初中生数据分析中元认知能力现状及培养策略的研究

发布时间：2018-05-01 09:32

本文选题：初中生 + 数据分析　；参考：《贵州师范大学》2015年硕士论文

【摘要】：培养初中生的元认知能力是新时期为培养学生综合素质所提出的新要求。初中生统计部分学习的本质就是学生参与数据分析活动的过程。元认知能力是影响数学活动的重要因素,因此数据分析中元认知能力决定着数据分析活动的质量和效率。数据分析元认知能力的培养,对于数据分析能力的提高和数据分析观念的发展都起到重要的推动作用。本研究对现有元认知理论、数学元认知理论、数学问题解决元认知理论进行了系统的梳理和深入的理论分析。结合关于数据分析观念、数据分析操作过程和数据分析教学内容的研究,将初中生数据分析元认知能力定义为:“数据分析元认知就是以数据分析观念为指导,主体对自身数据分析思维活动过程,及伴随这一活动所产生的心理体验进行监控和调节的能力。”并对数学分析中元认知能力的结构与要素进行分析,构建了数据分析元认知能力的分析框架。它包含3个方面和8个维度即:“数据分析元认知认知、数据分析元认知体验和数据分析元认知监控,总共3个主要因素;又将其细分为:主体性、客体性、策略性、意识性、计划性、监测性、调控性和反思性,总共8个次因素。”本研究在数据分析中元认知能力的8维度分析框架下,结合数据分析过程中所涉及的方法、程序、思想等内容,在充分观察、了解、总结初中生数据分析活动的过程后,编制了初中生数据分析元认知能力现状的调查问卷。采用问卷调查法、访谈法等科学的研究方法,选取大连市2所不同类型初中的近300名学生为调查对象,进行了问卷测试,并运用SPSS软件对得到的数据进行定量分析。得到关于初中生数据分析中元认知能力现状和结论如下:1、初中生数据分析中元认知能力的整体水平处于中等水平,其中计划性、监测性、调控性和反思性相对水平较低。2、通过分析比较发现,数学成绩与数据分析中元认知能力成正相关关系,因此数学成绩高的学生数据分析元认知能力较高。3、通过比较不同类型学校学生数据分析中元认知能力各维度得分后发现,乡镇学校学生的数据分析元认知能力水平明显低于城市学校的学生。且不同类型学校与学生数据分析元认知能力水平之间存在显著影响。说明教学水平是影响数据分析元认知能力的重要因素之一,换句话说学生数据分析能力可以通过优化教学水平得到提高。4、通过分析比较不同性别学生数据分析元认知能力各维度和总体得分后发现其差异性不明显。5、分析表明随着年级的增高,初中生数据分析元认知能力水平也在逐渐提高,且年级与数据分析元认知能力有显著性关系。得出结论是,学生的数学元认知是呈阶段性发展的。最后,本研究根据初中生数据分析中元认知能力所表现出的现状和分析出的结论,试提出6点关于提高初中生数据分析能力的培养策略和建议;1、结合学生元认知和认知特点,循序渐进阶段性培养2、创设数据分析问题情境,运用启发式教学模式激发学生的主动性3、强调反思训练,鼓励学生写反思日记4、运用出声思维,帮助学生进行数据分析元认知训练5、运用“问题-情境”教学培养问题意识,间接提高数据分析元认知能力6、在教学中加强统计思想的渗透,培养学生数据分析观念
[Abstract]:To cultivate the metacognitive ability of junior high school students is a new requirement for cultivating students' comprehensive quality in the new period. The essence of the statistical part of junior high school students is the process of students participating in the analysis of data. Metacognitive ability is an important factor affecting the mathematical activities. Therefore, the metacognitive ability determines the quality of the data analysis activities. Quantity and efficiency. The cultivation of metacognitive ability of data analysis plays an important role in improving the ability of data analysis and the development of data analysis concept. This study systematically combs and analyses the existing metacognitive theory, mathematical metacognitive theory and mathematical problem solving metacognitive theory. According to the analysis concept, the data analysis operation process and the data analysis teaching content, the metacognitive ability of the data analysis is defined as: "data analysis metacognition is guided by the idea of data analysis, the subject is monitoring and adjusting the psychological experience of the data analysis, and the psychological experience associated with this activity." And analyze the structure and elements of metacognitive ability in mathematical analysis, and build an analytical framework for metacognitive ability of data analysis. It consists of 3 aspects and 8 dimensions: "data analysis metacognitive cognition, data analysis metacognitive experience and data analysis metacognition monitoring, total 3 main factors; and it subdivides it into: Subject, objectivity, strategy, consciousness, consciousness, planning, monitoring, regulation and rethinking, there are 8 factors in total. "Under the framework of the 8 dimension analysis of metacognitive ability in data analysis, this study combines the methods, procedures and ideas involved in the process of data analysis to fully observe, understand and summarize the data analysis activities of junior high school students. After the process, we compiled a questionnaire on the status of metacognitive ability of data analysis of junior high school students. By using the methods of questionnaire, interview and other scientific research methods, we selected nearly 300 students from 2 different types of junior high school in Dalian as the investigation object, carried out a questionnaire test and analyzed the data obtained by using SPSS soft parts. The present situation and conclusion of middle school students' meta cognitive ability are as follows: 1, the overall level of metacognitive ability in the data analysis of junior high school students is at the middle level, in which the relative level of planned, monitoring, regulatory and reflective is low.2. The results show that the mathematical achievement is positively related to the meta cognitive ability in data analysis. The metacognitive ability of the students with high mathematical results is higher.3. By comparing the scores of metacognitive abilities in the data analysis of different types of school students, it is found that the level of metacognitive ability of the data analysis of the students in the township schools is obviously lower than that of the students in the urban schools. The teaching level is one of the important factors affecting the metacognitive ability of data analysis. In other words, the students' data analysis ability can improve.4 by optimizing the teaching level. By analyzing and comparing the dimensions and overall scores of metacognitive abilities of different sex students, it is found that their differences are unknown. The analysis shows that with the increase of grade, the level of metacognitive ability of data analysis of junior high school students is increasing gradually, and there is a significant relationship between grade and metacognitive ability of data analysis. The conclusion is that the students' metacognition is progressively developed. Finally, this study is based on the metacognitive ability of junior high school students' data analysis. The present situation and the conclusion of the analysis, try to put forward 6 points of training strategies and suggestions on improving the data analysis ability of junior high school students. 1, combining students' metacognitive and cognitive characteristics, step by step training 2, create data analysis problem situation, use heuristic teaching mode to stimulate students' initiative 3, emphasize reflection training, encourage students to write anti. Diaries 4, using sound thinking, helping students to carry out metacognitive training 5 in data analysis, training problem awareness with "problem situation" teaching, indirectly raising the metacognitive ability of data analysis 6, strengthening the infiltration of statistical ideas in teaching and training students' data analysis ideas.

【学位授予单位】：贵州师范大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：G633.6

【参考文献】