Section A: Project Information
This project addresses the issue of low efficiency and vague feedback in university English writing assignments by proposing the development of a new AI writing assistant tool, UniWrite AI. This tool leverages natural language processing (NLP), machine learning, and artificial intelligence technologies to quickly scan student essays, accurately identify grammatical errors, analyze the structure of the text, offer suggestions for vocabulary and sentence optimization, and provide ideas for expanding on the essay topic. Its key innovation lies in reducing the heavy workload of teachers while providing students with personalized and comprehensive feedback to enhance their writing skills. The design philosophy is to empower teaching with technology, streamline the teaching process, and improve teaching effectiveness. The potential impact is to significantly enhance the quality of university English writing instruction and promote the overall development of students' writing abilities. The participants of this project are three classes I teach in Wuhan, consisting of 90 students who are currently in their second year. They come from various majors across the university, have a medium level of English proficiency, and most are capable of passing the College English Test Band 4. Therefore, the introduction of this tool will greatly meet their needs for writing improvement.
Section B: Participant Information
| Title | First Name | Last Name | Organisation/Institution | Faculty/Department/Unit | Phone Number | Current Study Programme | Current Year of Study | Contact Person / Team Leader | |
|---|---|---|---|---|---|---|---|---|---|
| Ms. | Zhenru | Shang | The education university of Hongkong | MIT | shang.zr@hotmail.com | +8615527808615 | Doctoral Programme | Year 2 |
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Section C: Project Details
In university English writing instruction, teachers often face the challenge of providing only general evaluations and scores for a large volume of assignments, as they lack the time to conduct a detailed analysis of each essay's logical structure, grammatical errors, and vocabulary usage. This issue severely hampers the improvement of students' writing skills and increases the workload for teachers. This project is inspired by the need to address this challenge using AI technology. The underlying assumption is that NLP has made significant progress and can be effectively applied to writing correction, offering students more precise and comprehensive feedback. With the increasing acceptance of technology-enhanced teaching, this project has a high potential for success.
Feasibility and Functionality
This project will implement the solution using existing natural language processing technologies and machine learning algorithms. The core functions of UniWrite AI include:
Grammar Error Detection and Correction: A deep learning-based grammar checking model that can accurately identify and correct various grammatical errors in student essays.
Text Structure Analysis: Text analysis algorithms to evaluate the logical structure of the essay and provide suggestions for improvement.
Vocabulary and Sentence Optimization: Suggestions for vocabulary replacement and sentence optimization to help students enhance the diversity and accuracy of their language expression.
Idea Expansion for Writing: Providing related expansion ideas and writing materials based on the essay topic to stimulate students' creativity.
Personalized Feedback Reports: Generating detailed writing feedback reports covering grammar, vocabulary, structure, and content, to help students understand their writing strengths and weaknesses.
To ensure a good user experience, UniWrite AI will feature a simple and user-friendly interface, and continuously optimize its functions based on user feedback. Performance indicators include the accuracy of grading, the timeliness of feedback, and the stability of the system, which will be used to assess its effectiveness.
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Innovation and Creativity
UniWrite AI is innovative in its use of AI technology to solve the problem of university English writing correction. It not only can quickly and accurately detect grammatical errors but also conduct a comprehensive analysis of the essay's structure, vocabulary, and sentence patterns, and provide optimization suggestions, which is difficult to achieve with traditional correction methods. In addition, it can offer expansion ideas based on the essay topic, further stimulating students' writing inspiration. These innovative elements can more effectively help students improve their writing skills and enhance its effectiveness in addressing the challenge of improving students' writing abilities.
Scalability and Sustainability
To ensure the scalability of the solution, UniWrite AI will adopt a modular design, facilitating the expansion and upgrading of functions in the future. As the number of users increases, potential bottlenecks can be addressed by optimizing algorithms and increasing server resources. In terms of sustainability, regular collection of user feedback will be conducted to continuously optimize functions according to changes in teaching needs, adapting to evolving user requirements. Moreover, by making rational use of server resources and optimizing system performance, environmental sustainability can also be ensured to a certain extent.
Social Impact and Responsibility
This project enhances the quality of university English writing instruction, which helps improve students' overall quality and enhances their employability, thus having a positive impact on society. The main beneficiaries are second-year university students from various majors, with a medium level of English proficiency, and most are capable of passing the College English Test Band 4. By improving their writing skills, their learning experience can be enhanced, and their comprehensive development can be promoted. Indicators such as the improvement of students' writing scores and the reduction of teachers' workload can be used to measure its social impact. At the same time, the project will closely monitor changes in community needs and promptly adjust and optimize the project to better meet user requirements.
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