Q01
Message
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Generative AI and Student Learning Experience Survey
A research instrument measuring how generative AI tools affect student learning outcomes across learning depth, critical thinking, knowledge retention, and metacognitive awareness. Designed for pre/post and experimental research designs. Estimated completion time: 10–14 minutes.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
30 questions · ~13 min
Q02
Dropdown
Please indicate when you are completing this survey.
- Pre-intervention (beginning of study period)
- Post-intervention (end of study period)
- Single administration (cross-sectional)
Q03
Multiple Choice
Are you currently enrolled as a student at a college or university?
- Yes
- No
Q04
Multiple Choice
Which of the following generative AI tools have you used for learning or coursework? Select all that apply.
- ChatGPT (OpenAI)
- Claude (Anthropic)
- Gemini (Google)
- Microsoft Copilot
- Perplexity AI
- Grammarly AI features
- GitHub Copilot
- Other (please specify)
Q05
Multiple Choice
For which of the following learning activities do you use generative AI tools? Select all that apply.
- Understanding or summarizing readings and lecture notes
- Brainstorming ideas for assignments or projects
- Writing or drafting essays and reports
- Solving problem sets or practice exercises
- Studying for exams or quizzes
- Generating examples or explanations of concepts
- Getting feedback on my work
- Coding or technical tasks
- Research and finding sources
- Language translation or editing
- Other (please specify)
Q06
Message
The next set of questions asks about your learning experiences when using generative AI tools. Please think about your most recent course where you used AI tools and answer based on that experience. There are no right or wrong answers — we are interested in your honest perceptions.
Q07
Opinion Scale
How often do you check the accuracy or validity of information provided by generative AI before using it in your work?
Scale: 1 – 5
Min:NeverMax:Always
Q08
Opinion Scale
Thinking about material you learned with the help of generative AI, how confident are you that you could recall and explain the key concepts without any AI assistance?
Scale: 1 – 7
Min:Not at all confidentMax:Extremely confident
Q09
Opinion Scale
When starting a learning task that involves generative AI, how often do you set specific learning goals for yourself before beginning?
Scale: 1 – 5
Min:NeverMax:Always
Q10
Opinion Scale
Overall, how has your use of generative AI tools affected the quality of your learning?
Scale: 1 – 7
Min:Significantly decreased learning qualityMax:Significantly increased learning quality
Q11
Dropdown
What is your current academic level?
- First-year undergraduate
- Second-year undergraduate
- Third-year undergraduate
- Fourth-year undergraduate or beyond
- Master's student
- Doctoral student (PhD, EdD, etc.)
- Professional degree student (JD, MD, MBA, etc.)
- Other
Q12
Multiple Choice
Have you used any generative AI tools (e.g., ChatGPT, Claude, Gemini, Copilot) for learning or coursework in the past 3 months?
- Yes
- No
Q13
Opinion Scale
In a typical week during the academic term, how often do you use generative AI tools for learning or coursework?
Scale: 1 – 5
Min:NeverMax:Daily or almost daily
Q14
Ranking
Please rank the following learning activities from the one where you use generative AI MOST (1) to LEAST.
- Understanding or summarizing material
- Brainstorming and generating ideas
- Writing and drafting
- Problem-solving and practice
- Studying and exam preparation
- Getting feedback on my work
Drag to rank
Q15
Opinion Scale
When using generative AI for this course, to what extent did you develop a deep understanding of the underlying concepts?
Scale: 1 – 7
Min:Not at allMax:To a great extent
Q16
Opinion Scale
How often do you form your own conclusions about a topic before consulting generative AI?
Scale: 1 – 5
Min:NeverMax:Always
Q17
Opinion Scale
Compared to material you learned WITHOUT generative AI, how would you rate your ability to retain information learned WITH generative AI?
Scale: 1 – 7
Min:Much worse retentionMax:Much better retention
Q18
Opinion Scale
While using generative AI for learning, how often do you pause to check whether you actually understand the material rather than just reading the AI's response?
Scale: 1 – 5
Min:NeverMax:Always
Q19
AI Interview
Based on your responses in this survey, please share any additional thoughts about how generative AI has influenced your learning experience — both positively and negatively.
Q20
Dropdown
What is your primary field of study?
- Arts & Humanities
- Social Sciences
- Business & Management
- Natural Sciences
- Engineering & Technology
- Computer Science & Information Technology
- Health Sciences & Medicine
- Education
- Law
- Mathematics & Statistics
- Other (please specify)
Q21
Opinion Scale
How would you describe your overall level of engagement with your current coursework?
Scale: 1 – 7
Min:Not at all engagedMax:Extremely engaged
Q22
Opinion Scale
When using generative AI for this course, to what extent were you able to apply concepts to new problems or scenarios on your own?
Scale: 1 – 7
Min:Not at allMax:To a great extent
Q23
Opinion Scale
How often do you question the assumptions or perspectives embedded in generative AI responses?
Scale: 1 – 5
Min:NeverMax:Always
Q24
Opinion Scale
How confident are you that you could apply concepts learned with generative AI to a different course or real-world situation?
Scale: 1 – 7
Min:Not at all confidentMax:Extremely confident
Q25
Opinion Scale
How often do you change your approach to using generative AI when you realize your current strategy is not helping you learn effectively?
Scale: 1 – 5
Min:NeverMax:Always
Q26
Dropdown
What is your age?
- 18–20
- 21–23
- 24–26
- 27–30
- 31–35
- 36–40
- 41 or older
- Prefer not to say
Q27
Opinion Scale
When using generative AI for this course, to what extent did you analyze, compare, or critically evaluate the information you encountered?
Scale: 1 – 7
Min:Not at allMax:To a great extent
Q28
Opinion Scale
How often do you consult additional sources (textbooks, journals, peers) to compare against what generative AI provides?
Scale: 1 – 5
Min:NeverMax:Always
Q29
Opinion Scale
After completing a learning task with generative AI, how often do you reflect on whether the AI actually helped you learn or just helped you complete the task?
Scale: 1 – 5
Min:NeverMax:Always
Q30
Opinion Scale
When using generative AI for this course, to what extent did you create original work or synthesize ideas beyond what the AI provided?
Scale: 1 – 7
Min:Not at allMax:To a great extent
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
- Includes dedicated opinion-scale batteries mapped to four distinct constructs (learning depth, critical thinking, knowledge retention, metacognitive awareness) rather than generic satisfaction questions.
- Uses behavioral and ranking items (e.g., ranking which learning activities most involve generative AI, multi-select on tool usage) to capture actual usage patterns before asking about outcomes.
- Closes with an AI follow-up interview that adapts to each respondent's prior answers, letting them elaborate on their own experience instead of ending at a static open-text box.
- Structured for pre/post and experimental research designs with demographic and enrollment screening (academic level, field of study, age, enrollment status) built in for segmentation.
Jotform
E-learning Student Performance Evaluation Form TemplateThis is a general e-learning performance evaluation form, not a generative-AI-specific research instrument. It's fielding-ready as a form builder template but would need substantial editing to measure constructs like critical thinking or metacognitive awareness tied to AI tool use. Best suited for course-level feedback rather than academic research on generative AI.
What it does well
- Easy drag-and-drop customization typical of Jotform templates
- Quick to deploy for general course/e-learning feedback
- Integrates with Jotform's broader form ecosystem (payments, notifications, etc.)
Where it falls short
- No generative-AI-specific question content; would require full rebuild for this research topic
- Static question set with no adaptive follow-up or AI-driven probing
- No automated quality scoring of open-ended responses
QuestionPro
Distance learning survey template for studentsA distance-learning experience survey template focused on remote/online learning satisfaction, not generative AI use specifically. It's a ready-to-field template within QuestionPro's platform but covers a different construct set than AI-driven learning outcomes. Researchers would need to substantially rewrite items to address critical thinking or metacognition around AI tools.
What it does well
- Established survey platform with standard logic and reporting features
- Template addresses broader distance-learning context which may be useful for comparison studies
- Supports typical survey distribution channels
Where it falls short
- No generative-AI-specific items on critical thinking, retention, or metacognitive awareness
- No adaptive AI interview or voice-based follow-up to probe individual responses
- No published methodology on prompt design or scoring transparency
SurveyMonkey
Distance Learning Survey TemplateOriginally built around COVID-era distance learning check-ins, this template targets remote schooling logistics and satisfaction, not generative AI's cognitive effects on students. It is a usable, fielding-ready template on SurveyMonkey's platform but is topically distant from generative AI research needs. Would function better as a general remote-learning pulse survey than an experimental research instrument.
What it does well
- Widely recognized, easy-to-deploy survey platform
- Simple structure suited for quick pulse-check style feedback
- Established reporting dashboard for descriptive statistics
Where it falls short
- No content addressing generative AI tools or their cognitive/learning impact
- Fixed question flow with no adaptive follow-up questioning
- No mechanism for scoring response quality or depth of reflection
SurveySparrow
Distance Learning Check-in Bot TemplateA conversational check-in bot for distance learning during COVID-19, aimed at brief pulse-style engagement rather than in-depth research on generative AI's effect on learning. Its chatbot format is fielding-ready but designed for quick check-ins, not multi-construct academic measurement. Not suited as-is for pre/post experimental research designs.
What it does well
- Conversational chatbot format may feel more engaging than static forms
- Good for quick, low-friction check-ins with students
- Native to SurveySparrow's chat-style survey product
Where it falls short
- No generative-AI-specific or multi-construct research content (learning depth, retention, metacognition)
- Chatbot follow-ups are scripted, not adaptive AI-generated based on individual response content
- No transparent prompt methodology or automated quality scoring of responses
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.