Exploring Team-Sourced Hyperlinks to Address Navigation Challenges for Low-Vision Readers of Scientific Papers

Author:

Park Soya1,Bragg Jonathan2,Chang Michael3,Larson Kevin4,Bragg Danielle5

Affiliation:

1. Massachusetts Institute of Technology, Cambridge, MA, USA

2. Allen Institute for Artificial Intelligence, Seattle, WA, USA

3. Stanford University, Stanford, CA, USA

4. Microsoft Research, Seattle, WA, USA

5. Microsoft Research, Cambridge, MA, USA

Abstract

Reading academic papers is a fundamental part of higher education and research, but navigating these information-dense texts can be challenging. In particular, low-vision readers using magnification encounter additional barriers to quickly skimming and visually locating information. In this work, we explored the design of interfaces to enable readers to: 1) navigate papers more easily, and 2) input the required navigation hooks that AI cannot currently automate. To explore this design space, we ran two exploratory studies. The first focused on current practices of low-vision paper readers, the challenges they encounter, and the interfaces they desire. During this study, low-vision participants were interviewed, and tried out four new paper navigation prototypes. Results from this study grounded the design of our end-to-end system prototype Ocean, which provides an accessible front-end for low-vision readers, and enables all readers to contribute to the backend by leaving traces of their reading paths for others to leverage. Our second study used this exploratory interface in a field study with groups of low-vision and sighted readers to probe the user experience of reading and creating traces. Our findings suggest that it may be possible for readers of all abilities to organically leave traces in papers, and that these traces can be used to facilitate navigation tasks, in particular for low-vision readers. Based on our findings, we present design considerations for creating future paper-reading tools that improve access, and organically source the required data from readers.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Human-Computer Interaction,Social Sciences (miscellaneous)

Reference40 articles.

1. Accessible skimming

2. Cognitive Dimensions of Notations: Design Tools for Cognitive Technology

3. Erin Brady , Meredith Ringel Morris , and Jeffrey P. Bigham . 2015. Gauging Receptiveness to Social Microvolunteering . In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, Seoul Republic of Korea, 1055--1064 . https://doi.org/10.1145/2702123.2702329 10.1145/2702123.2702329 Erin Brady, Meredith Ringel Morris, and Jeffrey P. Bigham. 2015. Gauging Receptiveness to Social Microvolunteering. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. ACM, Seoul Republic of Korea, 1055--1064. https://doi.org/10.1145/2702123.2702329

4. ASL Sea Battle: Gamifying Sign Language Data Collection

5. Stacy M. Branham and Shaun K. Kane. 2015. Collaborative Accessibility: How Blind and Sighted Companions Co-Create Accessible Home Spaces . In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems ( Seoul, Republic of Korea) (CHI '15). Association for Computing Machinery, New York, NY, USA, 2373--2382. https://doi.org/10.1145/2702123.2702511 10.1145/2702123.2702511 Stacy M. Branham and Shaun K. Kane. 2015. Collaborative Accessibility: How Blind and Sighted Companions Co-Create Accessible Home Spaces. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (Seoul, Republic of Korea) (CHI '15). Association for Computing Machinery, New York, NY, USA, 2373--2382. https://doi.org/10.1145/2702123.2702511

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Papeos: Augmenting Research Papers with Talk Videos;Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology;2023-10-29

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3