首页> 外文学位 >Algebraic functions in a graphing technology environment: Student performance after small group work using teacher-generated versus student-generated examples.
【24h】

Algebraic functions in a graphing technology environment: Student performance after small group work using teacher-generated versus student-generated examples.

机译:绘图技术环境中的代数功能:使用教师生成的示例与学生生成的示例进行小组讨论后的学生表现。

获取原文
获取原文并翻译 | 示例

摘要

In this study I investigated the effects that two different levels of written guidance had on the performance of college level Precalculus students within the contextual environment of Graphing Calculators merged with Inquiry learning. There were two experimental groups and one control group. The control group took only the pretest and the posttest. The experimental groups were divided between High Structured (HS) guidance, which consisted of teacher-generated examples and Low Structured (LS) guidance, which consisted of student-generated examples. Based on Pretest scores, students were coded as High Prior Knowledge (HPK) or Low Prior Knowledge (LPK). Students were not allowed to have a calculator on either the Pretest or the Posttest; however, they used a calculator during the instructional intervention, which involved students working in small heterogeneous groups using the graphing calculators and examples (theirs or the teacher's) to explore the relationships between graphical and algebraic representations of parabolic functions.; All students significantly and meaningfully improved their scores between the Pretest and the Posttest, but there was no evidence to support one structure over the other. However, on the Retention test the HPK students in the Low Structured groups significantly and meaningfully outperformed the HPK in the High Structured groups. My intervention included a group Quiz. The Quiz took place before any class discussion and before the Posttest. The mean Quiz score for the LS group was meaningfully and significantly higher then the mean Quiz score for the HS groups. There were no results favoring High Structure over Low structure on any measure.
机译:在这项研究中,我调查了在图形计算器与探究学习相结合的环境中,两种不同水平的书面指导对大学水平的初等数学学生的表现产生的影响。有两个实验组和一个对照组。对照组仅接受前测和后测。实验组分为高结构(HS)指导和低结构(LS)指导,前者由教师生成的示例组成,低结构(LS)指导由学生生成的示例组成。根据预测成绩,学生被编码为高先验知识(HPK)或低先验知识(LPK)。不允许学生在预测或后测中使用计算器;但是,他们在教学干预期间使用了计算器,其中涉及使用图形计算器和示例(他们的或老师的)在异质小组中工作的学生,以探索抛物线函数的图形表示和代数表示之间的关系。所有学生在考试前和考试后之间都取得了显着和有意义的提高,但是没有证据支持其中一种结构优于另一种结构。但是,在保留测试中,低结构组中的HPK学生显着优于高结构组中的HPK。我的干预包括小组测验。测验是在任何课堂讨论之前和后期测试之前进行的。 LS组的平均测验分数显着高于HS组的平均测验分数。无论如何,没有结果支持高结构而不是低结构。

著录项

  • 作者

    Allen, Roseann P.;

  • 作者单位

    State University of New York at Albany.;

  • 授予单位 State University of New York at Albany.;
  • 学科 Education Mathematics.; Education Technology.
  • 学位 Ph.D.
  • 年度 2006
  • 页码 101 p.
  • 总页数 101
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 O1-4;T-4;
  • 关键词

  • 入库时间 2022-08-17 11:39:37

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号