Here are some of the best questions for an online course student survey about technical support, plus tips on designing smart, effective surveys. If you want to build a survey like this in seconds, Specific’s AI-driven tools can help you generate one instantly.
The best open-ended questions for technical support feedback
Open-ended questions are gold when you want detailed, honest feedback. They let online course students explain issues in their own words, revealing pain points or suggestions you might never have anticipated. This leads to better understanding and continuous improvement. Given that 90% of learners on AI-powered platforms report higher satisfaction, digging deep with the right questions is essential for meaningful technical support. [1]
Can you describe a recent technical issue you experienced while using the online course platform?
How did you go about seeking help for your technical problem?
What did you find most helpful about the technical support you received?
Where do you think our technical support process could improve?
Were there any obstacles that made it hard for you to get technical help?
How did the technical issue affect your ability to complete course activities?
If you could change one thing about our technical support, what would it be and why?
Do you have any suggestions for new support resources or tools that would make your experience better?
What expectations did you have about our technical support before using it, and were they met?
Is there anything else you’d like to share about your experience with our technical support team?
Use these questions to get at the “why” and “how,” not just the “what.” You’ll spot patterns across many student experiences, making your technical support much more effective.
The best single-select multiple-choice questions for clear insights
Single-select multiple-choice questions are essential when you want quantitative data, spot trends quickly, or gently introduce a topic. Sometimes, it’s easier for a respondent to choose from a few clear options than to craft a detailed answer from scratch. This can help spark a conversation—then you follow up with deeper, open-ended questions to collect richer feedback.
Question: How satisfied were you with the technical support you received for your online course?
Very satisfied
Somewhat satisfied
Neutral
Somewhat dissatisfied
Very dissatisfied
Question: Which support channel did you use most frequently?
Live chat
Phone
Online help center / FAQs
Other
Question: How quickly was your technical issue resolved?
Within a few minutes
Within a few hours
Within a day
More than a day
Issue was not resolved
When to follow up with “why?” After any quantitative or structured response—especially when someone is less than “very satisfied”—ask “why?” This clarifies root causes and unlocks context you can act on. For example: If a student selects “Somewhat dissatisfied,” you can follow up with, “Why did you choose this rating?” That extra context can turn vague complaints into opportunities for real improvement.
When and why to add the “Other” choice? Always add “Other” for questions about communication channels, issue types, or anything where your set of answers may not cover every scenario. Follow up by asking them to describe “Other”—these responses often surface new, valuable insights you hadn’t considered.
NPS questions for technical support feedback
The Net Promoter Score (NPS) is a classic for a reason: it measures loyalty and satisfaction in a single, powerful metric. For technical support in online courses, it’s especially useful. Why? Tech support is a key driver of the overall course experience—an unresolved problem can impact not just course completion, but whether a student recommends your platform at all. With NPS, you can track if your support is delighting or frustrating students, then automatically dig into promoters’ and detractors’ reasons with smart follow-ups. Ready to set this up? Create an NPS technical support survey in seconds.
The power of follow-up questions
Follow-up questions are where the magic—and the depth—happens. Instead of leaving feedback shallow or ambiguous, smart follow-ups clarify and probe for specifics. Automated follow-up questions from AI unlock details that static forms can’t, and this can be a game changer for your feedback loops.
Specific’s AI will prompt for follow-ups based on the respondent’s replies and context in real time. With e-learning platforms now leveraging AI so that AI chatbots can handle up to 90% of student queries—often without human intervention—having AI-driven follow-ups means your surveys are as smart and efficient as possible. [3] No more chasing students via email or piecing together incomplete answers. Conversation feels natural, and you get the whole story, fast.
Online course student: “The help desk was slow.”
AI follow-up: “Can you describe how long you waited before someone responded, and how it impacted your learning?”
How many follow-ups to ask? We find that two or three well-placed follow-ups are enough to get full, actionable context—especially when you allow users to skip to the next question once you’ve captured what you need. With Specific, you can customize this easily in your survey settings.
This makes it a conversational survey: These follow-up prompts turn your survey into a real conversation, so it feels like chatting with a knowledgeable human, not just filling out a form.
AI survey analysis made easy: All this rich, open-ended feedback can be overwhelming to analyze manually, but AI-powered analysis summarizes themes, flags issues, and lets you get insights at scale. You can even chat with the AI about your results.
Automated, dynamic follow-ups are a new standard. If you haven’t experienced it, try generating an AI survey—it’s a faster, smarter way to get the detail you need.
How to prompt GPT to create survey questions
Let’s say you want to use ChatGPT or any advanced AI model to create your next online course student survey about technical support. Here’s how to get more useful output with well-structured prompts:
Start simple with:
Suggest 10 open-ended questions for Online Course Student survey about Technical Support.
But you’ll get even better results if you provide more context. For example:
Our platform serves adult learners in tech courses. We offer live chat and email support, but some users report slow issue resolution. Our goal is to improve satisfaction and reduce complaints. Suggest 10 open-ended questions for a student survey about technical support.
Next, organize your ideas:
Look at the questions and categorize them. Output categories with the questions under them.
Once you have categories (e.g., “response time,” “quality of support,” “channel effectiveness”), write:
Generate 10 questions for categories ‘response time’ and ‘quality of support’.
This stepwise prompting helps the AI drill down on the areas you care about most.
What is a conversational survey?
A conversational survey mimics a real chat—dynamic, interactive, and tailored to the respondent’s previous answers. Instead of a set form, the AI asks questions, listens to responses, and follows up as a skilled interviewer would. This leads to richer feedback, higher engagement, and more accurate data.
Traditional manual surveys are slow to build, require lots of editing, and suffer from low response rates and shallow answers. By contrast, an AI survey generator (like Specific’s) is instant—just describe your goal, and the AI builds the structure, applies best practices, and can even edit the survey as you chat. You can try the AI survey editor to see how easy it is.
Manual Surveys | AI-Generated Conversational Surveys |
|---|---|
Time-consuming to create and edit | Instant, built from a prompt or conversation |
Rigid, one-size-fits-all | Personalized, adapts to context and responses |
Lacks dynamic follow-up | AI asks smart follow-ups in real time |
Hard to analyze responses | AI summarizes and categorizes feedback for you |
Why use AI for online course student surveys? AI surveys help you keep up with the pace and scale of e-learning. Already, in 2023, 60% of online courses used AI-driven assessments[2], making AI an expected, not optional, part of the experience. With Specific, the feedback journey is smooth, conversational, and tailored to both survey creators and online students. Everyone gets a better, more efficient experience. For more on building your survey from scratch, check out the detailed guide.
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