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The relationship between mathematical induction, proposition functions, and implication functions.

机译:数学归纳,命题函数和蕴涵函数之间的关系。

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摘要

In this study, I explored the relationship between mathematical induction ability and proposition and implication functions through a mixed methods approach. Students from three universities (N = 78) and 6 classrooms completed a written assessment testing their conceptual and procedural capabilities with induction and functions. In addition, I interviewed a subgroup of 10 participants to add context and meaning to the assessment results. This research study was unique in that it provided numeric correlations among important variables. The correlation between induction ability and function ability was r = 0.47 (p 0.001). The general linear model Mathematical Induction = -0.300 + 0.122 ACT Math + 0.222 Function Ability was significant at p 0.05 and explained 28.3% of the variation in induction ability. In the written assessment, I asked participants to construct two induction proofs. Out of the 156 attempts, 57 attempts were successful (37%). During the interview analysis, I identified participant subgroups based on mathematical goals, background, and motivation. I argued that the characteristics of these subgroups related directly to their scores on the written assessment. In particular, students who perceived mathematical induction as useful to themselves in their future career put forth the energy required to learn induction, both procedurally and conceptually. Based on the results of this study, I recommended that students learn about proposition functions prior to studying induction. I also recommended that the amount of class time spent on the instruction of induction increase along with a continued focus on the conceptual elements of the proof technique.
机译:在本研究中,我通过混合方法探讨了数学归纳能力与命题和蕴涵函数之间的关系。来自三所大学(N = 78)和六个教室的学生完成了书面评估,测试了他们在归纳和功能上的概念和程序能力。此外,我采访了一个由10名参与者组成的小组,目的是为评估结果添加背景和含义。这项研究的独特之处在于它提供了重要变量之间的数值相关性。诱导能力和功能能力之间的相关性为r = 0.47(p <0.001)。通用线性模型数学归纳= -0.300 + 0.122 ACT数学+ 0.222函数能力在p <0.05时显着,可以解释28.3%的归纳能力变化。在书面评估中,我要求参与者构建两个归纳证明。在156次尝试中,有57次尝试成功(37%)。在访谈分析过程中,我根据数学目标,背景和动机确定了参与者子组。我认为这些亚组的特征与他们在书面评估中的分数直接相关。特别是,那些认为数学归纳法对自己的未来职业有用的学生,在程序和概念上都提出了学习归纳法所需的精力。根据这项研究的结果,我建议学生在学习归纳法之前先学习命题功能。我还建议增加在归纳教学中花费的课堂时间,并继续关注证明技术的概念性要素。

著录项

  • 作者

    Andrew, Lane.;

  • 作者单位

    University of Northern Colorado.;

  • 授予单位 University of Northern Colorado.;
  • 学科 Education Mathematics.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 287 p.
  • 总页数 287
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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