Collaborative Research: Increasing Conceptual Understanding through Annotation Visualization

协作研究：通过注释可视化增强概念理解

• 批准号: 0942721
• 负责人: John Barr
• 金额: $ 3.27万
• 依托单位: Ithaca College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-10-01 至 2013-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0942721&HistoricalAwards=false
• 关键词: Collaborative; Research; Increasing; Conceptual; Understanding

Computer Science (31) This project's goal is to conduct a large study involving more than 400 students at two different institutions to study the relationship between conceptual misunderstandings, code testing and development times. Conceptual understanding is measured by engaging students in reading and annotating documents that contain both accurate and erroneous concepts, and measuring how many students detect the errors and how many iterations it takes to detect all errors. This is then compared with code debugging times with the expectation that the text engagement process will actually reduce the amount of time spent on project tasks. The project establishes a scalable model of Reading-Annotation-Visualization (RAV) that can be deployed in any of the early programming courses. RAV model proceeds by pre-analyzing the important conceptual challenges students will encounter in the programming phase and then supporting the comprehension of these concepts prior to the programming phase through annotation, visualization and classroom discussions.This project assesses the potential of a participatory reading, discussion and learning environment to improve the reading comprehension, writing, and programming skills of computer science undergraduates. It contributes to the understanding of the relationship between reading and discussion and programming skills in computer science. The project results are disseminated via conference proceedings. RAV model and Classroom Salon are shared with any other institution willing to implement a classroom instruction model where understanding of student misconceptions early in the learning process is critical to better learning outcomes.

计算机科学(31)这个项目的目标是进行一项大型研究，涉及两个不同机构的400多名学生，以研究概念误解、代码测试和开发时间之间的关系。通过让学生阅读和注释包含准确和错误概念的文档，并测量有多少学生检测到错误以及需要多少次迭代才能检测到所有错误，来衡量概念理解。然后，将其与代码调试时间进行比较，期望文本参与过程实际上将减少在项目任务上花费的时间。该项目建立了一个可扩展的阅读-注释-可视化(RAV)模型，可以部署在任何早期编程课程中。RAV模型通过预先分析学生在编程阶段将遇到的重要概念挑战，然后通过注释、可视化和课堂讨论来支持在编程阶段之前对这些概念的理解。该项目评估了参与式阅读、讨论和学习环境的潜力，以提高计算机科学本科生的阅读理解、写作和编程技能。它有助于理解计算机科学中阅读和讨论与编程技能之间的关系。项目成果通过会议记录进行传播。RAV模式和课堂沙龙与任何其他愿意实施课堂教学模式的机构共享，在这种模式下，在学习过程早期理解学生的错误概念对于更好的学习结果至关重要。