Month: February 2026

Moving from calculating concrete volumes to interpreting abstract interview data is one of the hardest shifts for a Quantity Surveyor. You are trained to find the “right answer” or the “market rate,” so it is natural to treat qualitative data like a survey to be tallied or a problem to be solved.

However, in qualitative research, this leads to the “Judgment Trap”, a situation where you label participants as “wrong,” “lazy,” or “correct” instead of analyzing the underlying issues.

Based on the Mirror Principle (see our previous post on The Qualitative Mirror), here is a practical guide to writing your findings chapter with academic neutrality.

1. The Three Mental Shifts

Before you write a single sentence, you must change how you view your data. You are no longer a Judge; you are an Analyst.

Shift 1: From “Verification” to “Contextualization”

The Problem: You hear an expert give an opinion, and you treat it as the “correct solution.”

The Fix: An expert’s opinion is not a fact; it is data. It represents one view of the mirror.

• Bad (Prescriptive): “The experts correctly stated that low-bid tendering is the root cause of project failure.” (You are agreeing with the expert).
• Good (Analytical): “Senior professionals consistently framed low-bid tendering as the primary driver of failure, emphasizing the conflict between financial constraints and quality assurance.” (You are describing the expert’s view).

📺 Watch this (6 mins): The Power of Understanding Multiple Realities

Why it helps: A simple explanation of why we don’t look for one “single truth” in qualitative research.

Shift 2: From “Frequency” to “Weight”

The Problem: You treat the interview like a survey. “7 out of 10 participants said…”

The Fix: We are not counting votes; we are weighing the intensity and consistency of the theme.

• Bad (Counting): “Most participants said the software is difficult.”
• Good (Weighing): “There was a dominant consensus regarding the software’s steep learning curve, particularly among junior surveyors who lacked prior training.”

📺 Watch this (4 mins): Frequency ≠ Importance in Qualitative Data

Why it helps: A clear explanation of why “counting how many people said it” often misses the real insight.

Shift 3: From “Judgment” to “Systemic Drivers”

The Problem: You assess performance. “The contractors failed to understand the contract.”

The Fix: Replace judgment adjectives (lazy, wrong, failed, good) with systemic verbs (prioritized, constrained, overlooked, emphasized).

• Bad (Judging): “Contractors were ignorant of the ISO standard.”
• Good (Systemic): “Contractors demonstrated a lack of familiarity with the ISO standard, which they attributed to the rapid turnaround times required during the tender stage.”

📺 Level Up Your Research (6 mins): Reflexivity vs. Bracketing Explained

Why it helps: This elevates you to the next level. It uses a “Suitcase” metaphor to show how to set your own judgments aside so you can see the data clearly.

2. The “Before & After” Lab

Let’s look at how a “Judge” writes versus how a “Researcher” writes, using common QS research topics.

Example A: The “Blame Game” (Payment Delays)

The Data: Contractors complained that consultants take too long to certify interim payments.

The “Judge” (Bad) ❌	The “Researcher” (Good) ✅
What they write: “Consultants are often lazy and fail to certify payments on time. This wrongful behavior destroys the contractor’s cash flow.”	What they write: “Contractors identified the certification period as a critical bottleneck. Delays were frequently attributed to a misalignment between the contractor’s submission format and the consultant’s verification requirements.”
The Error: You are taking sides! You are judging the consultant as “lazy.”	The Fix: You replaced judgment with a systemic explanation (“misalignment”). You reported the friction, not the fault.

Example B: The “Expert Trap” (BIM Adoption)

The Data: A Senior PM says, “Small firms shouldn’t use BIM; it’s too expensive for them.”

The “Hermit” (Bad) ❌	The “Researcher” (Good) ✅
What they write: “BIM is too expensive for small firms. Therefore, small firms should not attempt to implement it.”	What they write: “Senior Project Managers perceived the initial capital cost of BIM as a prohibitive barrier for small firms, suggesting that traditional CAD workflows may remain more viable in that specific context.”
The Error: You treated an opinion as a fact. You turned the participant’s view into a universal rule.	The Fix: You contextualized the finding. It is not that BIM is too expensive; it is that it is perceived as a barrier by this group.

Example C: The “Counting Trap” (Sustainable Materials)

The Data: 8 out of 10 participants mentioned “Cost” as the main barrier.

The “Counter” (Bad) ❌	The “Researcher” (Good) ✅
What they write: “80% of participants said cost is the problem. Only 2 people mentioned availability.”	What they write: “There was a dominant consensus that financial constraints supersede environmental considerations during material selection. Issues of availability appeared as a secondary, less critical concern.”
The Error: Qualitative research is not a vote. Numbers mean nothing without context.	The Fix: You weighed the findings (“dominant consensus” vs “secondary concern”). You explained the relationship between the themes.

3. The “Translation Protocol” (How to Write)

How do you actually draft these sentences? Use this 2-step process to blend participant reality with academic theory.

Step 1: The “Plain English” Draft

Write what you found using the simple terms the participants used.

• Draft: “Participants felt that ‘changing their mind’ regarding specs caused delays.”

Step 2: The “Academic Overlay”

Go back to your Literature Review. What is the academic term for “changing their mind”?

• Answer: Scope Creep or Design Variation.
• Refined Sentence: “Participants identified scope creep as a primary driver of delays, noting that clients frequently ‘changed their mind’ regarding specifications.”

⚠️ The Golden Rule:

• Never change the direct quote. If the participant said “changing their mind,” the quote must stay “changing their mind.”
• You only use the academic term (Scope Creep) in your interpretation before or after the quote.

Final Check

Before you submit your Analysis and Findings chapter, highlight every finding and ask yourself:

1. Am I counting? Did I use words like “many,” “most,” or “70%”?
   • Correction: Change to “consensus,” “dominant view,” or “divergent perspective.”
2. Am I judging? Did I use words like “good,” “bad,” “failed,” or “correct”?
   • Correction: Change to “effective,” “challenging,” “constrained,” or “aligned.”
3. Am I the Hermit? Did I present an opinion as a fact?
   • Correction: Add “Participants perceived…” or “Data suggests…”

Remember that your goal is not to decide who is right. Your goal is to explain why they see what they see.

In my years of supervising final-year dissertations, I have noticed a recurring pattern. Students, especially those from technical backgrounds like Quantity Surveying, approach qualitative research like a construction contract: they look for the “right” answer. They interview experts, record the answers, and present them as facts.

But qualitative research is not about finding one single truth. It is about understanding multiple realities.

To explain this, I often share a story based on a classic Sinhala folk song, Kedapatha (the mirror).

Before reading the story, I encourage you to listen to the song to feel the emotion behind the narrative. The lyrics are in Sinhala language. Even if you are unable to understand it, the melody captures the essence of human perception.

🎵 Listen here: Watch the Video on YouTube

Below is a close translation and adaptation of the story found in the lyrics.

The Story of the Mirror (In a Parallel World)

Imagine this story takes place in a parallel world, in a village where the physical phenomenon of a “reflection” is scientifically unknown. No one, not even the learned scholars, understands how a mirror works.

One day, a farmer found a mirror (probably have left behind by a traveller across parallel worlds). When he picked it up and looked into it, he was stunned. He saw the face of his late father. Overcome with emotion and filial piety, he decided to honour his father. He took the mirror home, hid it inside a trunk box, and secretly paid homage to it every day.

Noticing her husband’s strange behaviour, such as whispering into the trunk box and spending time alone with it, his wife grew suspicious. One day, when the farmer was away, she opened the trunk and found the mirror.

She looked into it and gasped. She didn’t see a father. She saw a woman.

Furious, she waited for her husband to return. “You have brought another woman into this house!” she screamed, holding the mirror up. “She is even hiding in this box!”

The farmer was baffled. “That is not a woman! That is my noble father!” he insisted.

They argued endlessly, with one seeing a woman and the other seeing a father, until they decided to visit the village Hermit. The Hermit was the wisest man in the land, a monk who had renounced worldly attachments. They believed he would settle the dispute.

The Hermit took the mirror. He looked into it deeply.

He shook his head and smiled compassionately at the couple. “You are both wrong,” he said. “It is neither your father nor another woman.”

He looked closer. “It is a Noble Person. A wise elder. He deserves to be in a place of wisdom.”

And so, the Hermit said, “You both lose. Let him be with me here,” and he took the mirror for himself.

The Lesson: The Researcher as a Villager

Now, imagine you are a researcher born in this same village.

You, too, have never seen a mirror. You cannot simply say, “It’s just a reflection,” because that concept doesn’t exist in your world’s knowledge base yet.

You have done your Literature Review; you scoured the village archives for strange things inside objects, but you found no explanation for this specific phenomenon. You are entering the field with the same lack of fundamental answers as the community.

If you observe this event, what do you write? Who is in the mirror?

• The Novice Researcher writes: “There is a Noble Person in the mirror.” (The critical error is claiming presence inside the object based on an expert’s word).
• The Biased Researcher writes: “There is a Rival Woman in the mirror.” (Sympathizing with the wife’s emotional distress).

The True Researcher realizes that the data does not support claiming anyone is in the mirror. You can only report what happened.

Based on your observation, you can interpret the findings at two levels:

1. High Confidence (The Fact): “Everyone who looked into the object saw someone, and that someone was unique to the person who looked.” (This is the only undeniable truth as there is no data to deny it).
2. Lower Confidence (The Theory): “There appears to be a resemblance between the observer and the figure they see.”

From here, you build your theory:

1. The Farmer (Male, grieving) -> Sees Father.
2. The Wife (Female, insecure) -> Sees Woman.
3. The Hermit (Wise, elder) -> Sees Elder.

You don’t find the “truth” of the object. You find the theory of projection: People seem to see what matters most to them.

In this story, the mirror is your research problem.

• The Farmer looked at the mirror and projected his Past (his father).
• The Wife looked at the mirror and projected her Insecurity (a rival).
• The Hermit, even with all his wisdom, looked at the mirror and projected his Ego (a noble person).

The “Mirror Principle” in Research

When you conduct interviews for your dissertation, you are that researcher in the parallel village. You don’t know the absolute truth about “BIM Adoption” or “Contractor Delays” because that truth doesn’t exist yet; it is constructed by the people living it.

If you interview a Contractor about “Payment Delays,” they might see “Unfair Consultants.” If you interview a Consultant about the same topic, they might see “Incompetent Contractors.”

If you simply report what they say as “The Truth,” you are making the same mistake as the Hermit. You are assuming the reflection is the reality.

Your job is to push yourself to the knowledge level of the community (understand what they see), but then stand back and analyze why they see it.

• Instead of concluding: “Consultants are unfair.”
• You conclude: “Contractors consistently perceived the payment process as unfair, reflecting their exposure to high cash-flow risks.”

A Classroom Lesson: The Language of the Lyrics

I often play this song in my lecture hall, and it highlights a second critical lesson.

When the music starts, my Sinhala-speaking students nod along, understanding the tragic irony immediately. However, a large majority of my Tamil-speaking students sit quietly, confused. They hear the melody, but the meaning is locked away from them until I translate it for them.

This mirrors the challenge of Research Competence.

If you enter a construction site to interview professionals, but you have not mastered the “language” of the industry, or if you don’t understand the specific jargon of contracts, procurement, or technology, you are like those students listening to a foreign song. You will hear the “noise” (the data), but you will miss the meaning.

You cannot interpret what you do not understand. This is why you must master your subject matter through a rigorous Literature Review before you ever speak to a participant.

Final Thought

Before you write your Analysis and Findings chapter, ask yourself two questions:

1. Do I speak the language? Have I done enough background reading to understand what the participants are really saying?
2. Am I describing the mirror? Or am I just repeating the reflection?

If you find yourself judging your participants or believing your experts blindly, remember the Hermit. Even the wisest among us can fall in love with our own reflection.