EAGER: Pilot Investigation of Using Gaze in a Reading Tutor

PI在这个项目中解决的一个大问题是如何不引人注目地跟踪新手读者的无声阅读，以便能够使用智能辅导系统来帮助阅读理解。这个EAGER项目的重点是回答这个问题的第一步。这个试点项目建立在以前的工作中的视觉和语音技术，传感器融合，机器学习，用户建模，智能导师，眼球运动，努力确定使用眼动跟踪技术的可行性，沿着从智能阅读导师收集的其他信息，以预测新手/年轻读者的阅读困难。特别地，该工作计划包括在使用现有的阅读导师的背景下收集真实世界条件下的注视数据，设计软件以显示这些轨迹，使得可以测量准确性，测试注视点准确性并检测注视-语音差异，以及使用该数据来开发用于在真实的时间中检测跟踪错误的方法，并将眼睛跟踪数据校准到嘈杂的学校环境，最终将使用增强阅读辅导员的主要环境。该项目的智力价值在于识别和解决将儿童的凝视数据与他们的无声阅读相关联的挑战，为校准眼动仪做出技术贡献，以便它们可以用于正常的日常应用，该项目最重要的潜在影响是建立一个基础，凝视输入来构建智能计算系统，该系统可用于帮助有阅读困难的儿童学会阅读，并通过阅读来学习。如果成功，PI将开发一个更大的项目，将扩展成功的项目听阅读导师，以便它可以跟踪读者，因为他们是阅读沉默，并帮助他们与他们的理解-这两个文本本身的理解和策略来深入理解。

The big question the PIs are addressing in this project is how to unobtrusively track silent reading of novice readers so as to be able to use an intelligent tutoring system to aid reading comprehension. This EAGER project focuses on the first steps in answering that question. This pilot project builds on previous work in vision and speech technology, sensor fusion, machine learning, user modeling, intelligent tutors, and eye movements in an effort to identify the feasibility of using eye tracking techniques, along with other information collected from an intelligent reading tutor, to predict reading difficulties of novice/young readers. In particular, the work plan includes collecting gaze data in real-world conditions in the context of using the existing Reading Tutor, designing software to display those traces so that accuracy can be guauged, testing gazepoint accuracy and detecting gaze-speech discrepancies, and using that data to develop heuristics for detecting tracking errors in real time and calibrating eye tracking data to noisy school environments, a primary environment where the augmented Reading Tutor would ultimately be used. The intellectual merit of this project is in identifying and addressing challenges in relating children's gaze data to their silent reading, in making technical contributions to calibrating eye trackers so that they can be used in normal everyday applications, and in setting the stage for intelligent tutors across diverse domains to exploit gaze more broadly.The project's most important potential broader impacts is in establishing a foundation for exploiting gaze input to build intelligent computing systems that can be used to help children with reading difficulties learn to read and read to learn. If successful, the PIs will develop a larger project that will extent the successful Project Listen Reading Tutor so that it can track readers as they are reading silently and help them with their comprehension -- both comprehension of text itself and strategies for coming to deep understanding.