Research: Staying the course: Understanding the motivational factors contributing to persistence among undergraduate engineering students in online courses

本研究将探讨激励工程本科学生在网上课程注册完成课程，而不是辍学的因素。网络课程已成为工程本科教育中越来越多使用和重要的教学手段。在线形式可以为那些可能无法访问的学生提供教育机会，因此，有可能对国家工程劳动力的规模和构成产生积极影响。然而，在线课程的学生退出这些课程的比例高于传统的面对面课程。提议的工作将利用亚利桑那州立大学的在线本科工程学位课程来生成一个模型，该模型基于以下类型的数据来描述和预测课程级别的持久性：单个学生的属性，显示学生在在线课程学习管理系统中点击的位置和时间的跟踪数据，以及关于在线课程本身的信息。这项工作的直接影响将是加深对本科工程专业学生选择留在或放弃在线课程的原因的理解。从长远来看，研究结果还将有助于提高在线工程本科学生成功完成学位课程的比例。在项目中，基于学生动机理论和在线和本科工程学生的坚持，将开发一个在线课程水平的工程坚持模型，并进行实证评估。该项目提出了三项研究。学生体验研究采用纵向的、面对面的方法来调查本科工程专业学生在在线课程中的经历如何影响他们对课程成功可能性的信念、对课程价值的看法、对课程的参与程度以及完成课程的最终决定。学习管理系统交互研究将基于学习者的关联分类技术应用于亚利桑那州立大学在线本科工程课程的历史数据，以描述学生参与在线课程学习管理系统的模式，因为它们与课程级别的持久性有关。最后的持久性建模研究从这些模式中生成一个统一的课程参与度量。该测量将用于纵向结构方程建模分析，比较在线课程水平持久性模型的三种变化：(1)将投入作为课程成功期望、课程任务值、课程特征感知和课程水平持久性之间关系的部分中介；(2)将投入概念化为课程成功期望、课程任务值、课程特征感知和课程完成持久性之间关系的完全中介；(3)根本不包括业务的变型。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This study will investigate the factors that motivate undergraduate engineering students enrolled in online courses to complete the courses, rather than drop out. Online courses have become an increasingly utilized and important instructional method in undergraduate engineering education. The online format can provide educational opportunities to students who otherwise may not have access and, therefore, has the potential to positively affect the size and makeup of the nation's engineering workforce. However, students in online courses drop out of these courses at greater rates than those in more traditional, face-to-face courses. The proposed work will utilize the online undergraduate engineering degree programs at Arizona State University to generate a model that describes and predicts course-level persistence based on the following types of data: attributes of individual students, tracking data that shows where and when students click within their online course learning management system, and information about the online courses themselves. The immediate impact of the work will be an increased understanding of the reasons that undergraduate engineering students choose to stay in or drop online courses. In the longer term, the findings will also contribute to efforts that support a greater percentage of online undergraduate engineering students successfully completing their degree programs.During the project, a Model of Online Course-level Persistence in Engineering grounded in theories of student motivation and online and undergraduate engineering student persistence will be developed and empirically evaluated. The project proposes three studies. The Student Experiences Study uses a longitudinal, within-person approach to investigate how undergraduate engineering students' experiences in their online course influence their beliefs about their likelihood of success in the course, their perceptions of the value of the course, their level of engagement in the course, and their ultimate decision to complete the course. The Learning Management System Interaction Study applies the learner-based technique of associative classification to historical data from online undergraduate engineering courses at Arizona State University to describe students' patterns of engagement with their online course learning management system as they relate to course-level persistence. The final Persistence Modeling Study generates a unified measure of course engagement from these patterns. This measure will be used in a longitudinal structural equation modeling analysis that compares three variations on the model of online course-level persistence: (1) a variation in which engagement is included as a partial mediator of the relationships between expectancies of course success, course task values, perceptions of course characteristics, and course-level persistence, (2) a variation in which engagement is conceptualized as a full mediator of the relationships between expectancies of course success, course task values, perceptions of course characteristics, and persistence to course completion, and (3) a variation in which engagement is not included at all.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.