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From Overwhelmed to Aligned: A Guide to Navigating Research Blocks
From Overwhelmed to Aligned: A Guide to Navigating Research Blocks
INTRODUCTION
INTRODUCTION
Research Blocks Aren’t About Intelligence—They’re About Process
Research Blocks Aren’t About Intelligence—They’re About Process
Research isn’t only about collecting data. It’s about cultivating ideas, nurturing questions, and weaving patterns into something coherent, meaningful, and alive.
If you’ve ever felt stuck, lost, or overwhelmed in the research process, that doesn’t mean you’re doing it wrong. Research moves in cycles. Like a garden, it flourishes at times, rests at others, and always asks for care and attention.
Most academic training skips over how to work through these quieter, less certain phases.
This guide is here to help. It offers practical strategies to untangle common research blocks, from clarifying your question to making sense of messy data, so you can move forward with more confidence and clarity.
Step 1: Clarifying Your Research Question (Without Spiraling)
Step 1: Clarifying Your Research Question (Without Spiraling)
Your research question is the backbone of your work - but it’s also one of the hardest things to pin down. If you keep revising (or second-guessing) your question, ask yourself:
Is my question actually too broad? (If you can’t answer it in a dissertation, it’s too big.)
Am I looking for the ‘perfect’ question instead of a useful one?
Have I let my data shape my question, or am I forcing my question onto my data?
👉 Try this: Instead of crafting a ‘perfect’ research question, create a mind map of all the words and concepts that are floating around for you in regards to your research. From these words, draft 3-5 versions of a research question that play around with the relationships among these concepts. See which one you gravitate the most toward.
Step 2: Developing Qualitative Data Collection Tools That Actually Work
Step 2: Developing Qualitative Data Collection Tools That Actually Work
Creating surveys, interview guides, or observation protocols can feel overwhelming. Instead of overcomplicating it, focus on:
Clarity: Will your questions actually give you the information you need?
Alignment: Does your tool connect to your research question?
Flexibility: Can it adapt if participants interpret things differently?
👉 Try this: Test your instrument on one person (a friend, colleague, or even yourself). Where do they get confused? Where do they give answers that aren’t useful? Is there a question you aren't asking but want to? Revise accordingly.
Step 3: Collecting Data Without Feeling Scattered
Step 3: Collecting Data Without Feeling Scattered
The hardest part of collecting data isn’t just logistics – it’s starting. If you’re feeling too scattered to start:
Set a soft deadline for your first data point. (No more waiting for ‘the right time.’ Pick a time (two weeks, one month, summer, etc) to get data down, even if it isn’t the data you expected or initially planned.)
Don’t aim for perfection. Rather, aim for something usable.
Document your process: What’s working? What’s surprising? What needs adjusting?
👉 Try this: Map out the process you envision for data collection. Make it fun! Does it look like the board for Candyland? Or more like the Upside Down? Which areas of the map are you most excited to visit? Which areas are you worried about approaching? Journal the feelings that are coming up and how you can use positive feelings to work through the negative feelings? (Are all the feelings negative...? Contact me to help you work through it!)
Step 4: Making Sense of Messy Data (Without Drowning in It)
Step 4: Making Sense of Messy Data (Without Drowning in It)
Once data starts coming in, panic often sets in. Where do you even begin? What even is “data analysis”? Is it better to use a computer program or your human brain? Rather than stress about these questions, start by answering:
Big-picture patterns: What themes or surprises stand out?
Low-stakes analysis: Jot down observations before you officially start coding.
Trusting the process: Your first thoughts might be wrong. That’s normal.
👉 Try this: Change locations - go to a coffee shop, a park, a public library. Write or audio record 3-5 “gut reactions” to your data before diving into formal analysis. These initial impressions often reveal key insights. Bonus: Do this after every data collection session.
Applying this to research: A story
During my doctoral data collection, I worked in three different high schools across the city. In each neighborhood, I found a nearby coffee shop where I would go immediately after spending time with teachers and students in the classroom. Instead of organizing formal data, I would sit and write—capturing my thoughts, feelings, and impressions as they came to me. Sometimes, this process lasted an hour or two; other times, it was just 15 minutes.
At the time, I didn’t think of this writing as data collection. But when I later organized my formal data—interviews, surveys, focus groups, video recordings, observations, and pedagogical materials like assignments—I realized how invaluable those informal writings were. They ensured that my own thoughts and voice as a researcher remained just as present as those of my participants. This was especially important in a formal school setting, where institutional discourse was so dominant that it could easily overshadow other perspectives. Having a space to separate my own reflections from the dominant narrative helped me better understand students’ experiences and the ways teachers both supported and limited opportunities for meaningful learning in the classroom.
To this day, when I drive past one of those coffee shops, I feel immense gratitude for the insight that space gave me.
Step 5: Pulling Everything Together (Without Breaking Down)
Step 5: Pulling Everything Together (Without Breaking Down)
If you feel like your research is a pile of scattered pieces, that’s normal. But instead of forcing a structure too soon, try:
Mapping connections between your research question, literature, and data.
Writing messy summaries of each theme before polishing them.
Asking: What is my data actually saying? (Not: What do I want it to say?)
👉 Try this: Talk it out. Go for a walk with a close friend and tell the story of your research. What did you want to find? What did you find? What surprised you or confused you? No judgements, no grand arguments - just let your voice say what your mind is developing while you move your body. Don't have a friend you think would understand? Audio record your thoughts (even pretend you're on a podcast) while you're walking.
FINAL THOUGHTS
FINAL THOUGHTS
Research Is Messy, And That’s Okay!
Research Is Messy, And That’s Okay!
If you’re feeling stuck, it’s not because you’re bad at research. It’s because research is an unfolding process, and you’re in the middle of it. You don’t have to untangle it alone.
If you want personalized support, let’s talk! If you want to do these activities together, book an initial meet and greet session.
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