Survey example: College Doctoral Student survey about funding and stipend adequacy

This is an example of an AI survey about funding and stipend adequacy for college doctoral students—see and try the example to experience it yourself.

Everyone struggles to design effective college doctoral student funding and stipend adequacy surveys because it’s tough to capture nuances across disciplines and groups. One-size-fits-all surveys just don’t cut it.

We built Specific so anyone can generate, launch, and analyze conversational surveys in minutes—leveraging the same technology powering this example. All tools you see here are built by Specific, the leader in AI-driven feedback collection.

What is a conversational survey and why AI makes it better for doctoral students

Traditional survey creation for funding and stipend adequacy is slow, often generic, and misses the context that’s so critical for doctoral students. We’ve seen how manual forms rarely capture the hardships some face—whether it’s about stipends falling under the poverty line in Canada, or major funding gaps across different disciplines in the U.S. [4][5]

AI survey generators flip the script. Instead of building question lists by hand, you tell the AI what you need, and it crafts an expert-level survey instantly—complete with context-aware follow-ups tailored to doctoral students in varied fields. That’s a game changer for feedback quality.

Why use AI for college doctoral student surveys?

• Better insights: AI-generated follow-ups drill deeper on ambiguous answers, surfacing context behind stipend adequacy complaints and funding struggles.

• Faster creation: AI survey makers instantly produce ready-to-use surveys that experts love, no manual copy-paste required.

• Richer data: Real-time conversational flow keeps responses honest, detailed, and nuanced.

Specific delivers the best-in-class experience for conversational surveys—respondents stay engaged, and creators see higher completion rates with actionable data. If you want to see the power of conversational AI survey examples in practice, try generating your own or read our deep dive on the best questions for college doctoral student funding surveys.

Automatic follow-up questions based on previous reply

What makes Specific’s AI survey examples truly conversational is the way our system asks follow-ups—live, based directly on what the doctoral student just said. The AI listens and responds like a human researcher, drawing out details and clarifying uncertainty. This dynamic probing is even more important given the real stakes: recent reports show doctoral stipends vary wildly, from Canada’s many science stipends under the poverty line, to Brown University’s $52,198 stipend baseline [3][5].

Without smart follow-up questions, responses remain vague or misleading. Here’s a concrete example:

• Doctoral student: “My funding is okay, but I struggle at the end of each month.”

• AI follow-up: “Can you share what specific expenses make it challenging to cover costs by month-end? Are those recurring or unexpected?”

• Doctoral student: “Stipend is average for my department.”

• AI follow-up: “Which department are you in, and do you feel your stipend is fair compared to peers in other fields?”

With automated follow-ups, you avoid time-consuming back-and-forth emails and surface the context you need immediately. This is a completely new way of surfacing richer feedback—try generating a survey to see it come to life.

Follow-ups transform a static survey into a true conversation—this is the essence of a conversational survey example.

Easy editing, like magic

Editing your survey with Specific feels almost unreal. You simply chat with the AI survey editor—say what you want changed, and the AI brings expert-level updates in seconds. No more wrestling with question logic or rewriting—just describe the revision, and the system does the hard work. This lets you test and refine your AI survey example instantly, all via a natural chat.

Flexible delivery: landing page or in-product

You can launch your AI survey example as a:

• Sharable landing page survey—perfect for emailing doctoral students, sharing in academic networks, or posting links in Slack groups.

• In-product survey—embed the conversational survey directly in a university portal or intranet, giving students a seamless way to share funding experiences while logged in.

For most funding and stipend adequacy surveys, the sharable landing page format works best—it’s ideal for reaching doctoral students wherever they are, regardless of their tech platform or department. But for universities running centralized support or campus app initiatives, in-product surveys deliver targeted feedback right inside your digital campus experience.

Read more about these delivery methods and when to use each in our articles on how to create college doctoral student surveys about funding and stipend adequacy.

Instant AI-powered survey analysis

Collecting responses is only half the story—the real breakthrough comes in analysis. With Specific’s AI survey response analysis, you get automated summaries, instant topic detection, and even the ability to chat with AI about what your doctoral students are really saying about funding and stipends. No spreadsheets, no sifting through hundreds of open-text responses—just automated survey insights delivered instantly.

Curious about best practices? Dive into our full guide on how to analyze college doctoral student funding and stipend adequacy survey responses with AI.

See this funding and stipend adequacy survey example now

Experience firsthand how AI-powered survey creation, dynamic follow-up questions, and instant insights can transform your approach to doctoral student funding research—see the full survey example and discover how much deeper you can go in minutes.