Outcome Predictions of Students in Massive Open Online Courses (OPSMOOC)

大规模开放在线课程（OPSMOOC）学生的结果预测

• 批准号: 1337166
• 负责人: Philip Sadler
• 金额: $ 25万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1337166&HistoricalAwards=false
• 关键词: Outcome; Predictions; Students; Massive; Open

This exploratory project seeks to develop methods to evaluate Massive Open Online Course (MOOC) offerings. Designed specifically for interactive study over the web, with considerable flexibility in terms of students' time commitment and scheduling, MOOCs have tremendous potential for improving access to higher education. To date, however, MOOCs have tended to exhibit high attrition rates. With enrollments in the tens or hundreds of thousands, even modest changes that increase completion rates could have a major impact on the absolute numbers of students benefiting from this new form of instruction. This project involves in-depth examination of a highly popular Harvard MOOC, offered through the edX platform. It combines primary data (on participating students' characteristics and their motivations for taking the course) with data pertaining to students' course activities in analyses (including descriptive statistics, hazard modeling, and multiple linear regression) to explore both traditional course outcomes (e.g., measures of student achievement) and persistence/attrition. By focusing on the metric of course completion early in the development of MOOCs, this project has potential to direct attention to those aspects of MOOCs that appear critical to student success and their continuing interest in STEM fields. It is anticipated that both research findings and methods of analyses can be incorporated into the instructional platform to aid instructors in monitoring difficulties and in rapid course improvement and that progress toward more uniform data collection will allow comparisons across a variety of MOOCs, particularly those with similar goals or content domains.

该探索性项目旨在开发评估大规模开放在线课程（MOOC）产品的方法。 MOOC专为通过网络的互动研究而设计，其时间投入和日程安排具有相当大的灵活性，MOOC具有改善高等教育获得的巨大潜力。 但是，迄今为止，MOOC倾向于表现出较高的流失率。 随着成千上万或数十万的入学人数，即使是增加完成率的适度变化也可能对从这种新的教学形式受益的学生的绝对数量产生重大影响。该项目涉及对通过EDX平台提供的备受流行的哈佛MOOC的深入研究。 它结合了主要数据（关于参与学生的特征及其参加课程的动机）与与学生课程活动有关的数据（包括描述性统计，危害建模和多个线性回归），以探索传统的课程成果（例如，学生成就的度量）和持久性/持久性/消耗性/消耗性。通过关注MOOC开发的早期完成的指标，该项目有可能将注意力集中在MOOC的那些方面，这些方面对学生的成功至关重要及其对STEM领域的持续兴趣。可以预料，研究结果和分析方法都可以纳入教学平台中，以帮助指导者监视困难和快速的课程改进，并且朝着更统一的数据收集方面的进步将允许对各种MOOC进行比较，尤其是那些具有相似目标或内容域的MOOC。