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

计算机科学（31）本合作项目提高了生物识别安全和隐私领域的本科教育和学生学习。该项目的具体目标是：(A)开发侧重于三个主题的课件模块：(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；(B)探索以同伴合作和竞争为基础的关联和集体智慧的概念，以促进主动学习，并通过该概念确定课件材料有效地对生物识别安全和隐私方面的本科学习产生积极影响的条件。这个项目的一个独特之处在于让学生积极地贡献精选的案例研究和问题解决方案，这些案例研究和解决方案将被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，这些智慧反映了对可用生物识别安全性和隐私期望的不同观点。第二，让学生参与到贡献的过程中，需要他们将知识和信息源连接起来，实现连接智能。该项目产生三个可交付成果：(A)关于生物识别安全和隐私的概念、原理和技术的学生学习指南；(B)生物特征数据和保护隐私的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识别数据和技术、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.