Reproducibility in AI-Moderated Research: A Researcher Assessment
This survey explores researcher experiences with reproducibility, transparency, and data quality in AI-moderated research. It serves as a replication study template to understand current practices, identify barriers, and assess the role of platform transparency in enabling reproducible AI-moderated studies.
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Template Overview
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This professionally designed survey template helps you gather valuable insights with intelligent question flow and automated analysis.
Sample Survey Items
Q1
Chat Message
Welcome to this study on reproducibility in AI-moderated research.
This survey is part of a research effort to understand how researchers document, replicate, and evaluate AI-moderated studies. Your participation is entirely voluntary, and you may stop at any time. There are no right or wrong answers — we are interested in your honest professional opinions and experiences.
Your responses will be kept confidential, analyzed in aggregate, and used for academic and methodological research purposes only.
Estimated completion time: 12–15 minutes.
Q2
Multiple Choice
Have you personally designed, conducted, or evaluated research that uses AI moderation (e.g., AI-driven interview probes, AI-moderated qualitative discussions, or AI-assisted survey logic)?
Yes, I have direct experience with AI-moderated research
No, but I am familiar with AI-moderated research methods
No, I am not familiar with AI-moderated research
Q3
Multiple Choice
Approximately how many AI-moderated research projects have you been involved with in the past 24 months?
1–2 projects
3–5 projects
6–10 projects
More than 10 projects
Q4
Multiple Choice
Which AI-moderated research platforms or tools have you used? (Select all that apply)
QuestionPunk
Remesh
Discuss.io (AI features)
Forsta / Confirmit (AI features)
Qualtrics (AI-assisted logic)
Custom-built AI moderation tools
Other (please specify)
Q5
Chat Message
<p>For the purposes of this study, <strong>'AI-moderated research'</strong> refers to any research methodology where an AI system actively conducts or adapts participant interactions in real time. This includes:</p><p>AI-driven qualitative interviews (where AI asks follow-up probes)</p><p>AI-moderated focus groups or discussions</p><p>AI-assisted survey logic that adapts questions based on prior responses</p><p>This does <strong>NOT</strong> include:</p><p>Using AI solely for data analysis after collection</p><p>Using AI to write survey questions without real-time moderation</p><p>Simple chatbot-based data collection with fully scripted flows</p>
Q6
Opinion Scale
When you have conducted or contributed to an AI-moderated study, how thoroughly did you typically document the AI system prompts and instructions used?
Range: 1 – 5
Min: Not documented at allMid: NeutralMax: Fully and systematically documented
Q7
Opinion Scale
How thoroughly did you typically document the AI model version and configuration parameters (e.g., temperature, model name, token limits)?
Range: 1 – 5
Min: Not documented at allMid: NeutralMax: Fully and systematically documented
Q8
Opinion Scale
How thoroughly did you typically document the logic flow and branching rules governing the AI moderation?
Range: 1 – 5
Min: Not documented at allMid: NeutralMax: Fully and systematically documented
Q9
Opinion Scale
How thoroughly did you typically document the sampling criteria and participant recruitment procedures?
Range: 1 – 5
Min: Not documented at allMid: NeutralMax: Fully and systematically documented
Q10
Multiple Choice
What are the primary barriers you face when documenting AI-moderated study protocols? (Select all that apply)
Platform does not expose configuration details
AI model versions change without notice
No established documentation standards exist
Time constraints during project execution
Proprietary restrictions from the platform vendor
Lack of institutional requirements for AI documentation
Uncertainty about which elements are necessary to document
Other (please specify)
Q11
Chat Message
The following section presents elements that could be disclosed to support transparency and reproducibility in AI-moderated research. For each element, please indicate whether the AI research platform you have used most recently makes this information accessible to you as a researcher.
Q12
Multiple Choice
On your most recently used AI research platform, is the specific AI model name and version (e.g., GPT-4o, Claude 3.5) accessible to you?
Yes, fully accessible
Partially accessible (some details available)
Not accessible
I don't know / Never checked
Q13
Multiple Choice
Are the system prompts and instructions given to the AI accessible to you?
Yes, fully accessible
Partially accessible (some details available)
Not accessible
I don't know / Never checked
Q14
Multiple Choice
Are the AI configuration parameters (e.g., temperature, max tokens, top-p) accessible to you?
Yes, fully accessible
Partially accessible (some details available)
Not accessible
I don't know / Never checked
Q15
Multiple Choice
Is the logic flow and branching structure of the AI moderation accessible to you?
Yes, fully accessible
Partially accessible (some details available)
Not accessible
I don't know / Never checked
Q16
Multiple Choice
Are the complete raw transcripts of AI-participant interactions accessible to you?
Yes, fully accessible
Partially accessible (some details available)
Not accessible
I don't know / Never checked
Q17
Opinion Scale
How important is each of the following for enabling reproducibility of AI-moderated research?
— Disclosure of AI model name and version
Range: 1 – 7
Min: Not at all importantMid: NeutralMax: Extremely important
Q18
Opinion Scale
— Disclosure of system prompts and instructions
Range: 1 – 7
Min: Not at all importantMid: NeutralMax: Extremely important
Q19
Opinion Scale
— Disclosure of AI configuration parameters
Range: 1 – 7
Min: Not at all importantMid: NeutralMax: Extremely important
Q20
Opinion Scale
— Disclosure of logic flow and branching rules
Range: 1 – 7
Min: Not at all importantMid: NeutralMax: Extremely important
Q21
Opinion Scale
— Access to complete raw interaction transcripts
Range: 1 – 7
Min: Not at all importantMid: NeutralMax: Extremely important
Q22
Opinion Scale
Compared to traditional (human-moderated) qualitative research, how would you rate the overall data quality of AI-moderated research?
Range: 1 – 7
Min: Much lower qualityMid: NeutralMax: Much higher quality
Q23
Opinion Scale
Compared to traditional human-moderated research, how would you rate AI-moderated research on: depth of participant responses
Range: 1 – 7
Min: Much worseMid: NeutralMax: Much better
Q24
Opinion Scale
Compared to traditional human-moderated research, how would you rate AI-moderated research on: consistency of moderation across participants
Range: 1 – 7
Min: Much worseMid: NeutralMax: Much better
Q25
Opinion Scale
Compared to traditional human-moderated research, how would you rate AI-moderated research on: participant comfort and candor
Range: 1 – 7
Min: Much worseMid: NeutralMax: Much better
Q26
Opinion Scale
Compared to traditional human-moderated research, how would you rate AI-moderated research on: ability to capture unexpected insights
Range: 1 – 7
Min: Much worseMid: NeutralMax: Much better
Q27
Opinion Scale
Compared to traditional human-moderated research, how would you rate AI-moderated research on: reproducibility of findings across studies
Range: 1 – 7
Min: Much worseMid: NeutralMax: Much better
Q28
Multiple Choice
Have you ever attempted to replicate an AI-moderated study (either your own or another researcher's)?
Yes, I have replicated my own AI-moderated study
Yes, I have replicated another researcher's AI-moderated study
Yes, both my own and others' studies
No, I have not attempted a replication
Q29
Opinion Scale
How confident are you that an AI-moderated study you have conducted could be successfully replicated by another researcher using the same platform and configuration?
Range: 1 – 7
Min: Not at all confidentMid: NeutralMax: Extremely confident
Q30
Ranking
Please rank the following challenges to reproducibility in AI-moderated research from most significant (1) to least significant.
Drag to order (top = most important)
AI model updates change behavior over time
Platform-specific 'black box' configurations
Non-deterministic AI outputs (randomness in responses)
Lack of standardized documentation protocols
Insufficient access to system prompts and parameters
Variations in participant behavior across samples
Q31
Opinion Scale
To what extent do you agree or disagree with the following statement: AI research platforms that share their prompts, models, and logic flows openly produce more reproducible research than platforms that do not disclose these elements.
Please describe a specific experience where you encountered a reproducibility challenge in AI-moderated research. What happened, and how did you attempt to address it?
AI InterviewLength: 2Personality: [Object Object]Mode: Fast
Reference questions: 7
Q33
Long Text
Based on your experiences, what single change to AI-moderated research platforms or practices would most improve the reproducibility of studies conducted on these platforms?
Max chars
Q34
Long Text
Based on your responses throughout this survey, please share any additional thoughts or observations about reproducibility in AI-moderated research.
Max chars
Q35
Dropdown
Which of the following best describes your primary professional role?
Academic researcher
Market research professional
UX / Design researcher
Data scientist / AI specialist
Research operations / insights manager
Consultant / Independent researcher
Student (graduate or postgraduate)
Other (please specify)
Q36
Dropdown
How many years of experience do you have conducting research (any methodology)?
Less than 2 years
2–5 years
6–10 years
11–20 years
More than 20 years
Q37
Dropdown
In which sector do you primarily conduct research?
Academia / Higher education
Technology / Software
Healthcare / Pharmaceuticals
Financial services
Consumer packaged goods
Media / Entertainment
Government / Public sector
Non-profit / NGO
Consulting / Agency
Other (please specify)
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