Within the Indian education system, psychology is categorized under “Arts.” This is misleading because in fact, psychology is a science. Psychological science refers to the body of knowledge (concerning the mind, brain, and behavior) that has been generated using the scientific method. For instance, one might wonder whether motivation is related to productivity or how depression affects health. Students and researchers of psychological science use the scientific method to answer such questions. The scientific method roughly involves the following:
Identifying factors of interest: The factors of interest are called ‘variables’ because they vary in some way and might help us infer a cause-and-effect relationship. Identifying variables is subjective to the research topic. For example, one might think motivation is related to productivity wherein the variables of ‘motivation’ and ‘productivity’ are of interest.
Formulating a research question: If two variables are indeed related, how and why do we think they are related? For instance, how do we think motivation affects productivity? We might hypothesize that those relatively higher on motivation will be more productive than those lower on motivation. Note that when formulating such a hypothesis, it is important to make the comparisons clear––here we are explicitly comparing productivity among people high on motivation to people low on motivation. In another type of comparison, we might have more than 2 groups (e.g., people with high/moderate/low motivation). Again, the type of comparison is subjective and specific to the research question.
For students: It is customary to devise your research question based on prior findings in the field, but it is important to remember that a hypothesis is your theory of the relationship between two factors. Though this makes your research more personalized, do not let your research become personal––do not invest your energies in trying to prove your hypothesis true; instead, let the data do the talking.
Testing the research question: Once the hypothesis is formulated (e.g., people relatively higher on motivation will be more productive than people lower on motivation), we formally test the hypothesis. In psychological science, we can test a hypothesis using psychometric tools that are created by experts to reliably measure variables of interest. In the aforementioned example, we might use two different tools to estimate a person’s motivation and productivity levels respectively. A psychometric tool that measures productivity might include a question such as, “How many hours do you work per week?”
For students: Broadly, it is advisable to use psychometric tools that have well-established norms, high reliability, validity, and generalizability. It is also possible to develop psychometric tools for specific research purposes. For more on this, read this chapter or visit this website.
Collecting data: Once we have decided on the variables of interest, research question, and psychometric tools, we move on to the data collection phase. This involves recruiting participants who will provide responses to the psychometric tools. In India, data collection might be particularly challenging because of limited funding. However, free survey software such as Google Forms and Survey Monkey are especially designed to create, distribute and collect data using online surveys. When funding is available, researchers could crowdsource data by paying people to participate in online surveys (e.g., using Amazon’s Mechanical Turk) and use paid survey software to collect data (e.g., Qualtrics).
For students: How do you decide how many participants to recruit? Deciding on your sample size can be challenging because there are no established norms to do this. There is an age-old rule of thumb which posits that recruiting 30 participants constitutes a large enough sample for any psychological research. However, N = 30 is simply a bad research practice. I will address the various ways one can decide on the size of their sample in a future post but for a simple explanation on why this decision is important visit this website or read this paper. For more on crowd-sourcing, visit this website.
Analyzing the data: After collecting responses from participants, researchers analyze the responses using appropriate statistical techniques and deduce inferences. To simplify, imagine a teacher who wants to determine students who scored above and below average on a test. To do this, the teacher will first have to find the class average and then group students relatively. Similarly, a researcher will analyze participants’ responses to determine specific trends in the data and deduce conclusions based on the observed trends. Results based on studies that utilize the scientific method aim to expand the knowledge in the field and help tackle real-world problems. For instance, if data from a study suggests that people high on motivation are relatively more productive than those low on motivation, this can be informative while making hiring decisions.
For students: Choosing an appropriate data analysis technique is essential and based on the specifics of your research question. The appropriateness of the technique will likely change from one research question to another. The recent wave in psychological science is to analyze data using some programming language like R or Python (click here to know why programming is essential for students). However, researchers in India have traditionally used programs with a simple point-and-click interface, such as SPSS. No matter the techniques, the important thing to remember is to let the data do the talking. Avoid research misconduct at all costs because in the end, all research is informative––whether the findings support your hypotheses or not.
To learn more about enhancing your research skills, watch out for our next blog.
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About the author
Prachi is a PhD student working with Dr. Joe Cesario at Michigan State University. She holds two Master's degrees: one from Fergusson College, Pune and the other from Arizona State University. She has previously worked at The Bishop's School, Pune with children having learning disabilities. Broadly, her research interests focus on judgement, decision-making, and social cognition. Her other interests include improving statistical practices and promoting open science practices in psychological research.
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