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Modeling Brain and Behavior to Uncover the Eye-Brain-Mind Link during Complex Learning

模拟大脑和行为以揭示复杂学习过程中的眼-脑-心联系

基本信息

批准号：
1920510
负责人：
Sidney D'Mello
金额：
$ 100万
依托单位：
University of Colorado at Boulder
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
起止时间：
2019-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1920510&HistoricalAwards=false
关键词：
Modeling Brain Behavior Uncover Eye

项目摘要

The project, based at the University of Colorado, will advance fundamental knowledge on learning from complex STEM texts. This is a critical skill for success in an increasingly information-driven world and workforce, but it is also an area where students consistently struggle. Scores on standardized assessments are stubbornly stagnant, troublesome achievement gaps remain, and the U.S. continues to lag behind its international peers. This is especially relevant to the reading of complex STEM content. The main idea of the project is that learning from text is fundamentally about the coordination of vision (the eye) with thought (the mind) in a manner constrained by the content (the text), the context (the task), and the individual (the learner). Thus, there is a need to understand how these factors interact in order to advance basic knowledge and to inform effective interventions. The team will study how brain and behavioral signals can be used to understand the reading process and associated learning outcomes in a manner that is sensitive to individual differences. Anticipated near-term broader impacts include the interdisciplinary training of students, especially those from groups underrepresented in STEM fields, community outreach, and promoting scientific reasoning skills relevant to multiple STEM areas. In the longer term, the results of the project will inform the design of future interventions that aim to make learning from text more efficient, engaging, and effective. The project is funded by the EHR Core Research (ECR) program, which supports work that advances the fundamental research literature on STEM learning.The intellectual merit of the project is to gain fundamental knowledge on how the eye and brain dynamically coordinate to construct mental representations during complex learning from STEM texts. The project will address this goal by collecting eye movements, reading behaviors, noninvasive brain signals, and learning outcomes from high-school and college students in controlled lab settings and in school environments. It is expected that students will improve critical thinking and scientific reasoning skills by engaging with multiple texts on scientific research methods. The project will use behavioral (eye tracking and reading times) and non-invasive brain measures (high-density functional near-infrared spectroscopy and electroencephalography) to identify neurobehavioral markers of core processes involved in reading comprehension (e.g., focused attention vs. mind wandering, inference generation and elaboration) and the extent to which these measures can predict learning outcomes (comprehension, knowledge, and transfer) assessed immediately after learning and a week later. The project will also leverage advances in deep machine learning to build computational neurobehavioral models of the process and outcome variables in a manner that is sensitive to textual difficulty and to individual differences (e.g., prior knowledge, interest). Thus, the project will advance fundamental knowledge by integrating three research areas: theories of low-level reading processes and associated models of eye movements, models of higher-order STEM text comprehension including multiple document comprehension, and emerging research on the cognitive neuroscience of reading including co-registration with eye movements.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.

该项目总部设在科罗拉多大学，将促进从复杂的STEM文本中学习基础知识。这是在一个日益信息驱动的世界和劳动力中取得成功的一项关键技能，但它也是学生们持续奋斗的一个领域。标准化评估的分数顽固地停滞不前，令人头疼的成绩差距依然存在，美国继续落后于国际同行。这与阅读复杂的STEM内容特别相关。该项目的主要思想是，从课文中学习从根本上是关于视觉(眼睛)和思维(思维)的协调，以一种受内容(课文)、上下文(任务)和个人(学习者)限制的方式。因此，有必要了解这些因素是如何相互作用的，以便增进基本知识并为有效的干预措施提供信息。该团队将研究大脑和行为信号如何以对个体差异敏感的方式来理解阅读过程和相关的学习结果。预计近期更广泛的影响包括对学生进行跨学科培训，特别是对STEM领域代表性不足的群体的学生进行跨学科培训，社区外联，以及促进与多个STEM领域相关的科学推理技能。从长远来看，该项目的结果将为未来干预措施的设计提供参考，这些干预措施旨在使从文本中学习更有效率、更有吸引力和更有效。该项目由EHR核心研究(ECR)计划资助，该计划支持推进STEM学习基础研究文献的工作。该项目的智力价值是获得关于眼睛和大脑如何在复杂的STEM文本学习过程中动态协调构建心理表征的基础知识。该项目将通过在受控实验室环境和学校环境中收集高中生和大学生的眼球运动、阅读行为、非侵入性大脑信号和学习结果来实现这一目标。预计学生将通过接触多篇关于科学研究方法的课文来提高批判性思维和科学推理能力。该项目将使用行为(眼球跟踪和阅读时间)和非侵入性大脑测量(高密度功能性近红外光谱和脑电图)来确定阅读理解涉及的核心过程的神经行为标记(例如，集中注意力与走神、推理产生和阐述)，以及这些测量可以在多大程度上预测学习结果(理解、知识和迁移)，在学习后立即和一周后评估。该项目还将利用深度机器学习方面的进展，以对文本难度和个人差异(例如，先前知识、兴趣)敏感的方式建立过程和结果变量的计算神经行为模型。因此，该项目将通过整合三个研究领域来推进基础知识：低水平阅读过程的理论和相关的眼动模型，包括多文档理解的高阶STEM文本理解模型，以及关于阅读的认知神经科学的新兴研究，包括与眼动的共同注册。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。

项目成果

期刊论文数量（16）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Eye-Mind reader: an intelligent reading interface that promotes long-term comprehension by detecting and responding to mind wandering

DOI：
10.1080/07370024.2020.1716762
发表时间：
2020-02-02
期刊：
HUMAN-COMPUTER INTERACTION
影响因子：
5.3
作者：
Mills, Caitlin;Gregg, Julie;D'Mello, Sidney K.
通讯作者：
D'Mello, Sidney K.

Going Deep and Far: Gaze-based Models Predict Multiple Depths of Comprehension During and One Week Following Reading

深入而深远：基于凝视的模型预测阅读期间和阅读后一周的多个理解深度

DOI：
10.5281/zenodo.6852998
发表时间：
2022
期刊：
International Educational Data Mining Societ
影响因子：
0
作者：
Caruso, Megan;Peacock, Candace;Southwell, Rosy;Zhou, Guojing;D'Mello, Sidney
通讯作者：
D'Mello, Sidney

Machine-Learned Computational Models Can Enhance the Study of Text and Discourse: A Case Study Using Eye Tracking to Model Reading Comprehension