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

这个渴望的项目旨在研究由哈佛大学提供的大规模在线开放课程(MOOC)，该实验是为了回应哈佛大学教师对中央资源的需求，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》，这门课程是哈佛大学所有MOOC课程中注册人数最多的一门课程(150,349人)，也是哈佛大学所有传统课程中注册人数第二多的课程(714人)。本课程的两个版本CS50x和CS50共享许多功能(讲课、习题集、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只向6.3%的注册者颁发结业证书。这为研究MOOC的高流失率提供了机会，这是一个困扰全国在线课程的问题。关于学生为什么不能完成MOOC课程，人们知之甚少。在毕业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？该项目收集了CS50x MOOC中的经验证据，以创建注册学生的概况，并确定在他们的背景、他们以前的计算经验以及他们在课程期间的学习行为中，哪些因素可以预测课程的成功完成。统计生存分析将被用来对辍学风险进行建模。该项目更广泛的影响是，通过描述对学生在MOOC中的成功有积极和消极影响的因素，它将允许制定更多知情的、因此更具潜在有效性的教学和体制政策，旨在提高学生的成功和扩大参与。

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.