Collaborative Research: CISE-MSI: DP: SCH: Privacy Preserving Tutoring System for Health Education of Low Literacy Hispanic Populations

合作研究：CISE-MSI：DP：SCH：低识字率西班牙裔人群健康教育隐私保护辅导系统

• 批准号: 2219587
• 负责人: Renu Balyan
• 金额: $ 14.02万
• 依托单位: SUNY College at Old Westbury
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2219587&HistoricalAwards=false
• 关键词: Collaborative; Research; CISE; MSI; DP

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).This project will implement a computer tutor for low literacy Hispanic breast cancer survivors. Breast cancer is the leading cause of cancer-related deaths in Hispanics, and although research has shown that education can greatly mitigate stress and improve quality of life, few educational interventions for this population exist. The computer tutor resulting from this project will mimic a human tutor that teaches about breast cancer survivorship skills and about breast cancer in general. Because tutoring involves conversation with the survivor, it is possible that they reveal sensitive personal information; therefore, it is important to encrypt the information in the tutoring session to prevent any privacy breaches. And for the tutoring component to be effective, special attention must be paid to the utilization of natural language processing models as well as models of behavior that are observed in the target population when tutoring and/or interacting with technology. For the privacy component to be effective, techniques that can encrypt and decrypt data at high speeds will be explored to make the interaction fluid. To date, computer tutors that converse with their students have been tried mainly with a highly literate population in college settings, so their impact on low literacy Hispanics is unknown. Therefore, this project will advance our understanding of the impact of designing artificial intelligence powered tutors to address diversity and disparities in the access to information by a subset of low literacy individuals, as well as our understanding of privacy preserving algorithms that work in real-time with complex natural language processing models. More broadly, project outcomes will facilitate access to information for minority populations and will serve to build research capacity and train minority students in the participating teaching-oriented institutions.The project will be carried out with two objectives in mind. First, development of a novel intelligent computer tutoring system that is customized so that it can effectively query and interact with Hispanic breast cancer survivors by adapting existing content that was created for this population in prior research. Because it has been shown that both the language of many adult Hispanics, and target population interactions with technology, are more nuanced than previously thought, our first objective also involves training natural language algorithms and designing interactions that model those of Hispanic breast cancer survivors. The second objective is to develop privacy-preserving algorithms that utilize robust end-to-end encrypted communication and can encrypt and decrypt distributed data in real time at a speed that does not hinder the interactions with the computer tutor. The contributions of this development process will be threefold: (1) to understand the role of culture and education in the interaction between low literacy Hispanic breast cancer survivors and intelligent tutoring systems; (2) to develop a framework that facilitates the implementation of intelligent tutoring systems for minority populations; and (3) to develop accurate and low latency privacy preserving mechanisms for NLP model training and dialogue interfaces.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.

该奖项是根据2021年《美国救援计划法》的全部或部分资助的（公共法117-2）。该项目将为低识字西班牙裔乳腺癌幸存者实施计算机老师。乳腺癌是西班牙裔与癌症相关死亡的主要原因，尽管研究表明，教育可以极大地减轻压力和改善生活质量，但对该人群的教育干预很少。该项目导致的计算机导师将模仿一个人类的老师，该教师会教授有关乳腺癌生存技巧和一般乳腺癌的教师。因为辅导涉及与幸存者的交谈，所以他们可能会揭示敏感的个人信息。因此，重要的是要在辅导会议中加密信息以防止任何隐私漏洞。为了使辅导组件有效，必须特别注意自然语言处理模型的利用以及在辅导和/或与技术互动时在目标人群中观察到的行为模型。为了使隐私组件有效，将探索可以高速加密数据并解密数据的技术，以使相互作用流体。迄今为止，与学生交谈的计算机辅导员主要在大学环境中接受了高知识的人口的尝试，因此他们对低识字性西班牙裔的影响尚不清楚。因此，该项目将促进我们对设计具有人工智能的教师的影响的理解，以解决较低的识字人群的子集解决信息中的多样性和差异，以及我们对保留复杂自然语言处理实时工作的隐私算法的理解。 更广泛地说，项目成果将有助于少数民族人口的信息获取信息，并将在参与教学的机构中培训研究能力并培训少数民族学生。该项目将考虑到两个目标。 首先，开发一种新型的智能计算机补习系统，该系统可以通过调整为先前研究中为该人群创建的现有内容来有效地查询并与西班牙乳腺癌幸存者互动。由于已经表明，许多成年西班牙裔的语言均和与技术的目标人群相互作用都比以前想象的更为细微，因此我们的第一个目标还涉及培训自然语言算法和设计对西班牙乳腺癌幸存者的相互作用。第二个目标是开发具有强大的端到端加密通信的隐私算法，并可以实时加密和解密分布式数据以不阻碍与计算机辅导员的交互的速度。这种发展过程的贡献将是三重：（1）了解文化和教育在低识字素养西班牙裔乳腺癌幸存者与智能辅导系统之间的相互作用中的作用； （2）开发一个框架，以促进为少数族裔人口实施智能辅导系统； （3）为NLP模型培训和对话界面开发准确和低的延迟隐私机制。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准，被认为值得通过评估来获得支持。