Using artificial intelligence in academic writing and research

An essential productivity tool

Dados Bibliográficos

ID23328267
AutoresMohamed Khalifa (0009-0009-0405-7470, La Trobe University, autor correspondente), Mona Albadawy (UNSW Sydney, autor correspondente)
Ano2024
Volume5
Páginas100145
Data de publicação2024-01-01
Open AccessSim
TipoARTICLE
PeriódicoComputer Methods and Programs in Biomedicine Update (JOURNAL)
Identificadores do periódicoISSN: 2666-9900 • E-ISSN: 2666-9900
EditoraElsevier BV (PUBLISHER)
DOI10.1016/j.cmpbup.2024.100145
OpenAlexW4392452942
IdiomaEN
Citações recebidas65
Referências citadas35

Academic writing is an essential component of research, characterized by structured expression of ideas, data-driven arguments, and logical reasoning. However, it poses challenges such as handling vast amounts of information and complex ideas. The integration of Artificial Intelligence (AI) into academic writing has become increasingly important, offering solutions to these challenges. This review aims to explore specific domains where AI significantly supports academic writing. A systematic review of literature from databases like PubMed, Embase, and Google Scholar, published since 2019, was conducted. Studies were included based on relevance to AI's application in academic writing and research, focusing on writing assistance, grammar improvement, structure optimization, and other related aspects. The search identified 24 studies through which six core domains were identified where AI helps academic writing and research: 1) facilitating idea generation and research design, 2) improving content and structuring, 3) supporting literature review and synthesis, 4) enhancing data management and analysis, 5) supporting editing, review, and publishing, and 6) assisting in communication, outreach, and ethical compliance. ChatGPT has shown substantial potential in these areas, though challenges like maintaining academic integrity and balancing AI use with human insight remain. AI significantly revolutionises academic writing and research across various domains. Recommendations include broader integration of AI tools in research workflows, emphasizing ethical and transparent use, providing adequate training for researchers, and maintaining a balance between AI utility and human insight. Ongoing research and development are essential to address emerging challenges and ethical considerations in AI's application in academia.

Academic writing · Data science · Engineering ethics · Knowledge management · Mathematics education · Political science · Relevance (law) · Structuring · Workflow · Artificial Intelligence in Healthcare and Education · Computer Science · Engineering · Psychology

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