CAREER: Adaptive Physical Interfaces
CAREER: Adaptive Physical Interfaces
批准号:
1844406
负责人:
Stefanie Mueller
金额:
$52.52万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-07-01 至 2024-12-31
中文摘要
自适应用户界面,即根据用户的工作环境、能力、技能和动机改变其布局和功能的界面,可以帮助更快地完成任务,并为具有不同能力的人群扩大访问范围。例如,自适应网站在手机而不是笔记本电脑屏幕上查看时会重新布局其内容,以保持对信息的快速访问;自适应菜单重新排序其功能,以显示在最显著位置频繁使用的功能;自适应网页样式设计器将视觉障碍用户难以看到的配色方案替换为易于处理的配色方案。到目前为止,自适应用户界面主要用于屏幕用户界面,例如在台式计算机、膝上型计算机和移动电话上运行的网页和其他数字应用程序。然而,随着计算进入我们的环境,以及具有集成传感功能的“智能”日常对象的可用性增加,现在可以考虑如何将为数字自适应用户界面部署的方法应用于物理用户界面,即我们在日常生活中使用的物理对象。例如,考虑一个孩子在训练轮的帮助下学习如何骑自行车的例子:车轮上集成的传感器可以测量孩子的平衡情况,并确定当前的学习进度,然后马达可以根据孩子的进度升降训练轮来增加或降低难度。研究小组将研究学习(例如,适应性写作辅助工具、儿童发展的适应性玩具)、健康和康复(例如,适应性助行器、拐杖、石膏)和无障碍(例如,用于做饭、个人护理和娱乐的适应性工具)领域的一系列应用用例。研究人员将遵循最初部署的研究计划,该计划最初是为了在数字自适应用户界面方面进行有影响力的早期工作。在第一阶段,将确定物理自适应工具的应用领域和用例。在对应用领域进行集群后,团队将为物理自适应工具构建示范原型。在完成第一轮样机后,将进行可用性测试和评估。在用户研究中,该团队将比较适应性物理工具与非适应性物理工具之间的用户性能。每项研究任务将被设计成与工具的背景相匹配(例如,衡量学习收益、生产力提高、健康改善),但主要研究设计将在所有工具上保持一致。利用从这次调查中获得的见解,该团队将为构建自适应物理工具构建一个设计原则框架,并提出一套衡量其成功应用的指标。该框架将涵盖多个方面,例如交互期间的适应时间(即,工具改变其物理状态的时间)、适应范围(即,当改变物理工具时范围致动器必须覆盖的范围)、以及适应集成(即,以不干扰用户交互的方式添加传感器和致动器)。根据设计原则的框架,该团队将开发一种设计工具,以促进自适应物理工具的开发。有了框架、设计工具和正式的研究设计,团队将深入调查特定的应用领域,如适应性学习、健康和康复以及可获得性。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
Adaptive User Interfaces, i.e. interfaces that change their layout and functionality based on working context, capabilities, skills, and motivations of users can help to complete tasks faster and widen access for populations with diverse abilities. For instance, an adaptive website re-layouts its content when viewed on a phone rather than a laptop screen to preserve fast access to information, an adaptive menu re-orders its functions to display the ones that are frequently used in the most prominent location, and an adaptive webpage stylizer replaces color schemes that are hard to see for users with visual impairments with those that are easy to process. So far, adaptive user interfaces have mainly been explored for on-screen user interfaces, such as webpages and other digital applications running on desktop computers, laptops, and mobile phones. However, with computing moving into our environment and the increased availability of "smart" everyday objects with integrated sensing, it now becomes feasible to ask how the approach deployed for digital adaptive user interfaces can be applied to physical user interfaces, i.e. the physical objects we use in our everyday lives. For instance, consider the example of a child learning how to ride a bike with the help of training wheels: sensors integrated in the wheels can measure how well the child is balancing and determine the current learning progress, then motors can lift or lower the training wheels to increase or decrease the difficulty level according to the child's progress. The research team will study a range of application use cases in the areas of learning (e.g., adaptive writing aids, adaptive toys for child development), health and rehabilitation (e.g., adaptive walkers, canes, casts), and accessibility (e.g., adaptive tools for meal preparation, personal care, and recreation). The investigator will follow the research plan that was initially deployed for influential early work on digital adaptive user interfaces. In the first phase, application areas and use cases will be identified for physically adaptive tools. After clustering the application areas, the team will build exemplary prototypes for physically adaptive tools. After finishing the first round of prototypes, usability testing and evaluation will be conducted. For the user studies, the team will compare user performance between adaptive physical tools vs. their non-adaptive counterparts. Each study task will be designed to match the context of the tool (e.g., measuring learning gain, productivity increase, health improvement), but the main study design will be coherent across all tools. Using the insights gained from this investigation, the team will build a framework of design principles for building adaptive physical tools and propose a set of metrics for measuring their successful application. The framework will cover aspects, such as the adaptation time during interaction (i.e., the time for the tool to change its physical state), the adaptation range (i.e., the range actuators have to cover when changing the physical tool), and the adaptation integration (i.e., adding sensors and actuators in a way that does not interfere with the user interaction). Based on the framework of design principles, the team will develop a design tool that facilitates the development of adaptive physical tools. With the framework, design tool, and formalized study design in hand, the team will investigate specific application areas, such as adaptive learning, health and rehabilitation, and accessibility, in depth.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.
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Adapt2Learn: A Toolkit for Configuring the Learning Algorithm for Adaptive Physical Tools for Motor-Skill Learning
Adapt2Learn:用于配置运动技能学习自适应物理工具的学习算法的工具包
DOI:
--
发表时间:
2021
期刊:
DIS '21: Designing Interactive Systems Conference 2021
影响因子:
--
作者:
[Turakhia, D.]
通讯作者:
Turakhia, D.
Can Physical Tools that Adapt their Shape based on a Learner’s Performance Help in Motor Skill Training?
根据学习者表现调整形状的物理工具有助于运动技能训练吗?
DOI:
10.1145/3430524.3440636
发表时间:
2021
期刊:
ACM Conference on Tangible and Embedded Interaction
影响因子:
--
作者:
[Turakhia, Dishita G, Qi, Yini, Blumberg, Lotta-Gili, Wong, Andrew, Mueller, Stefanie]
通讯作者:
Mueller, Stefanie
FlexBoard: A Flexible Breadboard for Interaction Prototyping on Curved and Deformable Surfaces
FlexBoard:用于在弯曲和可变形表面上进行交互原型设计的灵活试验板
DOI:
10.1145/3544548.3580748
发表时间:
2023
期刊:
CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
影响因子:
--
作者:
[Ko, Donghyeon, Kim, Yoonji, Zhu, Junyi, Wessely, Michael, Mueller, Stefanie]
通讯作者:
Mueller, Stefanie
SensorViz: Visualizing Sensor Data Across Different Stages of Prototyping Interactive Objects
SensorViz:可视化交互式对象原型设计的不同阶段的传感器数据
DOI:
10.1145/3532106.3533481
发表时间:
2022
期刊:
DIS '22: Designing Interactive Systems Conference
影响因子:
--
作者:
[Kim, Yoonji, Zhu, Junyi, Trivedi, Mihir, Turakhia, Dishita, Wu, Ngai Hang, Ko, Donghyeon, Wessely, Michael, Mueller, Stefanie]
通讯作者:
Mueller, Stefanie
MechSense: A Design and Fabrication Pipeline for Integrating Rotary Encoders into 3D Printed Mechanisms
MechSense:将旋转编码器集成到 3D 打印机构中的设计和制造流程
DOI:
10.1145/3544548.3581361
发表时间:
2023
期刊:
CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems
影响因子:
--
作者:
[Alalawi, Marwa, Pacik-Nelson, Noah, Zhu, Junyi, Greenspan, Ben, Doan, Andrew, Wong, Brandon M, Owen-Block, Benjamin, Mickens, Shanti Kaylene, Schoeman, Wilhelm Jacobus, Wessely, Michael]
通讯作者:
Wessely, Michael
CHS: Small: Collaborative Research: Learning Maker Skills By Building Game Props
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批准号:2008116
-
项目类别:Standard Grant
-
资助金额:$35.0万
-
财政年份:2020
-
负责人:Stefanie Mueller
-
依托单位:
CHS: Small: An Integrated Editing Environment for 3D Printing
-
批准号:1716413
-
项目类别:Standard Grant
-
资助金额:$45.29万
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财政年份:2017
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负责人:Stefanie Mueller
-
依托单位:
海外基金