大数据时代的教育决策研究:数据的力量与模拟的优势[J];中国电化教育;2016年01期
5 赵兴龙;;创新评价体系 加速教育变革 中央电化教育馆和英特尔公司共同启动“教育大数据分析研究”项目[J];中国电化教育;2015年12期
6 唐雪;;“学生画像”发挂科预警[J];大学生;2015年22期
7 穆肃;左萍萍;;信息化教学环境下课堂教学行为分析方法的研究[J];电化教育研究;2015年09期
8 唐辉军;宋扬;熊松泉;;高校学生微博使用行为大数据分析和管理研究[J];科教文汇(上旬刊);2015年08期
9 姜强;赵蔚;王朋娇;王丽萍;;基于大数据的个性化自适应在线学习分析模型及实现[J];中国电化教育;2015年01期
10 赵中建;张燕南;;与大数据同行的学习与教育——《大数据时代》作者舍恩伯格教授和库克耶先生访谈[J];全球教育展望;2014年12期
相关硕士学位论文 前1条
1 黄亚红;初中课堂学生行为观察分析与实证研究[D];华中师范大学;2016年
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