Measuring Student Engagement in Lower Division Engineering Mathematics Classes

衡量学生对低年级工程数学课程的参与度

• 批准号: 1900456
• 负责人: Aly Farag
• 金额: $ 30万
• 依托单位: University of Louisville Research Foundation Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-15 至 2022-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1900456&HistoricalAwards=false
• 关键词: Measuring; Student; Engagement; Lower; Division

With support from the NSF Improving Undergraduate STEM Education Program: Education and Human Resources (IUSE: EHR), this project aims to serve the national interest by improving undergraduate engineering education. It will do so by designing, implementing, and testing a system to measure engineering students' emotional, behavioral, and cognitive engagement in first- and second-year engineering mathematics classes. Engineering programs suffer from a high rate of attrition in the freshman year, primarily due to poor engagement of students with their classes. The project plans to develop a sensor-driven, computational approach to measure emotional and behavioral components of student engagement. This information will be used to identify teaching strategies that increase engagement, with the goal of enhancing student success and retention in STEM education pathways. The project features a multi-disciplinary collaboration between faculty and undergraduate researchers in engineering, the physical sciences, psychological sciences, and education. The project will involve approximately 300 students in first- and second-year engineering mathematics classes and the experienced faculty who teach these courses. Findings from the project could be a valuable step toward an early warning system to detect student disengagement and anxiety in STEM and non-STEM courses. Project goals include: (i) establishment of a robust network of non-obtrusive and non-invasive sensors in mid-size classes to enable real-time extraction of facial and vital signs, which will be integrated and displayed on instructors' dashboards; (ii) identification of robust descriptors for modeling the emotional and behavioral components of engagement using data collected by the sensor networks; (iii) pilot testing of the system's effectiveness in gathering meaningful data for subsequent work on emotional, behavioral, and cognitive metrics of engagement. The fundamental research question to be addressed relates to improving student learning by the automated capture of non-verbal cues of engagement: How can we use students' expressions of engagement, based on non-verbal signs such as facial expressions, body and eye movements, physiological reactions, posture, to enhance learning? Findings from the project will constitute a foundation for multi-disciplinary research to incorporate novel machine learning and artificial intelligence-based models for measuring engagement in STEM classes. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.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NSF改善本科STEM教育计划的支持下：教育和人力资源（IUSE：EHR），该项目旨在通过改善本科工程教育来服务国家利益。 它将通过设计，实施和测试一个系统来测量工程学生在第一年和二年级工程数学课程中的情感，行为和认知参与来做到这一点。工程课程在大一年度的流失率很高，这主要是由于学生与课程的参与度不佳。该项目计划开发一种传感器驱动的计算方法，以衡量学生参与的情绪和行为成分。 这些信息将用于确定增加参与度的教学策略，以增强学生在STEM教育途径中的成功和保留。该项目以工程学，物理科学，心理科学和教育方面的教师与本科研究人员之间的多学科合作为特色。该项目将涉及大约300名一年级和二年级工程数学课程的学生以及教授这些课程的经验丰富的教师。该项目的调查结果可能是朝着预警系统迈出的宝贵一步，以检测学生在STEM和非STEM课程中的焦虑。 项目目标包括：（i）在中型类中建立一个强大的非引人注目和非侵入性传感器网络，以实时提取面部和生命体征，将在教练的仪表板上集成并显示； （ii）使用传感器网络收集的数据来识别可靠的描述符，以模拟参与的情绪和行为成分； （iii）对系统在收集有意义的数据中的有效性的试验测试，以进行随后的情感，行为和认知指标的工作。要解决的基本研究问题与通过自动捕获非语言参与线索的自动捕获有关：我们如何根据面部表情，身体和眼睛运动，生理反应，姿势，诸如面部表情，身体和眼睛的运动，身体和眼睛的运动，身体和眼睛运动，姿势来增强学习？该项目的发现将构成多学科研究的基础，该研究结合了新颖的机器学习和基于人工智能的模型，以衡量STEM类中的参与度。 NSF IUSE：EHR计划支持研发项目，以提高所有学生STEM教育的有效性。通过参与的学生学习轨道，该计划支持有希望的实践和工具的创建，探索和实施。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响评估的评估来支持的。