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Conducting Literature Reviews and Analysis Efficiently with AI

Jonathan M. Torres, MLIS, MAEnglishLiterature reviewStep-by-step AI literature review

TL;DR

1-min read

In this 60-minute, instructor-led tutorial, Jonathan M. Torres, MLIS, MA, Associate Professor and Business and Data Services Librarian at Rutgers University-Newark, a LEADING Fellow selected for OpenAI Academy's Professors Teaching with AI series, presents evidence-based strategies for applying generative AI to research through SciSpace. It is aimed at academic librarians, researchers and information professionals who want to bring AI into their work and learn SciSpace basics. Attendees received the slides afterwards, and the tutorial offers a grounded starting point for guiding others as well as improving one's own research practice.

Key takeaways

  • The tutorial opens with an overview of generative AI models and why they matter in academic settings, giving context for how students and researchers now search for information.
  • It then shows how SciSpace can support literature review and analysis, helping users move from exploratory searching to a clearer picture of the research on a topic.
  • Citation management is covered as part of the same workflow, so sources stay organised while research is under way.
  • A practical segment focuses on writing prompts that retrieve more relevant information: be specific about topic, population, time frame and the output you want, ask for sources with each claim and refine based on results.
  • Librarians can use these tools to demonstrate effective prompting and to teach students to verify AI outputs against original sources.
  • Information literacy remains central, since users need to understand both the strengths and the limitations of generative AI for academic work.
Apply it

To apply this, try a structured prompt in SciSpace's Literature Review Generator, then summarise key sources with the Paper Summarizer and check them against the originals.

How to do it

  1. Understand generative AI models

    Learn the basics of generative AI models and their value in academic work. This helps you choose appropriate uses.

  2. Run a literature review in SciSpace

    Use SciSpace's literature review tool to search and analyse papers on your topic. This is the core of efficient literature review with AI.

  3. Write more effective prompts

    Refine your prompts to be specific about what you need. Better prompts retrieve more relevant information.

  4. Manage citations as you go

    Use the citation generator to keep references organised during your research. This prevents citation work piling up at the end.

  5. Share strategies with others

    Pass evidence-based strategies on to students and colleagues, especially if you are a librarian. This spreads good practice.

Try this on SciSpace

Frequently asked questions

How do I write better prompts for academic research?

Be specific about your topic, population, time frame and the type of output you want, such as a comparison table or list of key studies. Ask for sources with each claim, then refine the prompt based on what comes back. Clear, structured prompts generally return more relevant and verifiable information.

How can librarians use AI tools to support researchers?

Librarians can use AI tools to speed up exploratory searching, demonstrate effective prompting, and teach students to verify AI outputs against original sources. They also play a key role in information literacy, helping users understand the strengths and limitations of generative AI for academic research.

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