Here are some of the best questions for a College Undergraduate Student survey about dining services, and also tips on how to create them. With Specific, you can build a conversational, AI-powered survey in seconds—no technical skills needed.
The best open-ended questions for dining services surveys
Open-ended questions help uncover honest, nuanced feedback from students. Use them when you’re interested in detailed experiences, specific suggestions, or emotions that don’t fit into simple choices. Open-ended answers can spotlight issues and opportunities that multiple-choice questions often miss.
What do you like most about the current dining options on campus?
Describe any challenges or issues you've had with dining services this semester.
If you could improve one thing about your dining experience, what would it be?
How do you feel about the variety of food options available to you?
Tell us about a memorable positive experience you've had with campus dining.
Tell us about a frustrating or disappointing experience you've had with dining services.
If dining hours changed, how would this affect you and your schedule?
How well do dining services accommodate dietary restrictions or preferences?
What suggestions do you have to make dining facilities more welcoming?
Is there something you wish dining services knew about your needs as a student?
Based on recent data, an overwhelming 86% of students are now using artificial intelligence in their academic lives, which means they’re increasingly open to digital, conversational feedback channels like AI-powered surveys. [1]
The best single-select multiple-choice questions
Single-select multiple-choice questions are perfect when you want to quantify aspects of student experience or identify trends quickly. They work well as an entry point to start conversations—especially when you want respondents to pick from familiar, focused options before you probe deeper. It's often less demanding than asking for full explanations right away.
Question: How satisfied are you with the food quality in campus dining?
Very satisfied
Satisfied
Neutral
Dissatisfied
Very dissatisfied
Question: How often do you eat at campus dining facilities?
Daily
Several times a week
Once a week
Rarely
Never
Question: What is your main reason for choosing to eat (or not) at campus dining?
Convenience
Price
Food quality
Dietary needs/restrictions
Other
When to follow up with “why?” After a multiple-choice question, always consider a “why?” follow-up—especially when a student selects a critical or unexpected answer. For example, if a student chooses “Dissatisfied” with food quality, ask, “Why do you feel dissatisfied with the food quality?” This helps turn quantifiable data into actionable insight.
When and why to add the “Other” choice? Always add “Other” when your list of choices might not capture every student’s experience. This opens the door for unanticipated responses, which can spark valuable follow-up questions and reveal needs you haven’t considered.
Should you include an NPS question?
The Net Promoter Score (NPS) is a powerful, widely used single-question measure of satisfaction and loyalty. In the context of college dining, it quickly gauges how likely students are to recommend campus dining to a friend. It’s a versatile metric for benchmarking improvement across time and institutions.
A typical NPS question:
How likely are you to recommend campus dining services to other students? (Rate 0-10)
Then, based on the score, follow up with a tailored question: “What’s the most important reason for your score?” You can generate an NPS survey for college undergraduates about dining services right away with this link.
The power of follow-up questions
Follow-up questions transform basic surveys into rich, conversational interviews. Instead of collecting one-word or unclear answers, automated follow-ups help you clarify, dig deeper, and get the true context behind each response. They make the whole process more like a real conversation—not a boring form. See how automated follow-up questions work in Specific for more detail.
Student: “I don’t like the desserts.”
AI follow-up: “Can you tell us more—what specific desserts would you like to see or what didn’t you enjoy?”
How many follow-ups to ask? In our experience, limiting follow-ups to 2-3 per original question provides enough depth without tiring respondents. Specific lets you fine-tune this—if someone provides all you need in their first reply, the AI can skip further probing automatically.
This makes it a conversational survey: follow-up questions flow naturally, so the survey feels more like chatting with a helpful interviewer than filling a dull questionnaire.
AI survey response analysis: Even though open-ended feedback can be messy, you can analyze all responses using AI—see how to analyze survey responses with AI for practical tips. The AI will summarize, search, and surface themes quickly regardless of how many open-ended replies you receive.
Automated follow-ups are a new approach, and you’ll see how different it feels when you generate a survey and try it yourself.
How to prompt AI for great survey questions
If you want to have ChatGPT or another GPT model help generate survey questions, here are some effective prompts you can use:
Start simple and ask:
Suggest 10 open-ended questions for College Undergraduate Student survey about Dining Services.
For even better results, add specific context about your goals, audience, or situation. For example:
We are a university aiming to improve student satisfaction with on-campus dining. Our student body is diverse in tastes and dietary needs. Suggest 10 open-ended survey questions to gather detailed, actionable insights from undergraduates about dining services this semester.
Next, organize and refine. Ask:
Look at the questions and categorize them. Output categories with the questions under them.
Finally, focus your inquiry by selecting key areas to explore deeper. For example, if your categories are “Food Quality,” “Service Speed,” and “Dietary Options,” you could prompt:
Generate 10 questions for categories Food Quality and Dietary Options.
What is a conversational survey?
Conversational surveys feel like interactive, real-time chats, not static forms. You and your respondents experience a dynamic back-and-forth, with the AI guiding, probing, and learning much like a thoughtful interviewer or researcher. Every reply can prompt a deeper or clarifying follow-up on the spot.
This stands in stark contrast to traditional survey creation, where you labor to craft every possible question and follow-up, then send it out into the world and hope for the best. In fact, 70% of higher education institutions now integrate AI tools, and conversational AI surveys reflect the newest, most engaging way to collect feedback in education settings. [4]
Manual Survey Creation | AI-Generated Conversational Survey |
|---|---|
Write every question by hand, structure logic, set branching | Describe your goal and audience, AI builds survey instantly |
No dynamic follow-ups—risk getting unclear answers | Real-time, smart follow-up probes clarify and dig deeper |
Time-consuming to analyze open feedback | AI analyzes and summarizes responses automatically |
Feels impersonal to respondents | Feels like a real, engaging conversation |
Why use AI for college undergraduate student surveys? AI survey generators like Specific handle all the complexity for you—design, conversation, follow-up, and analysis. You save huge amounts of time, get richer data, and engage students on their terms. In fact, 88% of undergraduates in the UK used generative AI in assessments—making an AI survey example instantly relatable and accessible for them. [2]
With Specific’s AI survey generator, you can create, launch, and iterate on conversational surveys effortlessly. If you want a full step-by-step, read our guide on how to create a survey for college students about dining services.
See this dining services survey example now
Test out a truly conversational survey experience—get actionable insights in minutes and let AI do the heavy lifting from question design to smart follow-ups and instant response analysis.