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Supportive Automated Feedback for Short Essay Answers (SAFeSEA)

短论文答案的支持性自动反馈 (SAFeSEA)

基本信息

批准号：
EP/J005959/1
负责人：
Denise Mary Whitelock
金额：
$ 31.59万
依托单位：
The Open University
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2012
资助国家：
英国
起止时间：
2012 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FJ005959%2F1
关键词：
Supportive Automated Feedback Short Essay

项目摘要

The aim of this research is to provide an effective automated interactive feedback system that yields an acceptable level of support for university students writing essays in a distance or e-learning context. Our tool will be based on an existing system supporting the online writing and assessment of essays, OpenComment (Whitelock & Watt, 2008), but this requires several problems to be solved, both in natural language processing, and in educational theory and practice. This proposal is therefore a truly interdisciplinary one.The natural language processing problems are how to `understand' a student essay well enough to provide accurate and individually targeted feedback, and how to generate that feedback automatically. We intend to use techniques from document classification (measures of semantic similarity), information extraction, document summarisation, and text generation to address these problems. The tools we build need to be flexible enough to support different types and models of feedback.The educational problem is how to develop and evaluate effective models of feedback. This requires research into the selection of the content, mode of presentation and delivery of the feedback. The primary aspects of feedback which will be investigated are: summarisation; recognition of positive achievements; location of errors of commission or omission; misconceptions or problems connected with causal relationships; tactical and strategic hints both relating to the specific issues being addressed in the essay and issues connected with `metacognition' (i.e. self awareness of the learning process), and self-regulation of the learning process. For feedback to be effective, it should assist students not only to manage their current essay-writing task, but it should also lead to further development of their essay-writing skills, the skills associated with efficient self-regulation, and their motivation to complete their course. The methods used to obtain data on effectiveness will be student surveys, interviews with selected participants, analysis of the various versions of the essays submitted for feedback, and the quality of the final essay.

本研究的目的是提供一个有效的自动化互动反馈系统，产生一个可接受的水平的支持大学生写论文在远程或电子学习环境。我们的工具将基于现有的支持在线写作和论文评估的系统OpenComment（Whitelock & Watt，2008），但这需要解决自然语言处理和教育理论与实践中的几个问题。自然语言处理的问题是如何“理解”学生的文章，以便提供准确的、有针对性的反馈，以及如何自动生成反馈。我们打算使用文档分类（语义相似性的措施），信息提取，文档摘要和文本生成技术来解决这些问题。我们构建的工具需要足够灵活，以支持不同类型和模型的反馈。教育问题是如何开发和评估有效的反馈模型。这就需要对内容的选择、介绍方式和反馈的提供进行研究。将调查的反馈的主要方面是：总结;积极的成就的认可;委员会或遗漏的错误的位置;与因果关系有关的误解或问题;与文章中所讨论的具体问题和与“元认知”（即学习过程的自我意识）有关的问题的战术和战略提示，以及学习过程的自我调节。反馈是有效的，它不仅应该帮助学生管理他们当前的论文写作任务，但它也应该导致他们的论文写作技能，与有效的自我调节相关的技能，以及他们完成课程的动机的进一步发展。用于获得有效性数据的方法将是学生调查，与选定的参与者进行访谈，分析提交反馈的论文的各种版本，以及最终论文的质量。