Integrating Devops And Natural Language Processing To Streamline Thesis Management

Abstract

The existing system for handling university thesis reports mainly focuses on simple processes like storing and submitting files but requires more advanced content analysis and grammar detection services. There is a limitation to the above scenario, as students need help to refine their work, and commonly available tools like Turnitin that would make this possible can be accessed only by the faculty. In addition, these advanced tools are expensive and cumbersome to integrate into existing systems and, hence, hard to access. More faculty time and effort may be required during peak submission periods to manually assess complete theses, which could be more efficient with the current methods. The cumbersome and error-prone process always ended with wrong module formatting, citation mistakes, and inconsistent grading. These problems signal the development of a better thesis report management system that represents a higher level of student work and facilitates the educational process. To cope with those issues, we recommend a new thesis report management system that standardizes content analysis, grammar correction, and format validation, making these tools accessible to students and faculty. The system is expected to help the school develop a system that can be used and will reduce the burden on the lecturers regarding administrative work, making the educational process more efficient and improving the students' work. Implementing a thesis report management system facilitates a conducive academic environment by ensuring equitable access to essential educational resources for students. It enhances pedagogical efficacy through expeditious and constructive feedback mechanisms for educators.