AI in Research

For academics and researchers at the University of Reading, AI tools can act as powerful research assistants. By accelerating administrative tasks, literature reviews, and data formatting, you can win back hours to focus on primary analysis and discovery.

Navigating Academic Integrity

AI should assist your research process, not replace your intellectual contribution. The goal is to use these tools for structuring, summarising, and formatting, rather than generating the core academic argument or methodology.

Literature Reviews

Use Case: Speeding up the initial reading phase.

Example Prompt: "Summarise this uploaded journal article. Extract the primary hypothesis, the core methodology, and list the three main limitations the authors identified."

Grant Proposals

Use Case: Overcoming the blank page for funding bodies.

Example Prompt: "Using the attached project abstract, draft a layperson's summary of the research impact suitable for a grant application, keeping it under 300 words."

Data Formatting & Analysis Prep

Generative AI is exceptional at handling tedious data formatting chores:

  • Cleaning Data: Paste messy, unstructured text and ask the AI to format it into a clean CSV table for import into SPSS or Excel.
  • Writing Scripts: Ask AI to write Python or R scripts to automate the cleaning of large datasets (e.g., removing null values or standardising date formats).
  • Reformatting Citations: Paste a bibliography and ask the AI to reformat all entries from APA to Harvard style instantly.

Brainstorming & Refinement

Use AI as a sounding board to refine your work:

  1. Upload a draft abstract and ask for suggestions to make it punchier.
  2. Ask the AI to anticipate counter-arguments to your hypothesis.
  3. Generate potential interview questions for qualitative research focus groups.

Translation & Accessibility

  • Translate foreign language abstracts to determine if a paper is relevant to your literature review.
  • Generate alt-text descriptions for complex charts and graphs before publishing them online.

Journal Guidelines on AI Disclosure

The academic publishing landscape is adapting rapidly. Always review the specific guidelines set by your target journals or funding bodies regarding the use of generative AI. Many publishers now strictly prohibit listing AI as a co-author but require explicit disclosure in the methodology section if AI was used in the drafting or data preparation process.

Security Reminder

Never upload unpublished, embargoed, or highly sensitive participant data (especially medical or identifiable information) into public AI tools. Ensure you are using internally secured enterprise environments or entirely anonymised datasets.

These pages are currently in beta. To give feedback, please contact DTS at ai.training@reading.ac.uk.