Enhancing flexible STEM thinking by generating interactive diagrams at scale

通过大规模生成交互式图表来增强灵活的 STEM 思维

• 批准号: 2119007
• 负责人: Joshua Sunshine
• 金额: $ 84.94万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2119007&HistoricalAwards=false
• 关键词: Enhancing; flexible; STEM; thinking; generating

Math and science diagrams improve learning, both when diagrams are delivered with instruction, and when they are created for self-explanation. The resulting learning is often more flexible. For example, students that practice diagramming are better at transferring their learning from the problems they have explicitly practiced to more open-ended problems. Unfortunately, diagrams are too uncommon in instructional materials, especially practice problems. This is primarily because diagrams are much harder to produce than text and symbols. Teaching at scale adds further challenges. Ideally, e-learning platforms should deliver different problems to different students. These problems should be tailored to knowledge components, prevent cheating by copying, and be tuned the amount of practice to student needs. Problem templating systems aren’t built for diagrams and grading student-authored diagrams is hard to do even manually. To address the challenge, this project aims to develop a new tool for generating diagrammatic instructional content. This tool developed by the project will enable content authors to generate large problem sets by example. User will author one or two problems and the tool will synthesize a problem set from the examples. The project introduces efficient interaction techniques for viewing and editing these sets. The project will collect data from teachers and students to guide, refine, and evaluate the design of the tool. The project will conduct six studies, three will focus on the effectiveness of the tool in supporting authoring of educational content and three that focus on the impact of the resulting problems on student learning. These studies will enhance our understanding of when and how diagrams can be used to increase student understanding of science, technology, engineering and math (STEM) principles and lead to more flexible STEM thinking.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.

数学和科学图表可以改善学习，无论是在教学中提供图表还是为自我解释而创建图表时，最终的学习通常都更加灵活。例如，练习图表的学生能够更好地从他们所遇到的问题中学到知识。不幸的是，图表在教学材料中很少见，尤其是练习问题，这主要是因为图表比文本和符号更难制作，理想情况下，电子教学会增加更多的挑战。学习平台应该向不同的人提供不同的问题这些问题应该根据知识组成进行定制，防止抄袭，并根据学生的需要调整练习量。问题模板系统不是为图表而构建的，即使手动也很难对学生创作的图表进行评分。为了解决这一挑战，该项目旨在开发一种用于生成图解教学内容的新工具，该项目开发的该工具将使内容作者能够通过示例生成大量问题集，并且该工具将合成一个问题。从示例中设置。该项目将介绍用于查看和编辑这些集合的有效交互技术，以指导、完善和评估该工具的设计，其中三项研究将重点关注该工具的有效性。支持教育内容的创作，以及三项重点关注由此产生的问题对学生学习的影响。这些研究将增强我们对何时以及如何使用图表来提高学生对科学、技术、工程和数学 (STEM) 原理的理解的理解。并带来更灵活的 STEM 思维。该奖项反映了通过使用基金会的智力价值和更广泛的影响审查标准进行评估，NSF 的法定使命被认为值得支持。