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.

数学和科学图表改善了学习，无论是当图表与教学一起提供时，还是当它们是为自我解释而创建的时候。由此产生的学习往往更灵活。例如，练习作图的学生更善于将学习从他们明确练习的问题转移到更开放的问题上。不幸的是，图表在教材中太不常见了，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。规模化教学增加了进一步的挑战。理想情况下，电子学习平台应该为不同的学生提供不同的问题。这些问题应该针对知识成分进行调整，防止抄袭作弊，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，对学生创作的图表进行评分甚至很难手动完成。为了应对这一挑战，该项目旨在开发一种新的工具来生成图解教学内容。该项目开发的这个工具将使内容作者能够通过示例生成大型问题集。用户将创作一到两个问题，该工具将从示例中合成一个问题集。该项目引入了用于查看和编辑这些集合的高效交互技术。该项目将从教师和学生那里收集数据，以指导、改进和评估工具的设计。该项目将进行六项研究，其中三项侧重于该工具在支持编写教育内容方面的有效性，三项侧重于由此产生的问题对学生学习的影响。这些研究将加深我们对图表何时以及如何用来增加学生对科学、技术、工程和数学(STEM)原则的理解，并导致更灵活的STEM思维。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。