Here are some of the best questions for a college undergraduate student survey about instructor effectiveness, plus practical tips on crafting them. You can build a conversational survey like this in seconds with Specific’s AI survey generator.
Best open-ended questions for student surveys about instructor effectiveness
Open-ended questions invite students to share detailed feedback in their own words. They’re perfect when we want deeper insights into what makes an instructor effective or where there’s room for improvement. These questions help us spot patterns that rigid formats might miss and are essential when context matters—especially in higher education, where instructor impact is multi-faceted.
Here are ten of the best open-ended questions we recommend for a college undergraduate student survey on instructor effectiveness:
What are the instructor’s biggest strengths when it comes to teaching this course?
Can you describe a time the instructor helped clarify a difficult topic?
How does the instructor make the material engaging or relevant to you?
What feedback would you give the instructor to improve your learning experience?
In what ways does the instructor encourage class participation?
How accessible has the instructor been for questions or extra help?
Tell us about a moment when the instructor’s teaching style worked especially well—or didn’t work at all.
How well does the instructor adapt assignments or lessons to student needs?
What teaching methods used by this instructor have been most or least effective for you?
If you could change just one thing about the instructor’s approach, what would it be and why?
The value of open-ended questions is clear—students can highlight specifics. For example, research shows that students who succeed in remote learning often credit effective instructors for providing structure, clear communication, and accessibility [2]. These questions will surface actionable examples and suggestions.
Best single-select multiple-choice questions for student surveys
Single-select multiple-choice questions are best when we need quantifiable, structured feedback—especially at scale. They offer a quick snapshot of general sentiment or experiences, and can kick off further conversation. Sometimes, it’s easier for students to pick a choice, and then explain more if needed. These questions are also critical for identifying broad trends across instructors or departments.
Question: How would you rate the clarity of the instructor’s explanations?
Excellent
Good
Fair
Poor
Question: How approachable is the instructor when you need help?
Very approachable
Somewhat approachable
Not very approachable
Not at all approachable
Question: Which teaching methods did the instructor use most often in this course?
Lecture-based
Active learning (discussions, group work, problem solving)
Project-based
Other
When to follow up with "why?" The best time to ask "why?" is right after a respondent selects a rating or option, especially when we want richer context or to understand their motivation. For example, if a student marks "Poor" for clarity, a follow-up like “Why did you choose ‘Poor’?” lets them elaborate and gives us the actionable feedback we really need.
When and why to add the "Other" choice? Adding the "Other" choice ensures students can share experiences outside of the predefined options. If several select "Other," a follow-up question can uncover unique teaching strategies or issues you hadn’t considered, unlocking deeper insights.
Should you use an NPS-style question in student surveys?
The Net Promoter Score, or NPS, originally used in customer satisfaction, is becoming increasingly valuable in academic settings. We use it to gauge loyalty and overall satisfaction by asking students how likely they are to recommend an instructor (or a course) to peers. This single, simple question translates to actionable data and benchmarks across courses or semesters.
The NPS question is particularly relevant for instructor effectiveness because it compresses complex sentiment into a number we can track over time, then explore with follow-ups. Since effective instructors increase both current and future student performance—an extra one standard deviation boost in instructor quality leads to higher grades not just now but in following courses [1]—NPS helps us spot these standout educators quickly.
If you’re curious, you can instantly generate a student NPS survey with preset follow-up logic via Specific’s NPS survey builder.
The power of follow-up questions
Follow-up questions—especially when powered by AI—are a game-changer. They enable surveys to keep the conversation going, clarify vague responses, or probe for deeper insights—all automatically, in real time. You can dig into how automated follow-ups work and why they take your surveys further.
Specific’s AI survey builder uses advanced GPT-powered intelligence to automatically ask tailored follow-ups based on each student’s answer. This means every feedback moment becomes a mini-interview where the AI can clarify, ask "why," or explore related factors—just as an expert researcher would, but at scale. It reduces back-and-forth via email and gathers richer context for you to act on.
Student: "The instructor is helpful."
AI follow-up: "Can you describe a specific instance when the instructor helped you during the course?"
Without the follow-up, we’d just have generic comments, missing out on context that turns feedback into actionable insights. This ability to clarify, right in the flow, is what separates merely “good” survey tools from the best ones.
How many follow-ups to ask? In our experience, two to three follow-ups per question strike the right balance. Enough to get good depth, but not so many that students get fatigued. With tools like Specific, you can set a max and let the AI stop after collecting the context you need—or skip to the next question when your criteria are met.
This makes it a conversational survey: Instead of a dull form, you get a real back-and-forth exchange. Students feel heard, resulting in higher engagement and more thoughtful answers—a signature of conversational surveys.
AI analysis, fast: Analyzing tons of open-ended and follow-up responses isn’t a problem anymore. With AI-powered response analysis, you can summarize, extract key themes, and chat with the data—no more sifting manually through comments after the fact.
Try it yourself—generate a survey with automated AI follow-ups and see how different the depth and quality of responses become.
How to prompt ChatGPT to generate quality survey questions
If you want to tap into generative AI for survey design, start simple but get specific as you iterate. Here’s a no-nonsense approach that works especially well for student and instructor-focused surveys:
First prompt:
Suggest 10 open-ended questions for College Undergraduate Student survey about Instructor Effectiveness.
But AI always does better with context. Try this expanded version:
I’m a curriculum coordinator designing a feedback survey for undergraduate students. The goal is to understand how effective their instructors are in explaining material, supporting students, and fostering class engagement. Suggest 10 personalized, open-ended survey questions.
To organize the results, prompt:
Look at the questions and categorize them. Output categories with the questions under them.
Drill down further as you see valuable categories:
Generate 10 questions for “engagement and participation” and “clarity of instruction.”
This method is perfect for refining your survey before using an AI survey generator like Specific, or to fuel brainstorming sessions for your team.
What is a conversational survey?
A conversational survey feels more like a chat than a questionnaire. Instead of static forms, students engage in a back-and-forth, guided by dynamic AI that tailors the conversation in real time. This conversational approach boosts response quality and engagement—students are more likely to open up when it feels natural, not transactional.
Here’s how conversational AI survey creation compares to the manual way:
Manual Survey Creation | AI Survey Generator (Conversational) |
|---|---|
Requires you to draft each question; tedious editing | Just describe your goal; AI drafts questions instantly |
Static, with little real-time adaptation | Dynamically adapts questions and follow-ups as students respond |
Tougher to analyze open-ended feedback | Automated AI analysis and summary of responses |
Low engagement; survey fatigue is common | Feels like a chat, leading to higher response rates |
Why use AI for college undergraduate student surveys? Because AI survey tools like Specific instantly generate tailored, research-backed questions—so you can focus on insights over grunt work. Paired with automated follow-ups and deep analytics, you get the gold standard for understanding student sentiment on instructor effectiveness. Try our step-by-step guide to creating student surveys for a hands-on walkthrough.
Every survey you launch through Specific offers a best-in-class, conversational interface—making the feedback process smooth and even enjoyable for students, faculty, and researchers alike.
See this instructor effectiveness survey example now
Create a survey experience that uncovers actionable feedback and empowers continuous improvement. See for yourself how conversational AI surveys make data collection and analysis easier and more insightful than ever.