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Best questions for college doctoral student survey about advisor relationship quality

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Adam Sabla

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Aug 29, 2025

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Here are some of the best questions for a college doctoral student survey about advisor relationship quality, plus quick tips on what to ask and how to create them. With Specific, you can build a smart, conversational survey in seconds—AI does the heavy lifting for you.

The best open-ended questions for doctoral students on advisor relationship quality

Open-ended questions let college doctoral students express themselves freely and explore nuances in their experience. These questions are especially valuable for capturing the real voices and context behind satisfaction metrics, surfacing insights forms and multiple-choice can easily miss. For example, research shows that approximately 80% of doctoral students report satisfaction with their advisors' academic guidance and support, but the remaining 20%—and even those who are “satisfied”—often have stories to tell about what’s working and what’s not [1]. Open-ended prompts are key to understanding the why behind the numbers.

  1. How would you describe your overall relationship with your advisor?

  2. What has been the most positive aspect of your experience working with your advisor?

  3. Have you faced any significant challenges in your interactions with your advisor? Please explain.

  4. In what ways has your advisor supported your academic or career goals?

  5. Can you share an example of when your advisor helped you navigate a difficult situation?

  6. How accessible is your advisor when you need guidance or support?

  7. Have your expectations about the advisor relationship changed since starting your program? How?

  8. What feedback would you give your advisor to improve their mentoring approach?

  9. Describe a time when your advisor’s feedback made a meaningful impact on your progress.

  10. What’s one thing you wish you’d known about working with advisors before starting your program?

Best single-select multiple-choice questions for doctoral student advisor surveys

Single-select multiple-choice questions are ideal when you want to quantify sentiment, collect stats, or make it easier for respondents to start sharing. They're less demanding than text boxes and help initiate a flow, which is crucial before digging deeper with follow-up questions. For example, when comparing satisfaction between doctoral and terminal master's students, quantifiable choices make such comparisons possible [1].

Question: How satisfied are you with the academic guidance provided by your advisor?

  • Very satisfied

  • Somewhat satisfied

  • Neutral

  • Somewhat dissatisfied

  • Very dissatisfied

Question: How often do you meet with your advisor?

  • Daily

  • Several times a week

  • Once a week

  • Less than once a week

Question: How did you select your doctoral advisor?

  • Assigned without input

  • Chose based on shared research interests

  • Had prior working relationship

  • Other

When to followup with "why?" Sometimes a respondent clicks “somewhat dissatisfied” or “other” but leaves you wondering what’s behind their choice. Always follow up with a “why?” when you notice strong or ambiguous responses. Example: if a student chooses “somewhat dissatisfied” with advisor support, you can prompt, “What contributed to your dissatisfaction?”—helping you gather actionable context.

When and why to add the "Other" choice? Research on advisor selection shows that while most students benefit from choosing advisors based on shared interests or prior relationships, there are always outlier experiences that structured choices miss. Adding “Other” with a followup uncovers unexpected insights, revealing edge cases and ideas you didn’t anticipate [3].

NPS-style question: Would you recommend your advisor?

The Net Promoter Score (NPS) format asks, “How likely are you to recommend your advisor to another doctoral student?” It’s an instant, industry-standard way to benchmark experiences over time, identify promoters and detractors, and prioritize follow-up. Given the finding that frequent advisor meetings correlate with satisfaction [5], an NPS for advisor relationships is a natural fit for doctoral programs. You can generate an NPS survey specifically for doctoral advisor relationships here.

The power of follow-up questions

Follow-ups are the secret to unlocking rich, actionable feedback. Instead of a static form, a conversational survey—like the ones you build with Specific—asks smart, real-time follow-up questions based on the student’s previous answers. This goes far beyond what traditional forms or generic AI survey templates can deliver. (See more about automatic AI follow-up questions.)

  • Doctoral student: “My advisor is helpful, but sometimes I feel unsupported.”

  • AI follow-up: “Can you share a situation where you felt unsupported? What could your advisor have done differently?”

If you don’t ask a follow-up like this, you’re left guessing—is it a scheduling issue, lack of feedback, something personal? Follow-ups create clarity and surface actionable insights.

How many followups to ask? In practice, 2-3 targeted followups are usually enough to achieve clarity and gather the key context you’re after. In Specific, you can configure followup depth or enable skipping to the next question when sufficient detail is gathered—saving time for both students and administrators.

This makes it a conversational survey: Each follow-up guides students further without feeling intrusive, transforming the traditional survey into a true back-and-forth conversation.

Analyze unstructured answers with AI: With all these open-ended responses and stories, manual analysis can overwhelm. But with AI-powered survey response analysis, it’s simple to filter, summarize, and chat with your data—no matter how detailed or varied the responses.

Automated follow-up questions are a game changer. Try generating this survey now to see a truly conversational AI experience in action.

How to prompt ChatGPT (or GPTs) to generate great advisor survey questions

Want to use GPT models directly to brainstorm or refine your questions? Start simple and then add more detail for better results. For example, you can prompt:

Suggest 10 open-ended questions for College Doctoral Student survey about Advisor Relationship Quality.

But, the more context you share, the better the results. Try adding your goal, who you are, or details about your program:

I’m an administrator designing a survey for doctoral students in our Social Sciences PhD program. Our goal is to understand how advisor relationships impact academic progress and wellbeing. Suggest 10 open-ended questions to uncover both strengths and pain points in the advisor-student dynamic.

Once you have a list, ask GPT to structure or cluster them:

Look at the questions and categorize them. Output categories with the questions under them.

Then focus on the category you want to dig into, such as “advisor accessibility” or “emotional support”:

Generate 10 survey questions for the category “advisor accessibility and communication.”

This stepwise refinement—combined with input from stakeholders—ensures you cover every angle that matters for your doctoral student community.

What is a conversational survey (and why AI-generated surveys beat manual forms)

Unlike standard forms, an AI-powered conversational survey adapts in real time, mimicking a live expert interviewer. With tools like Specific, you aren’t just building a static list of questions—your AI agent actively listens, prompts for detail, and clarifies ambiguity right in the flow. This means higher engagement and truer insights, especially for delicate topics like advisor relationships.

Manual Surveys

AI-Generated Conversational Surveys

Questions are static and one-size-fits-all

Adaptive follow-ups based on each answer

Requires lots of manual analysis

AI-powered summaries and insights available instantly

Low response rates for open-text questions

Feels like a real conversation—higher engagement

Survey creation is tedious

Survey generator handles the heavy lifting

Why use AI for college doctoral student surveys? Over 81% of researchers and 86% of students now use AI in their academic routines, so meeting students on their terms (with mobile-friendly, conversational surveys) just makes sense [7][8]. AI survey examples created with Specific adapt instantly to student responses, making the process feel personalized and meaningful for every respondent—no more “robotic” checkbox forms.

Want a step-by-step approach to create a survey with Specific’s AI Survey Generator? It’s a one-stop solution—great questions, rapid editing, and shareable pages all-in-one. And if you need to adjust your survey, the AI survey editor lets you simply chat your changes into place.

Specific offers the best-in-class experience for conversational surveys, making feedback collection not only smooth and quick but surprisingly insightful for both administrators and doctoral students. If you’re looking for the next step beyond traditional survey forms, this is the way to go.

See this advisor relationship quality survey example now

See how expert-designed questions, real-time follow-ups, and instant AI insights can transform your understanding of doctoral advisor relationships. Build smarter surveys and take your research to the next level—start now.

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Sources

  1. cra.org. Doctoral Students Are More Satisfied with Their Advisor Relationships Than Terminal Master’s Students

  2. PMC. Supervisory Styles and Student Wellbeing among Doctoral Students in the United Kingdom

  3. NACADA Journal. Advising Doctoral Students in Education Programs: A Developmental Approach

  4. Emerald. Supervisory Relationship Quality Across Disciplines

  5. Emerald. Meeting Frequency and Student Satisfaction

  6. arxiv.org. Large Language Models in Academic Research Workflows

  7. Campus Technology. 86% of Students Already Use AI in Their Studies

  8. Statista. Frequency of Using AI Tools among Students in Indonesia

  9. Campbell University. Survey: Faculty Concerns about AI Tool Usage

Adam Sabla - Image Avatar

Adam Sabla

Adam Sabla is an entrepreneur with experience building startups that serve over 1M customers, including Disney, Netflix, and BBC, with a strong passion for automation.

Adam Sabla

Adam Sabla is an entrepreneur with experience building startups that serve over 1M customers, including Disney, Netflix, and BBC, with a strong passion for automation.

Adam Sabla

Adam Sabla is an entrepreneur with experience building startups that serve over 1M customers, including Disney, Netflix, and BBC, with a strong passion for automation.