Structural Vetting Of Research Proposals: Problematisation and Solving with Artificial Intelligence

Abstract

The structure of content in academic writing is formal and research proposals with poor structure is a concern during supervision. In supervision pedagogy, proofreading of research proposals is an important routine task involving various tools and time commitment. In this paper, we have motivated the need for an Artificial Intelligent (AI) tool that can assist a human
expert in the process of vetting the structure of research proposals. The research method involves interviewing experts with vast experiences in postgraduate supervision about the concept of structural vetting, and the time it takes when there are many students. We identified
some of the issues facing postgraduate supervisors for which an implementation of an AI tool would be beneficial. The survey was done using an interactive AI chatbot, available at https://bit.ly/3bFK3gV, which allowed for capturing feedback survey from academics in an engaging and interactive manner. All respondents identified poor structure as an issue in submitted research proposals and only 34% of the respondents’ supervisors would consider research proposals with poor structure for acceptance into further postgraduate studies.

Keywords: Postgraduate Supervision, Document Vetting, AI Tool, Structural Editor, Supervision Pedagogy