Originally published on Medium as @mapfulness on May 6, 2019

As a media studies teaching assistant who also happens to be a librarian, I get a lot of questions about best studying and notetaking practices. Whether you’re a student learning how to study in college for the first time or a professional who needs to get up to speed on a topic, it can be bewildering to set about learning something new on your own. Where to start?

I put this quick guide together of the process I use in grad school that helps me structure my knowledge work. None of the components of this process are original and you have probably encountered many of them at some point. They are meant to help people who need to conduct self-directed study in a domain in which they may have little to no prior knowledge. And by process, I’m talking about workflow.

Knowledge work is work and any independent research project can benefit from some form of workflow.

It always surprises me when it doesn’t occur to students that effective studying is serious work and requires some planning. But planning can take away some of the information overload of learning — it even helps make it enjoyable. Think of the workflow as a way to organize your research: it gives you an opportunity to define your purpose, form better search queries, and make sense of your search results by identifying key elements of relevance. It’s an iterative process that can keep you on task with your learning and can even suggest new conceptual paths you might want to branch out into.

So a workflow might go like this:

1) Motivation: Define your problem or objective. You have to think about purpose: what do you want to accomplish by doing this deep dive into your subject domain?

2) Search: Exploratory search: Develop questions (you might have initial ones, but you’ll also develop ones as you read), and let those questions guide your search. Refining the search: You might make a list of keywords; I find this helps as I’m skimming something to assess relevance. When triaging your results, it’s useful to ask whether the reading helps you answer your question or addresses something important in one of your keywords.

3) Read: As you read, you may want to organize your readings according to themes. For instance, if you are learning about a sprawling subject like Big Data or AI, you might sort readings into subdomains such as machine ethics, robot ethics, decision support tools, surveillance, or algorithmic bias. This can help you with your mental mapping of a new subject’s information space. It can also help you see where readings in the themes connect, too. I tend to do a lot of informal concept mapping during this part. At first, it is overwhelming. You may cast your net wide during your search activities and now you have to actually just work through your results to see what’s relevant (or might be) and what isn’t useful to you. It’s often a process of reduction, expanding your search again as you discover new ideas, have new questions, make new connections, and so on.

4) Record: First notes are important — they’re your first impressions of a conceptual space. I write these out and label them as first notes. I then label second notes, third notes, etc. The idea here is to start off your notetaking like a skeleton you are filling in, so you want to leave room to add notes in the future. You can trace the evolution of your own understanding this way because once your understanding changes, you cannot go back to a prior state of understanding. These notes end up being useful in various ways you won’t discover until later reflection (particularly if you’re doing any kind of modelling). A lot of research requires a kind of constant dialogue with yourself, which sets you up for the heavy cognitive work in the next step.

5) Think: Seriously. This part is just about letting it simmer, going back to readings, maybe pulling in new ones, making new notes, talking about your ideas with others; anything that helps you wrap your head around the contentions, contradictions and possibilities in the information space you’ve immersed yourself in. Reflection, frustration, it’s pretty much normal — hopefully by this time you grow to love the questions even more now than you did at the start. It’s the best part, but it’s also the hardest. And it never really ends.

6) Communicate. Whether you include this step depends on the purpose of your independent study. Chances are that you may be called upon at some point to teach others what you know. All that rich complexity you now get to share, so you might think about how you would explain your research clearly to people. What motivated this work? What did you discover? Why should anyone care about this?

Things I’ve learned as a research student and TA

As you search and read:

Think about your purpose: you’re reading why? You want to think about whether you’re interested in understanding the theoretical landscape or reading as a practitioner looking for applicable solutions in your organization, for example. Because these are different reads, and a thorough reading list may require consideration of both theory and praxis. Knowing (generally) what you want and need from your research readings can help you stay on task because there’s always so much you could read.

You should also have research questions.

You might have some already or some may emerge as you work through the body of knowledge. When you realize you’ve got a question, you can then think about what kind of information you need to answer it. For instance, if you find you have a question about whether or not facial recognition is biased, you’d want to look for studies on facial recognition software and look at the results and discussion sections of those papers closely. Were the recognition results accurate? If not, which people were affected? You’d also want to pay attention to the works referenced in such papers as they can be helpful in exploring further into a conceptual area.

As you take notes:

As I mentioned, notes should be iterative. What you pull from a first reading will be different from what you pull after having read more papers/texts/articles/news stories, etc. It’s kind of like uncovering the map in Skyrim: you wander around a bit, and then eventually you find your map populates with place name markers. You can go back to those place names (papers, authors, studies) knowing this time what to expect and having a better idea of what you’re looking at. You develop your own internalized representation of the information space.

How I work: I go through my reads paragraph by paragraph, pulling out key ideas, terms, people, questions, results, etc. I highlight a lot. It helps sort out how I should be working across readings, particularly subdomains. By this I mean I organize reads thematically: I have a section of readings where the focus is human information behaviour, another theme is knowledge organization, another is information retrieval, and of course, a huge theme for me is health informatics. All of these themes are organized based on what they can help me answer. For example, information retrieval readings will contain background I need to understand facets of exploratory search. And these themes play off each other — as I read I may discover papers in my human information behaviour list that help me answer questions in my information retrieval readings, like how people form search queries.

As I mentioned, your notes become important, even if they are just your earliest list of keywords. They help you see how the concepts all hang together. Think of them as a cognitive tool you can use to identify trends in your readings, new questions, or possibilities for future study.

The point of a workflow for learning is to give structure and direction to an activity that can easily create information overload for a non-expert.

This is the process that works for me — don’t be afraid to adapt your independent research workflow to your own context.