Collaborative Project: Participatory-based approach on Teaching and Learning Biometric Security and Privacy

计算机科学(31)这个合作项目改善了生物识别安全和隐私领域的本科生教育和学生学习。这个项目的具体目标是：(A)开发专注于三个主题的课程模块：(I)生物识别技术，(Ii)隐私，以及(Iii)保护隐私的生物识别安全技术；以及(B)探索基于同伴合作和竞争的连接和集体智能的概念，以促进主动学习，并通过这个概念确定在什么情况下课程材料有效地对本科生在生物识别安全和隐私方面的学习产生积极影响。该项目的一个独特特点是鼓励学生积极贡献选定的案例研究和问题解决方案，以积累并纳入学习指南。参与内容材料的积极贡献在两个方面具有重要意义。首先，它允许课件捕捉集体智慧，反映对可用的生物识别安全和隐私期望的不同观点。其次，让学生参与到贡献的过程中，需要他们将知识和信息来源联系起来，以实现连接智能。这个项目产生了三个交付成果：(A)关于生物特征安全和隐私的概念、原理和技术的学生学习指南；(B)生物特征数据和隐私保护生物特征数据检索软件；(C)实验手册，帮助学生获得关于生物特征数据和技术、其应用及其隐私影响的实践经验。

Computer Science (31)This collaborative project improves undergraduate education and student learning in the area of biometric security and privacy. The specific objectives of this project are: (A) to develop courseware modules that focus on three topics: (i) biometric technologies, (ii) privacy, and (iii) techniques for privacy preserving biometric security; and (B) to explore the notion of connective and collective intelligence grounded on peer collaboration and competition for promoting active learning, and through which to identify the conditions under which the courseware materials are effective to create a positive impact on undergraduate learning in biometric security and privacy.A unique characteristic of this project is to engage students to actively contribute selected case studies and problem solutions to be accumulated and included in the learning guide. Engaging in the active contribution of content materials is significant in two regards. First, it allows the courseware to capture the collective intelligence that reflects diverse viewpoints on usable biometric security and privacy expectation. Second, engaging students in the process of contribution requires them to connect knowledge and information sources to achieve connective intelligence.This project produces three deliverables: (A) a student learning guide on the concepts, principles, and technologies on biometric security and privacy; (B) biometric data and privacy preserving biometric data retrieval software; and (C) lab manuals for experiments that help students gain hands-on experience on the biometric data and technologies, their applications, and their privacy implications.