SBIR Phase I: Linguistic Analysis of Web Content for 21st Century Inquiry Learning

SBIR 第一阶段：21 世纪探究性学习的网络内容语言分析

• 批准号: 1315554
• 负责人: Eleni Miltsakaki
• 金额: $ 14.91万
• 依托单位: Choosito!
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-07-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1315554&HistoricalAwards=false
• 关键词: SBIR; Phase; Linguistic; Analysis; Web

This SBIR Phase II innovation is twofold. First, advanced natural language processing techniques are used to analyze the content of websites and identify features of the text that determine processing difficulty for the individual student. After the initial evaluation of text difficulty, the system becomes adaptive and automatically updates its decision for the suitability of a website by keeping track of the user's reading experience. This machine learning technology enables differentiated learning and, thus, enables fair access of web content to English Language Learners and special education groups. Second, the content of websites is characterized by advanced text analysis and classification to detect school subject areas. Elementary school students, for example, will find science content written at a level that they can comprehend, thus, being enabled to laser focus their attention to accessible content and engage with it critically. The proposed technology addresses the critical problem of information management and helps teachers teach their students the skills that they need to find, evaluate, and take advantage of available information in any context. The broader/commercial impact of the proposed technology will be in the integration of the recently articulated common core standards (21st century learning) in the K-12 classroom. The development of the proposed technology will offer unprecedented opportunity for differentiated learning and give students a life-long tool to help them understand and critically engage with the information available to them. Early integration of information literacy and inquiry based learning is enabled not only by identifying age appropriate resources but, also, by offering a total project management platform. Teachers and curriculum developers will save valuable time and effort because they will have community space to find curated up-to-the-minute resources and core projects, which they can edit, save, and share, assign them to students, and receive submitted work, all in one window. Students, too, have personal space to keep notes, automatically keep track of resources for later review and citation, collaborate, prepare, and submit their reports. The platform can integrate with school library resources, thus, becoming a powerful tool for librarians. Application Programming Interfaces can be developed for collaboration with publishers enabling them to smoothly integrate core standards in their curricula and update them for 21st century learning.

SBIR 第二阶段的创新是双重的。 首先，使用先进的自然语言处理技术来分析网站内容并识别文本特征，这些特征决定了个别学生的处理难度。在对文本难度进行初步评估后，系统会变得自适应，并通过跟踪用户的阅读体验来自动更新其对网站适合性的决定。 这种机器学习技术可以实现差异化学习，从而使英语学习者和特殊教育群体能够公平地访问网络内容。其次，网站内容的特点是先进的文本分析和分类，以检测学校的学科领域。例如，小学生会发现科学内容以他们可以理解的水平编写，因此能够将注意力集中在可访问的内容上并批判性地参与其中。 所提出的技术解决了信息管理的关键问题，并帮助教师教授学生在任何情况下查找、评估和利用可用信息所需的技能。所提议技术的更广泛/商业影响将体现在 K-12 课堂中最近阐明的共同核心标准（21 世纪学习）的整合中。所提出的技术的发展将为差异化学习提供前所未有的机会，并为学生提供终生工具，帮助他们理解和批判性地参与可用的信息。信息素养和基于探究的学习的早期整合不仅可以通过识别适合年龄的资源来实现，还可以通过提供全面的项目管理平台来实现。教师和课程开发人员将节省宝贵的时间和精力，因为他们将拥有社区空间来查找精选的最新资源和核心项目，他们可以编辑、保存和共享这些项目，将其分配给学生并接收提交的作业，全部在一个窗口中。学生也有个人空间来记笔记、自动​​跟踪资源以供以后审阅和引用、协作、准备和提交报告。该平台可以与学校图书馆资源整合，成为图书馆员的有力工具。可以与出版商合作开发应用程序编程接口，使他们能够顺利地将核心标准集成到他们的课程中，并更新它们以适应 21 世纪的学习。