Emerging Research - Empirical Research-- Measuring the Impact of 0nline Discourse in Undergraduate STEM Courses: Semi-automatic Assessment of Large Discussion Board Corpora

新兴研究-实证研究--衡量本科STEM课程中0nline话语的影响：大型讨论板语料库的半自动评估

• 批准号: 1008747
• 负责人: Yigal Arens
• 金额: $ 30万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2015-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1008747&HistoricalAwards=false
• 关键词: Emerging; Research; Empirical; Measuring; Impact

The investigators seek to explore the extent to which the quantity and quality of student participation in course discussion boards (a.k.a. online asynchronous discussions (OAD)) is associated with retention in or dropping out from undergraduate computer science and industrial engineering majors. This study represents a planning and pilot study using data from discussion board enhanced STEM courses at the University of Southern California. The ultimate goal of the investigators' intended future research will be to produce knowledge usable in making more effective use of this learning technology.The methods include computational analysis of the discussion text, a survey questionnaire, and information gathered from the registrar's office. Machine learning/natural process learning techniques will be used to process the data. The investigators will use generalized linear modeling and Multivariate Analysis of Covariance techniques in their analysis. Additionally, the investigators seek to determine differences in participation by demographic characteristics and language/technical backgrounds.Discussion boards are now commonplace in undergraduate STEM learning environments, yet a solid base of research on their use and on user behaviors does not exist. This research is intended to begin to fill that gap. And, given many instructional reforms depend upon them, it is vital that we understand these factors better in order to improve instruction and learning.

调查人员试图探索学生参与课程讨论板（又名“讨论板”）的数量和质量在多大程度上影响了学生的参与。在线异步讨论（OAD））与计算机科学和工业工程专业本科生的留校或辍学有关。 这项研究是一项规划和试点研究，使用的数据从讨论板增强STEM课程在南加州大学。 研究人员未来研究的最终目标是产生可用于更有效地利用这种学习技术的知识，方法包括对讨论文本的计算分析、调查问卷和从注册办公室收集的信息。 机器学习/自然过程学习技术将用于处理数据。研究者将在他们的分析中使用广义线性模型和多元协方差分析技术。此外，调查人员还试图通过人口统计特征和语言/技术背景来确定参与的差异。讨论板现在在本科STEM学习环境中很常见，但对它们的使用和用户行为的研究并不存在。 这项研究旨在开始填补这一空白。 而且，鉴于许多教学改革都依赖于这些因素，我们更好地理解这些因素以改善教学和学习至关重要。