网络学习环境对中小学生视力的影响研究

发布时间：2018-03-27 11:21

本文选题：计算机视觉　切入点：网络学习环境　出处：《华中师范大学》2017年硕士论文

【摘要】：随着我国教育信息化的不断深入,中小学生的网络学习环境得到很大提升,青少年网民规模持续增长。目前中小学生视力问题日益突出:表现年龄提前、近视和低视力检出率不断增加,信息化的学习环境是否会对学生的视力造成影响,这是众多教育者关注的问题。当前,对网络学习环境的研究集中于教学效果、学习效果、自我效能等方面,少有学者关注其对视力的影响。研究方法上多采用问卷、教育实验、内容分析等,运用信息技术的方法较少。为了研究网络学习环境对学生视力的影响及建立有效的干预方法,本文从物理环境、资源环境、人文环境三个方面对网络学习环境特征进行测量与分析。选取不同地区的12所小学、初中、高中作为研究对象,分析网络学习环境特征与视力的相关性,基于数据挖掘方法建立学生视力水平预测模型,提出视力的干预方法并验证其有效性。本文采用计算机视觉和问卷调查相结合的方法获取客观合理的数据。计算机视觉测量法通过摄像头采集人脸图像上瞳距像素距离,将其换算成实际用眼距离,选取平均上网距离作为最终上网用眼距离。相对于传统人工测量及问卷的方式,该方法更加客观科学。本研究通过Pearson相关性分析发现网络学习环境与视力的相关性,采用数据挖掘的方法建立预测模型。通过决策树、随机森林、支持向量机三种算法预测视力水平。结果显示:物理环境和人文环境对学生视力有很大影响;随机森林整体预测效果最好,在不近视、轻度近视上均有较好的预测效果。基于研究中发现影响视力的因素,提出相应的干预方法并验证其有效性。用眼距离与网络学习时间干预采用计算机视觉的方法,结合心理教育干预课程培训学生如何保护视力和改掉用眼恶习。干预结果显示,该方法能有效缓解学生视力下降问题,效果显著。这对指导学生正确合理用网,促进网络学习环境发展具有一定意义。
[Abstract]:With the deepening of educational information in China, the network learning environment of primary and middle school students has been greatly improved, and the scale of youth Internet users has continued to grow. At present, the eyesight problems of primary and middle school students are becoming increasingly prominent: the performance of the early age, The detection rate of myopia and low vision is increasing, whether the information learning environment will affect the vision of the students is a problem that many educators pay attention to. At present, the research on the network learning environment focuses on the teaching effect and the learning effect. In terms of self-efficacy, few scholars pay attention to its influence on eyesight. Questionnaires, educational experiments, content analysis and so on are used in the research methods. In order to study the influence of network learning environment on students' eyesight and to establish effective intervention methods, this paper focuses on physical environment and resource environment. This paper measures and analyzes the characteristics of network learning environment from three aspects of humanistic environment, selects 12 primary schools, middle schools and senior middle schools from different regions as research objects, and analyzes the correlation between the characteristics of network learning environment and visual acuity. Based on the method of data mining, the prediction model of students' vision level is established. In this paper, the method of computer vision and questionnaire is used to obtain objective and reasonable data. The distance between pupil and pixel in face image is collected by computer vision measurement. It is converted into actual eye distance, and the average distance is chosen as the final distance. Compared with the traditional manual measurement and questionnaire, This method is more objective and scientific. In this study, the correlation between network learning environment and vision was found by Pearson correlation analysis, and the prediction model was established by data mining. The results show that the physical environment and the humanistic environment have great influence on the visual acuity of the students, and the overall prediction effect of the random forest is the best, in the case of not nearsightedness, the results show that the visual acuity is predicted by the support vector machine (SVM). Based on the factors affecting visual acuity found in the study, the corresponding intervention method was put forward and its effectiveness was verified. The method of computer vision was used to intervene with eye distance and network learning time. In combination with the psychological education intervention course, the students were trained to protect their eyesight and to change their bad eye habits. The result of intervention showed that the method could effectively alleviate the problem of visual acuity decline of students and have a remarkable effect on guiding students to use the net correctly and reasonably. It is significant to promote the development of network learning environment.
【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】：G637.8

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