Empirical Research: Emerging Research: Learning with Multiple Graphical Representations in a Complex, Real-world domain: Intelligent Software Tutors for Fractions
实证研究:新兴研究:在复杂的现实世界领域中使用多种图形表示进行学习:分数智能软件导师
基本信息
- 批准号:0910010
- 负责人:
- 金额:$ 100.74万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2009
- 资助国家:美国
- 起止时间:2009-08-15 至 2013-07-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The cognitive science and educational psychology literatures provide ample evidence that instructional materials and activities that judiciously combine multiple representations of learning content (MRs) can have significant learning benefits. Much of this literature has focused on learning with a combination of text and figures; only some of it has focused on learning with multiple graphical representations. In order to benefit from multiple representations, students must connect key information across the different representations. Students typically must be supported in doing so (Ainsworth, 2006).This project studies the use of MRs in the domain of fractions, a very challenging area of mathematics for middle-school students in which graphical representations are used extensively (e.g., pie charts, number lines, fraction strips, set models, etc.) The research focuses on three general (and open) questions that instructional designers face when creating a curriculum that involves the use of MRs: First, when multiple representations of learning materials are used, how frequently should learners switch between representations? Second, what kinds of activities are most effective in helping students make connections between different representations? Third, what fraction of the students? time should be devoted to making connections between representations, relative to activities centered on a single representation?Researchers from Carnegie Mellon University and the University of Freiburg (Germany) investigate these questions in the context of an established educational technology: intelligent tutoring systems. These types of software tutors have been shown to improve students' mathematics learning in a number of scientific studies. A set of authoring tools created in a lab at Carnegie Mellon make the development of these tutors more cost effective and more accessible to education researchers than it used to be. During a three-year grant period, the project will (1) create web-based intelligent tutors as supplemental activities for fractions learning; these tutors support activities in which students work with interactive graphical representations of fractions, and make connections between the representations, and (2) conduct controlled experiments in Pittsburgh middle schools to investigate the three research questions outlined above.The proposed research will result in principles for learning with MRs. It will produce new knowledge about how fraction representations can best be used to support robust learning. The proposed research has the potential to produce more effective fractions instruction in the lower and middle grades, and thereby facilitate later mathematics learning. The proposed software tutors will be made freely available on the Mathtutor website (http://webmathtutor.org).
认知科学和教育心理学的文献提供了充分的证据,教学材料和活动,明智地结合联合收割机多种表征的学习内容(MR)可以有显着的学习效益。这些文献中的大部分都集中在文本和图形相结合的学习上;只有一部分集中在使用多种图形表示的学习上。为了从多种表征中获益,学生必须将不同表征中的关键信息联系起来。学生通常必须在这样做的支持(安斯沃思,2006年)。该项目研究了在分数领域使用MR,这是一个非常具有挑战性的数学领域,对中学生来说,图形表示被广泛使用(例如,饼图、数字线、分数条、集合模型等)本研究的重点是三个一般的(和开放的)问题,教学设计师在创建一个涉及使用MR的课程时所面临的:第一,当学习材料的多个表示使用,学习者应该多久切换表示?第二,什么样的活动最有效地帮助学生在不同表征之间建立联系?第三,学生的比例是多少?相对于集中在单一表征上的活动,应该花时间在表征之间的联系上?来自卡内基梅隆大学和弗赖堡大学(德国)的研究人员在一个既定的教育技术背景下调查这些问题:智能辅导系统。在一些科学研究中,这些类型的软件导师已经被证明可以提高学生的数学学习。在卡内基梅隆大学的一个实验室中创建的一套创作工具使这些导师的开发比以前更具成本效益,更容易为教育研究人员所用。在三年的资助期内,该项目将(1)创建基于网络的智能导师,作为分数学习的补充活动;这些导师支持学生使用分数的交互式图形表示的活动,并在表示之间建立联系,以及(2)在匹兹堡中学进行对照实验,调查上述三个研究问题。拟议的研究将导致它将产生关于如何最好地使用分数表示来支持鲁棒学习的新知识。这项研究有可能在低年级和中年级产生更有效的分数教学,从而促进以后的数学学习。拟议的软件导师将在Mathtutor网站(http://www.example.com)上免费提供。webmathtutor.org
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Vincent Aleven其他文献
Comparative Analysis of GPT-4 and Human Graders in Evaluating Human Tutors Giving Praise to Students
GPT-4 和人类评分者在评估人类导师对学生的表扬方面的比较分析
- DOI:
10.48550/arxiv.2307.02018 - 发表时间:
2023 - 期刊:
- 影响因子:3.5
- 作者:
Dollaya Hirunyasiri;Danielle R. Thomas;Jionghao Lin;K. Koedinger;Vincent Aleven - 通讯作者:
Vincent Aleven
High scaffolding of an unfamiliar strategy improves conceptual learning but reduces enjoyment compared to low scaffolding and strategy freedom
与低支架辅助和策略自由相比,一种陌生策略的高支架辅助提高了概念学习,但降低了乐趣。
- DOI:
10.1016/j.compedu.2025.105364 - 发表时间:
2025-10-01 - 期刊:
- 影响因子:10.500
- 作者:
Conrad Borchers;Hendrik Fleischer;Sascha Schanze;Katharina Scheiter;Vincent Aleven - 通讯作者:
Vincent Aleven
Designing Tools for Caregiver Involvement in Intelligent Tutoring Systems for Middle School Mathematics
设计让看护者参与中学数学智能辅导系统的工具
- DOI:
10.22318/icls2024.630637 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Ha Tien Nguyen;Conrad Borchers;Meng Xia;Vincent Aleven - 通讯作者:
Vincent Aleven
Problem-Solving Strategies in Stoichiometry Across Two Intelligent Tutoring Systems: A Cross-National Study
- DOI:
10.1007/s10956-024-10197-7 - 发表时间:
2025-01-11 - 期刊:
- 影响因子:5.500
- 作者:
Conrad Borchers;Hendrik Fleischer;David J. Yaron;Bruce M. McLaren;Katharina Scheiter;Vincent Aleven;Sascha Schanze - 通讯作者:
Sascha Schanze
Vincent Aleven的其他文献
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{{ truncateString('Vincent Aleven', 18)}}的其他基金
Supporting collaborative reflection by K-12 teachers with analytics from intelligent tutoring software
通过智能辅导软件的分析支持 K-12 教师的协作反思
- 批准号:
2119501 - 财政年份:2021
- 资助金额:
$ 100.74万 - 项目类别:
Standard Grant
Collaborative research: Fostering conceptual understanding and skill with an intelligent tutoring system for equation solving
协作研究:通过求解方程的智能辅导系统培养概念理解和技能
- 批准号:
1760922 - 财政年份:2018
- 资助金额:
$ 100.74万 - 项目类别:
Standard Grant
Human/AI Co-Orchestration of Dynamically-Differentiated Collaborative Classrooms
动态差异化协作课堂的人机/人工智能协同编排
- 批准号:
1822861 - 财政年份:2018
- 资助金额:
$ 100.74万 - 项目类别:
Standard Grant
EXP: Helping Teachers Help Their Students: Teachers' Use of Intelligent Tutoring Software Analytics to Improve Student Learning
EXP:帮助教师帮助学生:教师使用智能辅导软件分析来改善学生的学习
- 批准号:
1530726 - 财政年份:2015
- 资助金额:
$ 100.74万 - 项目类别:
Standard Grant
IERI: Learning-Oriented Dialogs in Cognitive Tutors: Toward a Scalable Solution to Performance Orientation
IERI:认知导师中以学习为导向的对话:走向绩效导向的可扩展解决方案
- 批准号:
0437794 - 财政年份:2004
- 资助金额:
$ 100.74万 - 项目类别:
Standard Grant
Improving Life-Long Learning Skills with Interactive Learning Environments
通过互动学习环境提高终身学习技能
- 批准号:
0308200 - 财政年份:2003
- 资助金额:
$ 100.74万 - 项目类别:
Continuing Grant
ITR/PE(CISE): Tutoring Explanation and Discovery Learning: Achieving Deep Understanding through Tutuorial Dialog
ITR/PE(CISE):辅导解释和发现学习:通过辅导对话实现深度理解
- 批准号:
0113864 - 财政年份:2001
- 资助金额:
$ 100.74万 - 项目类别:
Continuing Grant
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