AI Literature Reviews Are So Much Better With the Triple T Method

As a PhD student, you’re likely feeling a mix of excitement and overwhelm as you embark on your research journey. Reflecting on my own experience, I remember the challenges and limitations of the tools available on the market to assist with conducting your literature review. During the COVID period, tools like Research Rabbit and Zotero were a bit more rudimentary and easier to use, and they proved invaluable in my first year. However, this realisation prompted me to share insights on how to effectively utilise such tools.

This short blog was inspired after watching the potential of AI tools showcased in “Write A Masterpiece Systematic Literature Review With AI [Next Level Strategies]” by Andy Stapleton, Please note that the advice and approaches discussed in this blog reflect my personal experience and are not professional academic advice. In this blog, I will introduce the Triple T Approach — Tactics, Techniques, and Tools — to streamline literature reviews. By integrating strategic planning, methodological execution, and AI tools like ChatGPT, Elicit, and Litmap, this approach ensures a comprehensive and efficient review process.

Be Aware of the Texas sharpshooter!

Before diving into the Triple T framework, it’s crucial to heed the advice of being wary of the Texas sharpshooter fallacy. that refers to a scenario where a person, lacking actual shooting skills, randomly fires bullets at a barn wall. Subsequently, they paint a bull’s-eye around a fortuitous cluster of bullet holes and proclaim themselves a sharpshooter. Falling into this trap can be tempting, particularly with tools that produce seemingly strong evidence, which may obscure their biases.

This is why it’s essential to question everything produced by AI, by adopting a philosophical skepticism mindset. It’s crucial to question everything produced by AI to provoke awareness of any bias existing in the data set and challenge our assumptions while evaluating evidence generated by GenAI tools and exploring different perspectives and their implications on our research direction.

This logical pitfall warns against being drawn to tools that appear to provide strong evidence, potentially concealing biases. Utilizing these tools effectively requires critical thinking skills; in this context, these skills act as your shooting skills for the Texas sharpshooter fallacy! This is why I always recommend reading more about this topic, as it introduces essential life skills to help not only grow your research but also grow as a researcher.

This approach ensures a comprehensive and efficient review process while also keeping in mind the limitations of current AI tools and their biases. When choosing each tactic, try to link it with appropriate tools and techniques while considering how they align together and the implications of such an approach on the limitations of AI tools. I have only focused on the bias challenge, but of course, there are many limitations awaiting AI in academia. Always remember that you are leading the tools, not the other way around.

What is the Triple T Approach?

The Triple T framework breaks down into Tactics, Techniques, and Tools. Tactics involve strategic decisions in structuring the review, conducting thorough literature searches, and synthesizing information. Techniques encompass methods such as AI-assisted structuring and analytical reading, while Tools consist of resources like ChatGPT and Mendeley for efficient literature management.

Applying the Triple T Approach to Your Literature Review Workflow:

Here’s a quick walkthrough of some of the concepts and strategies applied in the approach to ensure a methodical and tool-driven process, enhancing the quality and depth of your review.

1. Tactics:

• Structuring the Review: Develop a clear, organized structure for your literature review.

• Comprehensive Literature Search: Systematically search for and select relevant literature.

• Synthesizing Information: Integrating findings from various sources into a cohesive narrative.

2. Techniques:

• AI-Assisted Structuring: Using AI to generate a preliminary structure for your review.

• Targeted Literature Discovery: Employing specific queries based on your review structure to find relevant literature.

• Analytical Reading and Organization: Critically reading and categorizing literature for easy reference and synthesis.

3. Tools:

• ChatGPT and Perplexity: For generating the initial structure of your literature review.

• PaperPal and Jenni AI: Tools to assist with proofreading your initial drafts and refining your literature structure.

• Elicit or Scispace: To search for and summarize seed papers based on your structured queries.

• Litmap and Connected Papers: For discovering related literature reviews.

• Mendeley or Zetro: To manage and organize your references and PDFs.

• Docanalyzer.AI: For analyzing documents and aligning them with your review structure.

By aligning your research with this approach, you’ll streamline your workflow and lay a robust foundation for your literature review paper. Of course, this approach is flexible. For example, when you start structuring the plan for your literature review, you could use tools like Perplexity and then draft and proofread the initial paper structure using PaperPal. However, you could also gather information before you do any planning. Thus, a tactic like synthesizing information will need some techniques for targeted literature discovery through Elicit. So, please add or update any section of this approach that you feel fits your needs!