# Case Study: Systematic Reviews with AI

URL: https://research-memex.org/docs/case-studies/systematic-reviews/systematic-review-syllabus
Description: An overview of a course that applies the Research Memex approach to systematic literature reviews through inspectable human-AI collaboration.



*Systematic reviews teach orchestration because every step is inspectable.*

## Case study overview [#case-study-overview]

This page outlines a course that teaches the Research Memex approach through a common academic task: the systematic literature review. This case study demonstrates one way to build AI partnership into the research workflow, from literature discovery through to final synthesis, while keeping every step inspectable.

<Aside label="Provenance">
  The materials are based on a module originally developed for MRes students.
</Aside>

We're sharing this approach to show how researchers can develop the complete pipeline, learning when and how to work with AI as a cognitive partner. Your implementation might look different based on your field and research questions.

### Learning schedule & key topics [#learning-schedule--key-topics]

This case study is structured around four sessions, each building on the last:

| Session | Topic                                          | Core Competency            |
| ------- | ---------------------------------------------- | -------------------------- |
| 1       | Foundations of Systematic Reviews              | Understanding the "Why"    |
| 2       | Building the Human-AI Research Pipeline        | Interpretive Orchestration |
| 3       | Human vs. AI Synthesis: Learning from Practice | Critical Evaluation        |
| 4       | Advanced Agentic Workflows                     | Research Architecture      |

### Getting started with the case study [#getting-started-with-the-case-study]

To get the most out of this case study, we suggest following the [Quick Start Checklist](/docs/implementation/foundational-setup/quick-start-checklist) first. Each session also has its own detailed guide with associated readings and exercises. Adapt the pace and focus to match your own learning goals.

### Learning assessment [#learning-assessment]

The learning process is assessed through two main components:

Learning through practice (50%)

* Session 2 Exercise: Master prompt development and cognitive scaffolding using a sample literature set.
* Session 3 Exercise: Develop critical evaluation skills by documenting AI failure modes and the limitations of automated synthesis.
* In-class work: Build presentation and peer feedback abilities.

Capstone learning project (50%)

Participants choose a final project that best serves their research goals:

* Option A: Validation skills - critically compare AI vs. human synthesis approaches
* Option B: Workflow design - develop reproducible human-AI research pipelines
* Option C: Quality control - build expertise in identifying and preventing common AI failure modes

Each option develops different competencies for research with AI partners. Choose what matters most for your work.

### Tools & budget [#tools--budget]

* Essential tools: The workflows in this case study use Research Rabbit (free), Zotero (free), and Cherry Studio (an open-source tool for multi-model AI interaction). See the [API Keys Setup Guide](/docs/implementation/ai-environment-setup/api-keys-setup-guide) for more.
* API budget: For course participants, a budget is typically provided for API access. Independent learners can use free tiers from providers like Google AI Studio.

### Support [#support]

* Technical: See the setup guides for each tool.
* Content: See the [PRISMA 2020 Guidelines](http://prisma-statement.org/) and the [Cochrane Handbook](https://training.cochrane.org/handbook) for systematic-review methodology.

## Navigation [#navigation]

Next steps:

* [Session 2: Building the Human-AI Research Pipeline](/docs/case-studies/systematic-reviews/session-2-ai-powered-practice)
* [Session 3: Human vs AI Synthesis](/docs/case-studies/systematic-reviews/session-3-human-vs-ai-synthesis)
* [Session 4: Agentic Workflows](/docs/case-studies/systematic-reviews/session-4-agentic-workflows)

Resources:

* [Quick Start Checklist](/docs/implementation/foundational-setup/quick-start-checklist)