Teacher survey for students: great questions for midterm course evaluation

Creating an effective teacher survey for students requires balancing depth with brevity—especially during midterm course evaluation season when students are juggling multiple responsibilities.

Conversational teacher surveys can probe deeper through smart, AI-powered follow-ups while still keeping completion times short. With AI survey creation tools like Specific, it’s possible to gather rich, actionable feedback without overburdening your students.

Essential questions for your midterm student feedback survey

Here's a battle-tested template that captures comprehensive student feedback in under 10 minutes:

1. Overall course satisfaction (0–10)
   Follow-up: If rating below 7, probe for specific examples of dissatisfaction.

2. Course clarity: “How clear are the course objectives and expectations?”
   Follow-up: If unclear, ask for particular areas that need clarification.

3. Teaching effectiveness: “How effective is the instructor’s teaching style?”
   Follow-up: If less effective, prompt: ‘What would make lectures more engaging?’

4. Workload balance: “How manageable is the course workload so far?”
   Follow-up: If too heavy/light, ask for examples or suggestions to balance it.

5. Most valuable aspect: “What part of the course has been most valuable to your learning?”
   Follow-up: Probe for reasons and specific experiences.

6. Area for improvement: “What’s one thing you’d change about the course?”
   Follow-up: Request actionable suggestions if feedback is vague.

7. Sense of inclusion: “Do you feel included and respected in class discussions?”
   Follow-up: Ask for examples if the answer is ‘rarely’ or ‘sometimes’.

8. AI tool usage: “Have you used any AI tools (e.g., ChatGPT) for this course?”
   Follow-up: If yes, ask how it affected learning or assignments.

9. Instructor support: “How approachable and helpful has your instructor been?”
   Follow-up: Probe for examples if ratings are low.

10. Feedback frequency: “Do you receive feedback on your work often enough?”
    Follow-up: If not, ask how more frequent feedback could help.

11. Resource quality: “How helpful are the materials (readings, slides, videos)?”
    Follow-up: Prompt for improvements if materials are rated low.

12. Open comments: “Is there anything else you’d like your instructor to know?”
    Follow-up: If no comment, prompt gently for any small suggestions or unspoken issues.

Using varied question types—ratings, open-ended prompts, and targeted follow-ups—lets you surface both quantitative trends and nuanced narrative insights. AI-powered survey builders reduce manual setup and leverage automated follow-ups for richer data. For example, a 2024 study found that AI-assisted survey tools in education reduce data processing labor by over 55%, streamlining response analysis and freeing up more time for action. [6]

Building trust through anonymity settings

Students provide more honest and candid feedback when they know their responses are viewed anonymously, which is critical for a successful feedback process during course evaluations.

With Specific, enabling anonymous mode in your survey settings encourages open responses—students know that names and identities aren’t linked to their answers, yet the platform can still ask smart, AI-powered follow-up questions during the chat. To do this, simply configure the survey’s settings in the AI survey editor, toggling on anonymous mode while retaining contextual response tracking for improved follow-up logic.

Even with anonymous feedback, teachers see aggregate response trends without the risk of identifying individual students, ensuring a respectful balance between privacy and actionable analytics.

Managing survey frequency with recontact periods

Survey fatigue is real—too many requests lower both response rates and quality. That’s why controlling your survey’s recontact period is crucial for ongoing feedback:

• For midterm evaluations, I recommend a 4–6 week recontact window. This ensures each student receives only one survey per course stage, aligning with their natural feedback rhythm rather than overwhelming them.

• End-of-term surveys can then be set up as a separate one-off, avoiding overlap with midterm requests or exam periods.

With recurring feedback settings in Specific, you can automate these cycles and adjust recontact periods in the survey configuration—letting students provide feedback at key milestones, never more than necessary. This leads to more thoughtful responses and fewer complaints about being over-surveyed.

Supporting multilingual classrooms with automatic translations

In diverse classrooms, language barriers shouldn’t prevent students from sharing valuable feedback. Surveys are only useful if every student fully understands and can express themselves in their preferred language.

Specific’s automatic translation and language detection features address this challenge head-on. When enabled, students automatically see your midterm course evaluation survey in the language they use in your online learning platform, app, or device. For instance, if a student’s browser is set to Spanish, the survey questions and AI prompts appear in Spanish—no manual setup needed.

All survey responses, regardless of language, are translated back so teachers can analyze and compare them together. This ensures everyone’s voice is included in the final analysis and makes the feedback process inclusive and equitable.

Analyzing feedback patterns across class sections

If you teach multiple sections, you know each group can have its own personality, challenges, and areas of strength. Identifying these differences is key to targeted course adjustments.

With Specific’s chat-powered AI response analysis, you can ask targeted questions and explore patterns by section or class period. The analysis chat lets you use prompts like:

Compare the feedback between my morning and afternoon sections. What are the main differences in student satisfaction and learning challenges?

What are the top 3 areas for improvement mentioned by students, and which class sections mentioned each issue most frequently?

This approach streamlines understanding—AI does the heavy lifting of grouping, summarizing, and surfacing themes. According to a 2024 study, using AI to analyze survey data in education settings cut manual processing time by 55% and improved accuracy in identifying key feedback issues. [6]

For more examples of how to use chat-based analysis and follow-ups, check out the guide on automated probing questions and GPT-powered response analysis.

Maximizing student participation in course evaluations

• Choose timing carefully—avoid sending surveys during midterms or finals week

• Send 1–2 brief reminders for non-responders

• Allocate a few minutes of class time for survey completion

• Explain how their feedback will be used to make real improvements

• Consider small participation incentives, like “drop your lowest quiz score” or offering class shout-outs

Conversational survey formats increase completion rates—students respond more naturally to chat-style questions than traditional static forms. In fact, 67% of secondary school students in 2024 reported using AI chatbots for learning tasks, and engagement is significantly higher in conversational formats. [2] The easier and more relevant the process feels, the more honest and complete the responses.

Ready to gather meaningful student feedback? Create your own midterm evaluation survey and start understanding what your students really think about your course.

If you want to get started with a shareable, mobile-friendly survey, check out conversational survey pages for easy distribution.