Approaching a Research Question

The very idea of “research” may raise cringed eyebrows from many.

What may come to mind is the notion of aimlessly shooting in the dark attempting to answer some pertinent, and some not-so-pertinent questions.

Well, it is that and much more. Having had the experience of searching for answers and decoding some research questions throughout my ten Fellowship months, there are a number of things I would have done differently now (like every other task in the world).

When you are stuck in the middle of ambiguity and uncertainty, as is typical of a research setting, it is always helpful to have a plan of action. So here goes the top 4 lessons I learnt as I went about exploring unknown territories, forging new paths and discovering new directions along the way:

Image source: https://www.searchenginejournal.com/which-seo-skill-do-practitioners-think-is-the-most-important-poll/250447.

1. Define the Problem Statement

Some might say “Duh! Isn’t that obvious?” Sadly, it isn’t always! At times, one gets so engrossed in the area of research that one is exploring that it is not uncommon to lose direction and end up wondering where you had begun. In such a scenario, a well-thought out, clearly articulated, precise research question is extremely important, so that every time you tend to go astray, a simple question like, “Is this pertinent to the question I am trying to answer?” will help you stay on track. However, being clear and precise with your problem statement does not mean that you need to be quick with it. Take your time! Problem statement definition is often the first step of a project life-cycle, but a lot goes in before you reach to that succinct problem that you are going to spend days and weeks mulling over. And this brings me to the next lesson.

2. Do Your Literature Survey First and Do It Well

Literature reviews are not just meant to be documented and analysed when you finally get down to penning your research paper. While many might put off the tedious task of going through tonnes of published papers for the end, it does pay off to do it at the very beginning. Firstly and most importantly, it informs you of the research already carried out in the field and helps you identify the gaps that your research could potentially fill in. Secondly, it opens your mind to new ideas and possibilities that can be potentially explored. While its always enlightening to study new inventions and discoveries, you wouldn’t want to do the same reading again and again. So make it a point to summarise every paper that you have read in relation to your upcoming research. Your summary can be a general synopsis of the learning you derived from the paper or can follow a structured approach of documenting each paper, for example, adopting the STAR methodology of describing each work (S-Situation or Problem Statement, in this case, T- Task, A- Approach, R- Result).

3. Know Your Data

Before you start on the actual ground work of analysing your data, it is essential that you have a fair idea of what you are dealing with (in case of data that you haven’t collected yourself) and if it is worth your effort in the days to come. Some critical questions might be: What attributes does the data have and are they relevant to your research question? How complete is the data or is it plagued with missing values? Is the representative of the population that you are trying to study? Dabble with your data set for a while and get a feel of the numbers before you actually jump onto analysing it.

4. Find the Right Guidance

While google might be there to answer all your questions, it is important that you bring on board an advisor to guide you through your research study. The person could be anyone with the domain knowledge and the technical expertise, capable of giving you direction when you are stuck and helping you foster the ideas that you might have. Right from defining your problem statement down to publishing your results, you would need someone to bounce ideas off, review results with and know the feasibility of your proposals. Hence, get the right guidance!

While these points may be derived from my experience doing technical research using data analytics, some aspects of it are universal and might apply to any research study. Keeping them in mind would definitely help you make productive use of your time and ensure that you get the best results from your efforts.

An Indian by nationality, an engineer by profession and a tinkerer by habit, Asra aspires to explore the world beyond its confines and come up with solutions that can drive change, thereby promoting better quality of life for all. A Bachelors in Technology specializing in Computer Science & Engineering, Asra has worked for a leading Bay Area company for two years before taking up the AIF Clinton Fellowship. With the goal of applying technology and analytics to the field of developmental policy, Asra is seeking to answer some of the pertinent challenges faced by India's development sector. During her tenure as a Fellow, Asra will be working with IFMR LEAD in the domain of data science for public policy. When she is not mulling over life and its intricacies, you might find her engrossed in a book or enjoying an engaging conversation.

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