Remote Exam Fairness & Privacy Perceptions Survey
Measures student perceptions of fairness, privacy, and acceptability of proctoring practices in remote exams. Designed for higher-education institutions seeking to evaluate and improve remote assessment policies.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
In the last 12 months, have you taken any remote exams (proctored or unproctored)?
- Yes
- No
How many remote exams (including unproctored) did you complete in the last 12 months?
- 1
- 2–3
- 4–6
- 7 or more
- Prefer not to say
Which proctoring features were used in any of your remote exams? Select all that apply.
- Webcam monitoring
- Microphone/audio capture
- Screen sharing or recording
- Room scan (pan the camera)
- Photo ID verification
- Browser lockdown or site whitelist
- Keystroke/typing analysis
- Not sure / Don't remember
Overall, how fair did your remote exams feel compared with in-person exams?
How intrusive did the proctoring feel during your remote exams?
Please rank the following aspects of remote exams from most important to least important to you.
- Fair grading accuracy
- Academic integrity (preventing cheating)
- Student privacy
- Accessibility and accommodations
- Technical reliability
- Clear communication from the provider
- Convenience/flexibility
Based on your responses in this survey, what changes would most improve fairness and privacy in remote exams?
What is your age?
- Under 18
- 18–20
- 21–24
- 25–29
- 30–39
- 40–49
- 50 or older
- Prefer not to say
Thank you for completing this survey! Your responses are confidential and will be used to improve remote exam policies. Your participation is greatly appreciated.
Which types of remote exams did you take in the last 12 months? Select all that apply.
- Live human proctor via webcam
- AI-automated proctoring
- Unproctored (no proctor)
- Open-book allowed
- Not sure / Don't remember
The exam rules and expectations were clearly communicated before the exam.
The exam provider clearly explained how my data would be stored and used.
We'd like to understand more about your experiences with fairness and privacy in remote exams. Please share your thoughts, and our AI moderator will ask a few follow-up questions.
Which best describes your gender?
- Woman
- Man
- Non-binary
- Prefer not to say
The exam format gave me a fair opportunity to demonstrate my knowledge.
I felt confident that my personal data was handled securely during the exam.
Where do you primarily study?
- Africa
- Asia
- Europe
- North America
- South America
- Oceania
- Prefer not to say
All students had equal access to the resources needed for the exam.
Rank these proctoring practices from most acceptable to least acceptable to you.
- Photo ID verification
- Webcam on during exam
- Screen sharing/recording
- Room scan
- Recording the entire session
What is your current highest level of education?
- Secondary/High school
- Vocational/Technical
- Some college/Undergraduate in progress
- Bachelor's degree
- Graduate/Professional (Master's/PhD/MD/etc.)
- Other
- Prefer not to say
The grading felt consistent and unbiased.
What is your current enrollment status?
- Full-time student
- Part-time student
- Not currently enrolled (completed within last 12 months)
- Other
- Prefer not to say
Compared with in-person settings, how prevalent do you believe cheating was in your remote exams?
What is your primary field of study?
- STEM (e.g., CS, Engineering, Math, Natural Sciences)
- Social Sciences
- Arts & Humanities
- Business/Economics
- Health & Medicine
- Education
- Other
- Prefer not to say
What’s included
AI follow-ups
Adaptive probes on open-ended answers that pull out detail a static form would miss.
Attention checks
Built-in safeguards against rushed answers and low-quality respondents.
AI-drafted copy
Wording, ordering, and branching written by the AI — tuned to your research goal.
Auto report
Themes, quotes, and a plain-English summary write themselves once responses come in.
How it compares
We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.
Why this template
- Purpose-built for remote exam contexts, not general remote learning — includes proctoring feature usage questions, ranked acceptability of specific proctoring practices, and opinion-scale items on fairness, clarity of rules, equal access, and grading consistency.
- Dedicated privacy-trust items (data storage transparency, security confidence) alongside fairness items, letting institutions separate 'privacy concern' from 'fairness concern' in results.
- Includes an adaptive AI follow-up interview segment to probe open-ended reasoning behind fairness/privacy scores, something static question sets can't do.
- Open-ended 'what would improve fairness' question plus demographic breakdowns (enrollment status, field of study, education level) support segmented, actionable reporting for institutional policy reviews.
QuestionPro
Remote learning survey questions and sample survey templateThis is a general remote-learning pulse survey template aimed at gauging student experience with online/remote instruction broadly, not exam proctoring or privacy specifically. It's a fielding-ready template on an established survey platform, but institutions would need to substantially rewrite or supplement it to cover exam fairness and proctoring acceptability. Useful as a broader remote-learning satisfaction pulse rather than a proctoring/privacy-focused instrument.
What it does well
- Established survey platform with a ready-to-use template and presumably customizable question library
- Targets the same general audience (students in remote/online learning settings)
- Likely supports standard question types (multiple choice, rating scales) for quick deployment
Where it falls short
- No exam-specific or proctoring-specific content (no proctoring feature checklist, no ranking of proctoring practice acceptability, no data-handling trust items)
- Static question format with no adaptive AI follow-up interview to probe why students feel exams were fair/unfair or how privacy concerns arose
- No published methodology on question design or transparent prompt logic, and no automated per-response quality scoring
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.
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