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Learning Internal Visualization Skills for Complex Engineering Concepts in Active Learning Classes

Learning Internal Visualization Skills for Complex Engineering Concepts in Active Learning Classes
在主动学习课程中学习复杂工程概念的内部可视化技能
批准号:
1933078
负责人:
Martina Rau
金额:
$30.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-10-01 至 2023-09-30

项目摘要

项目成果

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中文摘要
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英文摘要
With support from the NSF Improving Undergraduate STEM Education Program: Education and Human Resources (IUSE:EHR), this project aims to serve the national interest by improving engineering students' ability to understand graphs and other visual representations. Engineering instructors often use visual representations, such as Cartesian and polar coordinate graphs, to help students learn. However, these visualizations can be confusing to students unless they know how the visualizations show information. This project will use an intelligent tutoring system to help students learn how particular visual features show specific foundational engineering concepts. It will also target student fluency in understanding visual representations, akin to fluency in a language. The intelligent tutorial system will also train students to imagine the visuals when they are no longer present. It is expected that these "internal" visualization skills will help students learn more easily from text and equations. Experiments will investigate which supports lead to most improvement in students' internal visualization skills and content learning. The experiments will be carried out in situations in which students learn individually and collaboratively, allowing the project team to establish which aspects of visual representations are best learned alone and which are best learned in a team. Such understanding is important for understanding the limits and maximizing the effectiveness of active learning classes.Internal visualization skills enhance learning when the visual representations are subsequently replaced by abstract equations. Two critical knowledge gaps will be addressed in the project: i) how best to support representational competencies in a way that enhances internal visualization skills; ii) how to effectively support representational competencies for both individual and collaborative activities, the latter being increasingly important in active learning. The project will provide new insights into how instruction can help students benefit from visual representation. Although the project focuses on the learning of foundational engineering concepts, it may yield results that inform the development of educational technology resources for other disciplines. The project will lead to an innovative educational technology resource that provides support for individual and collaborative learning with visuals, which may enhance students' success in STEM. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the IUSE program supports the creation, exploration, and implementation of promising practices and tools.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(4)
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会议论文
How drawing prompts can increase cognitive engagement in an active learning engineering course
绘图提示如何提高主动学习工程课程中的认知参与度
DOI: 10.1002/jee.20354
发表时间: 2020
期刊: Journal of Engineering Education
影响因子: 3.4
作者: [Wu, Sally P. W., Van Veen, Barry, Rau, Martina A.]
通讯作者: Rau, Martina A.
Preparing Future Learning with Novel Visuals by Supporting Representational Competencies
通过支持表征能力,用新颖的视觉效果为未来的学习做好准备
DOI: --
发表时间: 2022
期刊: International Conference on Artificial Intelligence in Education
影响因子: --
作者: [Jihyun Rho, M. Rau, Barry D. Van Veen]
通讯作者: Barry D. Van Veen
DOI: --
发表时间: 2022
期刊: Proceedings of the 15th International Conference on Educational Data Mining
影响因子: --
作者: [Rho, J. Rau]
通讯作者: Rho, J. Rau
Digitally Inoculating Viewers Against Visual Misinformation With a Perceptual Training
  • 批准号:
    2202457
  • 项目类别:
    Standard Grant
  • 资助金额:
    $84.98万
  • 财政年份:
    2022
  • 负责人:
    Martina Rau
  • 依托单位:
CAREER: Intelligent Representations: How to Blend Physical and Virtual Representations by Adapting to the Individual Student's Needs in Real Time
  • 批准号:
    1651781
  • 项目类别:
    Standard Grant
  • 资助金额:
    $59.84万
  • 财政年份:
    2017
  • 负责人:
    Martina Rau
  • 依托单位:
EXP: Modeling Perceptual Fluency with Visual Representations in an Intelligent Tutoring System for Undergraduate Chemistry
  • 批准号:
    1623605
  • 项目类别:
    Standard Grant
  • 资助金额:
    $54.04万
  • 财政年份:
    2016
  • 负责人:
    Martina Rau
  • 依托单位:
Supporting Chemistry Learning with Adaptive Support for Connection Making Between Graphical Representations in a Cognitive Tutoring System
  • 批准号:
    1611782
  • 项目类别:
    Standard Grant
  • 资助金额:
    $59.38万
  • 财政年份:
    2016
  • 负责人:
    Martina Rau
  • 依托单位:
国内基金
海外基金
Cortical control of internal state in the insular cortex-claustrum region