How to Explain Your Research Question in Everyday Language

Okay, this is a fantastic and crucial skill! Explaining a research question in everyday language means making it relatable, understandable, and free of jargon for someone who isn't an expert in your field.

The core idea is to go from a precise, technical question to a simple, "kitchen table" conversation starter.

Core Idea: Focus on the "What," "Why," and "Who Cares?"

Before you even write, ask yourself:

• **What's the real problem or curiosity?** (The underlying human/societal/natural issue)


• **What don't we know about it yet?** (The gap in knowledge)


• **What are we trying to find out specifically?** (Your research question, simplified)


• **Why does finding this out matter?** (The "so what?")

Key Principles for Everyday Language:

• Strip the Jargon: Go through your question word by word. If a word isn't understood by a 10-year-old or your non-scientist neighbor, change it or explain it simply.


• Use Analogies: Can you compare a complex process to something familiar (e.g., a cell to a tiny factory, a network to a road system)?


• Focus on the Outcome/Impact: Why should anyone care about the answer? How might it affect lives, the environment, or our understanding of the world?


• Start Broad, Then Narrow: Briefly set the stage with the general problem before introducing your specific question.


• Use Active Voice: "We are investigating..." is often clearer than "The investigation was conducted..."


• Frame as a Simple Question: Sometimes, just rephrasing your research question as a very simple, direct question is powerful.

Practical Steps to Explain Your Research Question:

• Write down your original, technical research question.


• Underline all the jargon and complex terms.


• For each underlined term, brainstorm a simpler synonym or a very brief, plain-language explanation.


• Example: "endogenous retroviral elements" -> "old bits of virus DNA already in our bodies"


• Example: "transcriptional regulation" -> "how genes get turned on or off"


• Example: "cognitive development trajectories" -> "how children's brains learn and grow over time"


• Identify the real-world problem or curiosity that led to this question.


• Draft a simple introductory sentence or two that sets the scene (the "what's the problem?").


• Now, rephrase your core question using the simpler language you brainstormed.


• Add a sentence about "why this matters" or what understanding it could lead to.


• Read it aloud. Does it flow? Would your non-expert friend understand it immediately?

Examples:

Let's take a few complex research questions and break them down:

Example 1: Biology/Medicine

Original Research Question: "What is the role of endogenous retroviral elements in the transcriptional regulation of interferon-stimulated genes during acute viral infection?"

Breakdown & Simplification:

• Jargon:


• "Endogenous retroviral elements": Old, inactive bits of virus DNA that got incorporated into our human DNA millions of years ago. We all have them.


• "Transcriptional regulation": How our body decides which genes to turn "on" or "off" to make proteins.


• "Interferon-stimulated genes": Specific genes that help our immune system fight off viruses.


• "Acute viral infection": When you get sick with a virus right now (like the flu or a cold).


• The "So What?": Understanding how our body fights viruses, potentially leading to new treatments.


• The Problem: When we get a virus, our body has to fight it. We know some genes are involved, but what else plays a role?

"When we catch a virus and get sick, our bodies fight back in amazing ways. We're looking at something really surprising: **how old, inactive pieces of virus DNA that are already inside our own genetic code might actually help our body turn on important defense genes to fight off new viral infections.** We want to understand if these ancient viral leftovers, which usually just sit there, are secretly helping our immune system respond."

(Optional addition for impact): "If we understand this, it could open up new ways to boost our natural defenses against all sorts of viruses."

Example 2: Social Science/Education

Original Research Question: "How do socio-economic status and early childhood educational interventions influence long-term cognitive development trajectories in at-risk urban populations?"

Breakdown & Simplification:

• Jargon:


• "Socio-economic status": How much money someone has, their job, and their education level.


• "Early childhood educational interventions": Things like high-quality preschool, early learning programs, or parent support groups for young children.


• "Long-term cognitive development trajectories": How children's thinking, learning, and problem-solving skills develop over many years.


• "At-risk urban populations": Children living in cities who face challenges like poverty, limited resources, or difficult home environments.


• The "So What?": Informing policies and programs to help children from disadvantaged backgrounds succeed.


• The Problem: We know some kids face more challenges from a young age. Can we help them thrive?

"We know that children growing up in challenging environments, especially in big cities, can face extra hurdles. Our research asks: Do good quality preschools or other early learning programs make a lasting difference in how well children from disadvantaged backgrounds learn, think, and solve problems as they grow up? We're trying to figure out if these early efforts can help close the learning gap and set kids up for success in school and beyond."

Example 3: Environmental Science/Engineering

Original Research Question: "To what extent do novel machine learning algorithms enhance the predictive accuracy of climate models for regional precipitation patterns under varying atmospheric CO2 concentrations?"

Breakdown & Simplification:

• Jargon:


• "Novel machine learning algorithms": New types of artificial intelligence (AI) or computer programs that can learn from data.


• "Enhance the predictive accuracy": Make predictions more precise or correct.


• "Climate models": Complex computer programs that simulate Earth's climate to predict future weather and climate trends.


• "Regional precipitation patterns": Where and when it rains locally (e.g., in a specific state or region), not just globally.


• "Varying atmospheric CO2 concentrations": Different levels of carbon dioxide pollution in the air (due to climate change).


• The "So What?": Better preparedness for droughts, floods, and agricultural planning in a changing climate.


• The Problem: Climate change is making weather harder to predict, especially local rainfall.

"Predicting exactly where and when it will rain, especially with climate change making our weather patterns more unpredictable, is incredibly difficult. Our project is exploring: Can we use powerful new artificial intelligence (AI) programs to make our climate models much better at predicting local rainfall, especially as carbon dioxide pollution in the atmosphere continues to change? Essentially, we're asking if AI can help us forecast floods and droughts more accurately, so communities can better prepare."

Your Turn!

Now, provide me with your research question, and I'll help you apply these principles!