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Complete Guide to Conducting Literature Reviews with SciSpace Agent

SciSpace AcademyEnglishLiterature reviewStep-by-step AI literature review

TL;DR

1-min read

This hands-on tutorial walks through a complete literature review workflow using SciSpace Agent, with the aim of making reviews faster and more systematic. It is intended for students, researchers and teams working on theses, survey papers, or systematic and scoping reviews who want a repeatable process they can use again. Throughout, AI handles discovery and organisation while key studies are still read by the researcher, so the final review remains accurate and defensible.

Key takeaways

  • Setting up the review properly comes first: frame the topic, choose keywords and define inclusion and exclusion criteria, such as publication dates, study designs, populations, languages or outcomes.
  • Deciding criteria before searching keeps screening consistent, reduces selection bias and makes the methods section easier to write.
  • SciSpace Agent is then used to discover and shortlist relevant papers, and to extract methods, results and limitations from each study in a consistent format.
  • Studies are grouped into themes that form a coherent narrative, which then feeds an outline and drafts of the Introduction, Methods and Discussion sections.
  • Quality checks include verifying every citation against the original paper, confirming extracted figures and claims, watching for summaries that overstate findings and reducing bias; a shared extraction template makes errors easier to spot.
  • The tutorial closes with how to reuse the workflow and keep review work organised for future projects, whether working alone or as part of a team.
Apply it

To apply this, set your criteria first, then use SciSpace's Literature Review Generator to find papers and the Literature Review Matrix to extract details in a consistent format.

How to do it

  1. Frame the topic and criteria

    Define your review topic, choose keywords and set inclusion and exclusion criteria before starting. A proper setup makes the review systematic.

  2. Discover and shortlist papers

    Use SciSpace Agent to discover relevant papers and shortlist those that meet your criteria. This is the core of a literature review with SciSpace Agent.

  3. Extract data in a consistent format

    Ask the agent to extract methods, results and limitations from each study in the same format. Consistency makes comparison easier.

  4. Group themes and draft sections

    Group studies into themes and draft Introduction, Methods and Discussion sections. Themes turn individual papers into a coherent narrative.

  5. Run quality checks

    Verify sources, check for bias and watch for common AI pitfalls. Quality checks keep the review trustworthy.

  6. Save the workflow for reuse

    Keep your review organised so you can reuse the workflow in future projects. This saves setup time next time.

Try this on SciSpace

Frequently asked questions

What are inclusion and exclusion criteria in a literature review?

They are the rules that decide which studies enter your review, such as publication dates, study designs, populations, languages or outcomes. Setting them before searching keeps screening consistent, reduces selection bias and makes your methods section easier to write. Record every criterion so readers can understand and reproduce your choices.

How can I avoid AI mistakes in a literature review?

Check every citation against the original paper, confirm that extracted figures and claims match the source, and watch for summaries that overstate findings. Use AI for discovery and organisation, but read key studies yourself. Applying the same extraction template to every paper also makes inconsistencies and errors easier to spot.

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