Abstract This paper introduces a deep learning-based virtual tool designed to assist emerging faculty members in improving their academic writing and research papers. With the increasing demand for faculty to produce high-quality academic content, early-career scholars often face challenges in mastering the intricacies of academic writing. This tool leverages state-of-the-art natural language processing (NLP) techniques, including transformer models like BERT and GPT, to provide personalized feedback on writing structure, clarity, academic tone, grammar, and citation management. By analyzing the user’s writing style and discipline-specific conventions, the tool delivers context-aware suggestions to enhance the quality of research papers and other academic documents. The paper explores the design, features, and application of the tool, evaluating its effectiveness through a user study involving novice faculty from various disciplines. Results demonstrate the tool’s potential in improving writing efficiency, content quality, and user satisfaction, suggesting that AI-driven writing assistants can significantly enhance the academic writing experience for emerging faculty.
Shamim et al. (Fri,) studied this question.