Measuring and Modeling Visual Attention in Online Multimedia Instruction

在线多媒体教学中视觉注意力的测量和建模

• 批准号: 2100071
• 负责人: Lester Loschky
• 金额: $ 54.04万
• 依托单位: Kansas State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2100071&HistoricalAwards=false
• 关键词: Measuring; Modeling; Visual; Attention; Online

Online multimedia instruction is expected to grow. Yet, given the tendency for students’ minds to wander and to be distracted especially during online instruction, it is important for researchers and educators to understand how to help students to stay focused on the important information while ignoring the unimportant information. This project addresses two fundamental issues: How does the online Science, Technology, Engineering, and Mathematics (STEM) instructor or educational materials developer know when learners are effectively paying attention to the learning material? How can they use this information to improve the design of their online learning materials in STEM? Attention and learning outcomes will be collected for several hundred students as they use multiple online modules, over a semester-long of a university introductory physics course. These data will be used to predict students’ attention and how it relates to their learning outcomes. This information will then be used to help improve online multimedia instruction.This project addresses a gap between the known effects of attention on learning and attempts to translate those theoretical constructs into pedagogical practice in rigorously, reliably, and validly measurable ways. This study is the first to bridge the theory and methods of studying attention in cognitive science with educational practice during a semester-long university online course. It points the way to making rapid, ecologically valid progress in understanding the connections between students' moment-to-moment attentional states and their long-term STEM learning. Such progress could be useful in advancing policy and practice surrounding improving STEM learning. In Phase 1(Basic Research), the Principal Investigators (PIs) propose a longitudinal, naturalistic study of attention and learning from online instruction. The PIs will study several hundred students' attention to online learning materials, and their learning, over a semester-long of a large university introductory physics course. In Phase 2 (Applied Research), using the above information, the PIs will identify generalizable targets of change in students' attentional states by alerting students at critical moments of attentional lapses, or cueing their attention to relevant information. For instructors and instructional designers, the project will provide meaningful, high impact data on students' varying attentional states over time, and will pinpoint attentional deficiencies. The proposed research will develop an Attentional Toolkit that takes a two-pronged approach to leveraging students' attentional states and improving their educational outcomes. The first prong ("demand side") addresses the learner by measuring their level of attentiveness and alerting/cueing their attention. The second prong ("supply side") addresses the instructor or online materials developer. To improve the broader impact of their research, the PIs will seek out a diverse pool of participants and take all measures necessary to improve fairness and reduce bias. Further, because the proposed methods are likely generalizable across numerous educational domains, the Attentional Toolkit could be broadly used across educational disciplines. In addition to publications and presentations, the Attentional Toolkit will be made available to faculty. The PIs will also provide workshops to faculty who are teaching multimedia online courses on how to use the Attentional Toolkit. This project is funded by the EHR Core Research (ECR) program, which supports work that advances fundamental research on STEM learning and learning environments, broadening participation in STEM, and STEM workforce development.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.

在线多媒体教学有望增长。然而，由于学生的思想倾向于徘徊和分心，特别是在在线教学期间，研究人员和教育工作者必须了解如何帮助学生专注于重要信息，而忽略不重要的信息。该项目解决了两个基本问题：在线科学，技术，工程和数学（STEM）教师或教育材料开发人员如何知道学习者何时有效地关注学习材料？他们如何使用这些信息来改进STEM在线学习材料的设计？将收集数百名学生的注意力和学习成果，因为他们使用多个在线模块，在一个学期的大学物理入门课程。这些数据将用于预测学生的注意力以及它与学习成果的关系。然后，这些信息将用于帮助改进在线多媒体教学。该项目解决了注意力对学习的已知影响与试图以严格、可靠和有效的可测量方式将这些理论构建转化为教学实践之间的差距。本研究首次将认知科学中研究注意力的理论和方法与教育实践相结合，在一个学期的大学在线课程中进行。它指出了在理解学生的时刻注意力状态与他们的长期STEM学习之间的联系方面取得快速，生态有效进展的方法。这种进展可能有助于推进围绕改善STEM学习的政策和实践。在第一阶段（基础研究），主要研究者（PI）提出了一个纵向的，自然的研究注意力和学习在线教学。PI将研究数百名学生对在线学习材料的关注，以及他们在一个学期的大型大学物理入门课程中的学习情况。在第二阶段（应用研究），主要研究主任会利用上述数据，在学生出现注意力涣散的关键时刻提醒他们，或提醒他们注意相关信息，从而找出学生注意力改变的一般目标。 对于教师和教学设计者，该项目将提供有意义的，高影响力的数据，学生的不同注意力状态随着时间的推移，并将查明注意力不足。拟议的研究将开发一个注意力工具包，采取双管齐下的方法来利用学生的注意力状态和提高他们的教育成果。第一个方面（“需求方”）通过测量学习者的注意力水平和提醒/提示他们的注意力来解决学习者的问题。第二个方面（“供应方”）针对教师或在线材料开发人员。为了提高他们的研究的更广泛的影响，PI将寻找一个多样化的参与者池，并采取一切必要的措施，以提高公平性和减少偏见。此外，由于所提出的方法很可能在众多的教育领域推广，注意力工具包可以广泛用于教育学科。除了出版物和演示文稿，注意力工具包将提供给教师。PI还将为教授如何使用注意力工具包的多媒体在线课程的教师提供研讨会。该项目由EHR核心研究（ECR）计划资助，该计划支持推进STEM学习和学习环境的基础研究，扩大STEM参与，以及STEM劳动力发展的工作。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。