This article will give you tips on how to analyze responses from a teacher survey about class size, making it easier to surface actionable insights without getting buried in data.
Choosing the right tools for analysis
The way you analyze your teacher survey responses will depend on the kind of data you’ve collected:
Quantitative data: If you’re looking at numbers—how many teachers picked each class size, for example—tools like Excel or Google Sheets work well. These are great for tallying up responses and making quick charts.
Qualitative data: Open-ended answers or follow-up comments are trickier. Reading every response just isn’t practical if you have dozens or hundreds of teachers. Here, AI tools step in to save the day, processing text to find recurring themes you’d otherwise miss.
There are two approaches for tooling when dealing with qualitative responses:
ChatGPT or similar GPT tool for AI analysis
You can export your survey data—say, all those teacher comments about class size—and copy-paste it into ChatGPT or another GPT-powered tool. Then, you “chat” with the AI, making it analyze, summarize, and answer questions about those responses.
Convenience is the tradeoff here. It works, but it’s rarely smooth: handling large data sets can get messy, and if you miss a chunk in copy-paste, you risk losing context—especially when sorting through hundreds of teacher voices.
All-in-one tool like Specific
Purpose-built tools like Specific are designed for this whole workflow. The platform both collects conversational survey data and uses AI to analyze every teacher response.
Better data, by design: When collecting survey data, Specific’s AI asks contextual follow-up questions. This means richer responses and fewer gaps.
Instant AI analysis: No spreadsheets or manual sifting. Specific summarizes key findings and main themes automatically, turning qualitative data into real, digestible insights—perfect if you want to quickly know how teachers feel about class size.
Conversational AI chat with results: You can chat with the AI about your teacher survey, just like you would in ChatGPT, but with extra features tailored for feedback and survey teams. You always know exactly which data is in the AI context, what question you’re asking about, and you keep everything organized for future reference.
Useful prompts that you can use for analyzing teacher survey responses about class size
If you want to go deep into your data (either in ChatGPT, or in a tool like Specific), having the right prompts is half the battle. Here are my favorites, tailored for teacher survey analysis on class size:
Prompt for core ideas—When you have a large set of qualitative data and want the AI to identify the principal concerns or suggestions, use this generic yet powerful prompt. This is the same technique Specific uses for reporting themes:
Your task is to extract core ideas in bold (4-5 words per core idea) + up to 2 sentence long explainer.
Output requirements:
- Avoid unnecessary details
- Specify how many people mentioned specific core idea (use numbers, not words), most mentioned on top
- no suggestions
- no indications
Example output:
1. **Core idea text:** explainer text
2. **Core idea text:** explainer text
3. **Core idea text:** explainer text
Add more context for better output: AI works better if you give it specifics about your survey—explain your school type, teacher population, or your analysis goals. Try telling the AI:
Analyze these responses from teachers at public middle schools in [your region] about classroom size. We want to know what core challenges teachers face, and how class size is impacting student learning and teacher workload.
Prompt for follow-up: If the AI found a theme (say, “Lack of individual attention”), ask: “Tell me more about ‘lack of individual attention.’” That extra prompt gets more quotes, examples, or sub-themes.
Prompt for specific topic:
Did anyone talk about student discipline? Include quotes.
This works for any keyword or concern—you can swap “student discipline” for “teacher burnout” or whatever you want to check.
Prompt for pain points and challenges:
Analyze the survey responses and list the most common pain points, frustrations, or challenges mentioned. Summarize each, and note any patterns or frequency of occurrence.
Prompt for suggestions and ideas:
Identify and list all suggestions, ideas, or requests provided by survey participants. Organize them by topic or frequency, and include direct quotes where relevant.
Prompt for personas:
Based on the survey responses, identify and describe a list of distinct teacher personas regarding class size. For each persona, summarize their key characteristics, motivations, goals, and any relevant quotes or patterns observed in the responses.
And if you’re starting from scratch and want to know what to ask in your next teacher survey, check out our guide on best questions for teacher survey about class size.
How Specific analyzes qualitative data from different question types
Specific’s AI breaks down responses based on the structure of each question, so you get more meaningful summaries without manual grunt work:
Open-ended questions (with or without follow-ups): The AI provides a concise summary for all responses, including any follow-up answers tied to the initial question.
Multiple choice with follow-ups: Every choice gets its own separate summary of all the follow-up responses—letting you see, for example, how teachers who prefer small classes differ from those who prefer larger ones.
NPS: Responses from detractors, passives, and promoters are each summarized in separate buckets. This makes it easy to spot what motivates your biggest fans or what’s bothering your dissatisfied teachers.
You can recreate this type of analysis in ChatGPT, but you’ll spend a lot more of your time organizing data, copy-pasting, and tracking which responses came from which question type—something that Specific automates completely.
How to tackle AI context limit challenges
Large teacher surveys often bump up against the “context size limit” of AI models—meaning the AI can’t process every response if you have too much data in one go.
Two practical ways to beat this (both offered by Specific):
Filtering: Only include conversations where teachers replied to key questions or gave long-form answers. This way, you narrow the dataset before sending it to the AI.
Cropping: Select just the questions you care about most—if student learning impact matters, you can send only those responses to the AI and keep analysis focused (and inside the context limit).
Combined, these options mean you don’t have to sacrifice data depth for data size—especially important when working with broad teaching staff or multi-school surveys.
Collaborative features for analyzing teacher survey responses
Working on survey results with colleagues can feel chaotic, especially when multiple people are analyzing responses or asking similar questions about class size trends.
Built-in team collaboration: In Specific, you don’t just chat with the AI on your own—multiple stakeholders (admins, research peers, or teachers themselves) can join in, each creating their own chats filtered by topic, demographic, or NPS score.
Clear ownership and transparency: Every AI chat shows exactly who started the conversation, making it easy for teams to review the logic or follow up on insights—no duplicate work.
Contextual avatars: When collaborating inside AI Chat, each message displays the sender’s avatar, so you always know whose ideas you’re building on. This makes team-based analysis smoother, quicker, and less error-prone—a lifesaver for distributed staff or remote research teams.
If you’re looking to get started on your first collaborative survey, you can jump straight to our AI-powered teacher survey generator for class size. Or, create any custom survey with the AI survey builder.
Create your teacher survey about class size now
Start collecting real classroom insights with a survey tailored for teachers—instantly analyze responses using AI, ask better follow-ups, and collaborate seamlessly. Get your questions answered and make your next decisions with confidence.