EAGER: Student Outcomes in a Computer Science MOOC (SOCSMOOC)

EAGER项目旨在研究HarvardX提供的大规模开放式在线课程（MOOC），该实验是为了响应哈佛教师对中央资源的需求而创建的，以帮助他们通过重新想象的教学来推动学习的边界，并利用在线时代教育研究的新可能性。这项研究的主题是“计算机科学导论”，这是哈佛所有MOOC中初始注册人数最多的课程（150，349），也是哈佛所有传统教学课程中注册人数第二多的课程（714）。本课程的两个版本，CS50x和CS50，共享许多功能（讲座，问题集，考试和项目），但在评分，学生反馈和课堂互动方面有所不同。与传统课程99.6%的完成率不同，CS50x仅向6.3%的入学者颁发完成证书。这提供了一个研究MOOCS高流失率的机会，这个问题困扰着全国的在线课程。很少有人知道为什么学生不完成MOOC。在完成率方面是否存在性别差异，少数民族在STEM中的代表性不足，学生年龄，语言流利程度？该项目在CS50x MOOC中收集经验证据，以创建注册学生的个人资料，并确定他们的背景，他们以前的计算经验以及他们在课程期间的学习行为中的哪些因素，预测成功完成课程。将使用统计生存分析对脱落风险进行建模。该项目更广泛的影响是，通过描述对学生在MOOC中取得成功产生积极和消极影响的因素，它将允许制定更知情，从而更有效的教学和机构政策，旨在提高学生的成功率和扩大参与。

This EAGER project seeks to study a Massive Open Online Course (MOOC) offered by HarvardX, an experiment created in response to a need by Harvard faculty for a central resource to help them push the boundaries of learning through re-imagined teaching and to take advantage of new possibilities for educational research in the online era. The topic of the study is "Introduction to Computer Science", a course with the largest initial enrollment of all of Harvard's MOOCs (150,349), as well as the second largest enrollment of all of Harvard's traditionally taught courses (714). Two versions of this course, CS50x and CS50, share many features (lectures, problem sets, exams, and projects), but differ in grading, student feedback, and classroom interactivity. Unlike the traditional course which has a 99.6% completion rate, CS50x awards completion certificates to only 6.3% of those who enroll. This presents an opportunity to study high attrition rates in MOOCS, a problem that plagues online courses nationwide. Little is known about why students do not finish MOOCs. Are there disparities in completion rates by gender, minorities underrepresented in STEM, age of students, language fluency? The project gathers empirical evidence in the CS50x MOOC to create a profile of the enrolled students and to determine which factors in their background, in their prior experience with computing, and in their learning behaviors during the course, predict successful completion of the course. Statistical survival analysis will be used to model the risk of dropping out. The broader impact of the project is that, by characterizing factors that positively and negatively influence students' success in MOOCs, it will allow for more informed, and hence more potentially effective, pedagogical and institutional policies aimed at increasing student success and broadening participation.