Improving Scientific Writing In Undergraduate STEM Classrooms: A Training Program for Students and Teaching Assistants Aided By Information Extraction Technology

提高本科STEM课堂中的科学写作：信息提取技术辅助的学生和助教培训计划

• 批准号: 1712423
• 负责人: Allen Johnson
• 金额: $ 27.86万
• 依托单位: Wake Forest University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-15 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1712423&HistoricalAwards=false
• 关键词: Improving; Scientific; Writing; Undergraduate; STEM

Scientific thinking and communication skills are vital for 21st century STEM careers. Research indicates that cycles of writing drafts, receiving actionable feedback and coaching, then making further refinements until a final product emerges is the most effective way for students to develop these skills. Ideally, students should be writing and revising routinely, but this may be time- and labor-intensive to be practical in high-enrollment STEM courses. Also, college teachers may not know how best to make high-impact writing instruction part of their classes. This project uses a research-based curriculum designed to develop scientific reasoning skills through writing, combining text analysis technology with an integrated writing training program. The project will test whether students' writing skills development can be accelerated by combining reading and text annotation exercises, automated feedback using text analysis technology, and holistic feedback from instructors. Graduate teaching assistants' mastery of these training methods will also be examined. Finally, the project will look directly at technology impacts by measuring how much automated feedback students use, and how that translates into progress towards writing mastery.The project's goal is to improve scientific writing skills of undergraduate students by promoting adoption of evidence-based writing training. The project has three interacting elements. 1) STEM Automated Writing Help Tool (SAWHET) is a computer-based tool designed to teach undergraduates scientific writing according to best practice principles. SAWHET collects texts of draft student lab reports, conducts text analysis, then gives students tailored feedback. 2) The Biology Thesis Assessment Protocol (BioTAP) is a protocol for assessing undergraduate STEM research theses. BioTAP will be used to teach students to score published papers and training reports before writing their first report. 3) Graduate teaching assistants will be trained to teach and assess scientific writing more consistently. The central research question will be addressed: Can an integrated writing training program combining these three elements accelerate student writing skills development? Assessments will include standardized student and teaching assistant knowledge, self-efficacy, and experience surveys; videotape analysis of classroom instruction; lexical complexity modeling of student writing; qualitative analysis of instructor comments on reports, and student lab evaluations. This project will provide much-needed data on how technology support affects development of scientific writing skills. Project products will include a repository of approximately 4,000 annotated biology student lab reports that can be used as training data for linguistic analyses, to test other automated systems, and other research.

科学思维和沟通技巧对于21世纪STEM职业至关重要。研究表明，写草稿，接受可操作的反馈和指导，然后进一步改进，直到最终产品出现的周期是学生发展这些技能的最有效方法。理想情况下，学生应该经常写作和修改，但这可能是时间和劳动密集型的高入学率STEM课程。此外，大学教师可能不知道如何最好地使高影响力的写作教学的一部分，他们的课。该项目采用研究型课程，旨在通过写作开发科学推理能力，结合文本分析技术与综合写作培训计划。 该项目将测试学生的写作技能的发展是否可以通过结合阅读和文本注释练习，使用文本分析技术的自动反馈，以及教师的整体反馈来加速。研究生助教对这些培训方法的掌握情况也将受到检查。最后，该项目将通过测量学生使用多少自动反馈以及如何将其转化为写作掌握的进步来直接研究技术影响。该项目的目标是通过促进采用循证写作培训来提高本科生的科学写作技能。该项目有三个相互作用的要素。1)STEM自动写作帮助工具（SAWHET）是一个基于计算机的工具，旨在根据最佳实践原则教授本科生科学写作。SAWHET收集学生实验报告草稿的文本，进行文本分析，然后给学生量身定制的反馈。2)生物学论文评估协议（BioTAP）是评估本科STEM研究论文的协议。BioTAP将用于教学生在撰写第一份报告之前对已发表的论文和培训报告进行评分。3)研究生助教将接受培训，以更一致地教授和评估科学写作。中心的研究问题将被解决：一个综合的写作训练计划结合这三个要素，可以加速学生的写作技能的发展？评估将包括标准化的学生和助教知识，自我效能和经验调查;课堂教学的录像带分析;学生写作的词汇复杂性建模;教师对报告的评论的定性分析，以及学生实验室评估。该项目将提供急需的数据，说明技术支持如何影响科学写作技能的发展。项目产品将包括一个约4,000份带注释的生物学学生实验室报告的存储库，这些报告可用作语言分析的训练数据，以测试其他自动化系统和其他研究。