Don't start your lit review with a question

Dear Scholar,

Whenever you look for advice on literature reviews, it always starts with defining either a question or a topic. But this is backwards since good questions can only come once you are substantially familiar with something. Instead, I suggest starting your literature review with an overview, drilling down to your niche, learning it intimately and then, as your last step, defining the question.

This article explores one of the many topics we are going to focus on in the upcoming literature review webinar. Down below is also a way to get a complementary ticket for free.

​The Best Way to Start Your Literature Review (Hint: It’s Not with a Question) (15 min read)

This week's article argues against starting a literature review by defining a research question. Instead, it suggests first gaining a broad understanding of the field to ensure you ask informed, relevant questions. The proposed strategy includes using both classical and AI methods to get an overview, narrowing down to an exciting niche, taking targeted notes, and mapping concepts to find research gaps. By following this approach, you end up with meaningful research questions that naturally emerge from your deep understanding of the topic.

​

​

Webinar, Oct 26th: The AI Literature Review

​

Get a free ticket with a Litmaps subscription.

I have partnered with Litmaps to give everyone signing up for their yearly subscription a free webinar ticket. The subscription is worth 120$, while the webinar is 40$. This means you get a 33% discount on Litmaps and learn how to use it in the webinar. Click the button, to learn more.

​

Topic highlight: Using AI to read through dozens of papers at once

A good literature review should be broad as well as deep. To find the balance you need to identify which papers are more relevant to your research question and which are less. AI can help you identify these papers and extract information from secondary sources.

In the upcoming webinar, I am going to present a workflow to do just this. In a nutshell, here is how it works:

1. Identify as many papers as you deem relevant
2. Analyze them with AI and extract areas of focus.
3. For each area: Use a semantic search to identify which papers align with it.
4. Use a different type of AI analysis to look at each focus area in detail using the papers found.

​

If you want to learn this technique in detail, sign up for the upcoming webinar. I will also introduce new tools that help you do this easily.

​

Who is coming to this webinar?

The webinar is for academics of all levels and all domains. I always ask my participants to tell me a little bit about themselves to make the webinars more engaging for everyone. This is the result:

For 45.6% this will be their first webinar/course with me. For the majority of you Synthesizing information is a key point to get from this webinar (83.3%). One of the key tools we are going to use, SciSummary, is known only by 23.3% of the participants.

​

​

Ilya Shabanov,

The Effortless Academic​

Don't want to receive emails like this: Unsubscribe from newsletter only .
Want to unsubscribe from all future emails? Unsubscribe from everything.
Your Preferences.