Narrative Modeling with StoryQ: Integrating Mathematics, Language Arts, and Computing to Create Pathways to Artificial Intelligence Careers

未来的劳动力正在被人工智能（AI）技术彻底重塑。人工智能理论、算法和实践的进步不仅为人工智能科学家、工程师、技术人员和企业家创造了巨大的需求，而且改变了几乎所有行业的工作性质。重要的是，今天的学生必须对人工智能有一个基本的了解，以便为进入未来的劳动力市场做好准备。该项目将设计一个名为StoryQ的12课高中课程和相关的教学指南，为学生提供关于如何在语言艺术写作项目中开发叙事建模（人工智能中最古老的领域之一）的第一手经验。通过整合适合年龄的数学，语言艺术和计算概念，研究人员将利用先进的数据探索和文本挖掘技术，并采用基于研究的教学方法来帮助高中生学习机器学习和人工智能的基本概念。该项目由学生和教师创新技术体验（ITEST）计划资助，该计划支持建立对实践，计划元素，背景和过程的理解的项目，有助于增加学生对科学，技术，工程和数学（STEM）以及信息和通信技术（ICT）职业的知识和兴趣。由学习技术和数据专家，机器学习研究人员以及叙事建模和数学学习集成专家组成的多学科团队领导，该项目将专注于帮助学生设想他们未来的职业生涯由人工智能驱动。研究人员将创建和测试基于Web的文本挖掘和叙事建模平台StoryQ，并使用StoryQ课程开发，实施和测试叙事建模。学生将学习设计，构建，测试和迭代改进来自学生和教师选择的文献以及学生自己的作品的叙述的机器学习模型。从核心叙事概念开始，学生将参与开发周期，引导他们探索自己的写作，手工注释模型，观察工作中经过训练的文本挖掘模型，熟悉错误分析，并最终构建自己的AI模型和评估过程。该项目通过从族裔和经济状况各异的两个马萨诸塞州学区招募参与者，扩大了代表性不足和服务不足人口中青年的参与。为了创造广泛包容的学习体验，来自不同背景的学生将写叙述来表达他们的文化和个性作为学习活动的一部分。研究问题包括：（1）如何设计学习环境来帮助学生理解核心AI概念，包括非结构化数据中的结构以及人类洞察力在AI技术发展中的作用？（2）如何设计学习环境来帮助学生培养对以文本挖掘实践为中心或广泛由人工智能技术驱动的职业的认识和兴趣？该项目将采用基于设计的研究设计。研究团队将进行课堂观察和对观察数据的深入分析，并为构建培养未来STEM和ICT劳动力的学习环境制定设计原则。该项目的成功将由一组外部评估人员进行评估，他们是人工智能，计算机教育，数学教育，语言艺术和扫盲教育的多样性和包容性专家。该项目的成果包括为高中提供的网络交付的课堂AI课程模块、教学指南和教师资源，这些将分发给教师和专业发展团体。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The future workforce is being drastically reshaped by artificial intelligence (AI) technologies. The advancement in AI theories, algorithms and practices has not only created great demands for AI scientists, engineers, technicians and entrepreneurs, but also reformulated the nature of work in almost all industries. Importantly today's students must gain a fundamental understanding of AI in order to be prepared to enter the workforce of the future. This project will design a 12-lesson high school curriculum called StoryQ and associated teaching guides that will provide students with firsthand experience on how narrative modeling, one of the oldest fields in artificial intelligence, can be developed while working on their language arts writing projects. By integrating age-appropriate mathematics, language arts, and computing concepts, researchers will leverage advanced data exploration and text mining technologies, and employ research-based pedagogical approaches to help high school students learn basic concepts in machine learning and artificial intelligence. This project is funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers. Led by a multidisciplinary team of learning technology and data experts, machine learning researchers, and experts in the integration of narrative modeling and mathematics learning, the project will focus on helping students envision their future careers as powered by artificial intelligence. The researchers will create and test StoryQ, a web-based text mining and narrative modeling platform, and develop, implement, and test narrative modeling with StoryQ curriculum. Students will learn to design, build, test, and iteratively improve machine learning models of narratives sourced both from student and teacher selected literature and from students’ own writings. Beginning with core narrative concepts, students will engage in development cycles that lead them to explore their own writing, annotate models by hand, observe a trained text mining model at work, become familiar with error analysis, and ultimately build their own AI model and evaluation process. The project broadens participation among youth from underrepresented and underserved populations by recruiting participants from two Massachusetts school districts with ethnically and economically diverse populations. To create broadly inclusive learning experiences, students from diverse backgrounds will write narratives to express their cultures and personalities as part of the learning activities. Research questions include (1) How can learning environments be designed to help students understand core AI concepts including the structures in unstructured data and the roles of human insight in the development of AI technologies? and (2) How can learning environments be designed to help students develop awareness and interest in careers that are centered on text mining practices or broadly powered by AI technologies? The project will use a design-based research design. The research team will carry out class observations and in-depth analysis of observational data, and draw design principles for building learning environments that cultivate future STEM and ICT workforce. The project’s success will be evaluated by a group of external evaluators who are experts in diversity and inclusion in AI, computing education, mathematics education, and language arts and literacy education. The outcomes of the project include the resulting web-delivered classroom-ready AI curriculum modules, a teaching guide and teacher resources for high schools, which will be disseminated to teachers and professional development groups. The StoryQ technology will be freely distributed.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.