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Integrating an Artificial Intelligence-Driven, Culturally Responsible Digital Graphic Novel Curriculum into STEM Introductory Biology Courses

Integrating an Artificial Intelligence-Driven, Culturally Responsible Digital Graphic Novel Curriculum into STEM Introductory Biology Courses
将人工智能驱动、对文化负责的数字图画小说课程融入 STEM 生物学入门课程
批准号:
2234281
负责人:
Shayla Williams
金额:
$30.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-03-01 至 2026-02-28

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中文摘要
翻译
该项目旨在通过实施一种吸引和留住STEM学生的新方法来服务于国家利益。传统的以课堂为中心的方案往往不能充分激发人们对STEM和以STEM为基础的研究的兴趣,特别是对于在追求STEM研究领域中代表性不足的少数群体。然而,实践证明,注重实践的课堂可以增加少数群体和女性在STEM中的参与率。使用图画小说是另一种实际操作的、经过验证的技术,因为这种人工制品是一种学习媒介,将文本和视觉结合起来,以提高学生的表现。然而,自定义图形小说的创作可能会很耗时。因此,该项目将侧重于使用人工智能/自然语言处理(AI/NLP)方法来开发根据用户的文化背景和挑战水平个性化的数字图形小说课程。学生的目标群体包括一年级和二年级的生物原理课程,因为大学的头两年被认为是STEM管道中的潜在“漏洞”。拟议的研究将开发一个前端学生体验和工作流程的原型,通过直观的、基于网络的界面设计与图形小说课程进行数字交互。教育课程、内容和引人入胜的幽默将与导航工具相结合,以便能够在不同的图形喜剧课程之间进行转换。设想中的网络应用程序将在亚马逊网络服务上进行开发、测试和生产。平台架构将由三个组件组成:电子数据源、学生网络界面和后端人工智能引擎。这一办法将解决在STEM领域使用图画小说等有效学习方式的影响的数据匮乏的问题,这些小说的人口在历史上处于主要不利地位。该项目的成功将创造一种可重复使用的方法,利用人工智能/NLP驱动的平台,有效地设计、制作并将定制的、响应文化的图形小说整合到基于探究的STEM课程中,并确定其有效性和对学生学习收益和STEM课程保持的影响。该项目的发现可能会对增加少数族裔STEM参与高级生物课程和生物学以外的学科产生额外的影响。NSF IUSE:EHR计划支持研究和开发项目,以提高所有学生的STEM教育的有效性。通过其参与的学生学习跟踪,该计划支持有前途的实践和工具的创建、探索和实施。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。
英文摘要
This project aims to serve the national interest by implementing a novel approach to engage and retain students in STEM. Traditional classroom-focused programs often fail to adequately stimulate interest in STEM and STEM-based research, especially for minority groups underrepresented in their pursuit of STEM fields of study. However, hands-on focused classrooms have been shown to increase minority and female participation in STEM. The use of graphic novels is another hands-on, practical proven technique, as such artifacts are a learning medium that combines both text and visuals to improve student performance. However, the creation of a custom graphic novel can be time-consuming. Thus, this project will focus on using an artificial intelligence/natural language processing (AI/NLP) approach to develop a digital graphic novel curriculum that is personalized to the cultural background and challenge level of the user. The target group of students comprises freshman and sophomores taking a Principles of Biology course because the first two years of college are considered potential “leaks” in the STEM pipeline. The proposed research will develop a prototype of the front-end student experience and workflows for digital interaction with a graphic novel curriculum through an intuitive, web-based interface design. An educational curriculum, content, and engaging humor will be integrated with navigation tools to enable transitions into, within, and between different graphical-comedic lessons. The envisioned web app will be developed, tested, and produced on Amazon Web Services. Platform architecture will be composed of three components: electronic data sourcing, student web interface, and a back-end AI engine. This approach will address a paucity of data on the impact of using an effective learning modality such as graphic novels with a predominately historically disadvantaged population in the STEM fields. The success of this project will create a reproducible method for effectively designing, producing, and integrating a customized, culturally responsive graphic novel using an AI/NLP-driven platform into inquiry-based STEM classes, as well as determining its efficacy and impact on student learning gains and STEM course retention. Project findings may have additional implications for increasing minority STEM participation in upper class biology courses and for disciplines outside of biology. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the 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.
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