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IEEE ITSS Peer Review Experience Survey
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The IEEE ITSS Peer Review Experience Survey seeks feedback on current review systems for IEEE ITSS journals and conferences. The results will be used in aggregate to improve reviewer training, review-system guidance, reviewer matching, and reproducibility practices. Please do not include manuscript IDs, paper titles, reviewer names, editor names, or confidential information from unpublished manuscripts. Participation is voluntary. The survey does not ask for your name or email address. Estimated completion time is 15–30 minutes for one role and may be longer for multiple roles.
If you are willing to follow up, optional contact details can be provided in the other contact form, which will be linked at the end of the survey.
Welcome and consent
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1.
[C1] I confirm that I am at least 18 years old, participation is voluntary, and I agree to participate in this survey.
Yes, I agree
No, I do not agree
*
2.
[C2] I understand that the survey is about review-system processes, not individual people, and I will not disclose confidential information from active or unpublished submissions.
Yes
No
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3.
[C3] I understand that results may be reported only in aggregate and may be used to design reviewer training, review rubrics, reproducibility checklists, and reviewer-pool activities.
Yes
No
Respondent profile
*
4.
[P1] Which roles have you had in relation to IEEE ITSS journals or conferences during the last three years? Select all that apply.
[Multiple]
Author
Reviewer
Associate Editor, Guest Editor, Editor, or Editorial Board member
Conference Technical Program Committee (TPC) member, Area Chair, Program Chair, or similar
Reader or potential future submitter
PhD student or Early Career Researcher (ECR) interested in reviewing
No direct experience but interested in ITSS publications
Other
*
5.
[P2] What is your current career stage?
Undergraduate student
Master's student
PhD student
Postdoctoral researcher (0-5 years after PhD)
Early-career researcher (other than postdoc), academic (e.g., lecturer, assistant professor), scientist, engineer, policy maker, authority, etc., 0-5 years after PhD (or graduation of the highest degree, e.g., MSc., Bachelor)
Mid-career researcher, academic (e.g., senior lecturer, associate professor), scientist, engineer, policy maker, authority (6–15 years after PhD or graduation of the highest degree)
Senior researcher, academic, scientist, engineer, policy maker, authority (＞15 years after PhD or graduation of the highest degree)
Other
Prefer not to say
6.
[P3] What type of organization do you primarily work or study in?
University / higher education
Research institute
Industry
Government or public agency
Nonprofit or NGO
Independent researcher / self-employed
Other
Prefer not to say
7.
[P4] In which region are you primarily based?
Africa
Asia-Pacific
Europe
Latin America and Caribbean
Middle East
North America
Other
Prefer not to say
8.
[P5] Are you currently an IEEE ITSS member?
Yes
No
Not sure
Prefer not to say
*
9.
[P6] Which research areas best describe your expertise or interests? Select up to five.
[Choose at most 5 items]
Transportation and mobility systems
Traffic flow theory, modeling, and simulation
Automated driving and intelligent vehicles
Connected and cooperative transportation
Artificial intelligence and machine learning
Computer vision, perception, and sensor fusion
Control, optimization, or robotics
Human factors, behavior, psychology, human–machine interaction, or ergonomics
Urban planning, policy, or ethics
Safety, risk, ethics, or responsible AI
Data engineering, benchmarks, or open science
Hardware, sensors, and embedded systems
Other
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10.
[P7] How familiar are you with IEEE ITSS journals and conferences overall?
Not familiar
Slightly familiar
Moderately familiar
Very familiar
Extremely familiar
11.
[P8] Would you like to answer detailed questions from the perspective of all roles you selected, or only your main role?
You may leave this blank to answer all applicable roles.
All applicable roles
Main role only
12.
[P9] If answering from one main role, which role should the survey prioritize?
[Multiple]
Choose one role in which you have experience. Selecting another role replaces your previous choice. Leave this blank to consider all applicable roles. Choose Potential future reviewer or author if you do not have direct experience.
Author
Reviewer
Editor or editorial board
Conference Technical Program Committee (TPC) or chair
Potential future reviewer or author
Venue and role experience
Venue and role experience
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13.
[V1] For each venue below, please indicate your experience during the last three years.
[Multiple]
Select all applicable roles for each venue. Author means submitted a paper; reviewer means served as a reviewer. Editor / AE / Technical Program Committee (TPC) / chair includes editors, associate or guest editors, TPC members, area chairs and program roles. Reader / prospective author means read papers or considered submitting. Within each row, select No experience or Not sure alone.
Author
Reviewer
Editor / AE / TPC / chair
Reader / prospective author
No experience
Not sure
IEEE OJ-ITS
IEEE OJ-ITS
IEEE T-ITS
IEEE T-ITS
IEEE T-IV
IEEE T-IV
IEEE ITS Magazine
IEEE ITS Magazine
ITSC
ITSC
IV
IV
Other IEEE ITSS venue
Other IEEE ITSS venue
*
14.
[V2] Which one venue should be treated as your primary reference point for detailed questions in this survey?
Choose No single primary venue if you have no direct venue experience.
IEEE OJ-ITS
IEEE T-ITS
IEEE T-IV
IEEE ITS Magazine
ITSC
IV
Other IEEE ITSS venue
Not sure
No single primary venue
*
15.
[V3] Approximately how many IEEE ITSS journal manuscripts or conference papers have you submitted as an author in the last three years?
0
1
2-3
4-5
6-10
>10
Not sure
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16.
[V4] Approximately how many IEEE ITSS journal manuscripts or conference papers have you reviewed in the last three years?
0
1
2-3
4-5
6-10
11-20
>20
Not sure
*
17.
[QA] Do you have IEEE ITSS author experience and want to answer the detailed author section?
Yes - I have author experience and would like to answer
No - skip the author section
*
18.
[QR] Do you have IEEE ITSS reviewing experience and want to answer the detailed reviewer section?
Yes - I have reviewer experience and would like to answer
No - skip the reviewer section
*
19.
[QE] Do you have IEEE ITSS editorial or conference-organizing experience and want to answer the detailed editor/Technical Program Committee (TPC) section?
Yes - I have editor/TPC experience and would like to answer
No - skip the editor/TPC section
Author experience
Author experience
*
20.
[A1] For your most recent or most representative IEEE ITSS submission, which venue was it submitted to?
Use your most recent completed review cycle if possible; otherwise select your most recent or most representative submission.
IEEE OJ-ITS
IEEE T-ITS
IEEE T-IV
IEEE ITS Magazine
ITSC
IV
Other IEEE ITSS venue
Not sure
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21.
[A2] What was the approximate time from submission to first decision for that submission?
<1 month
1-2 months
3-4 months
5-6 months
>6 months
Still under review
Not sure / not applicable
22.
[A3] How many review rounds did the submission go through before the final decision, or how many rounds has it completed so far?
0
1
2
3
4 or more
Still in first review
Not sure
23.
[A4] What was the status or final outcome of the submission?
Accepted
Accepted after revision
Major revision invited
Minor revision invited
Rejected after review
Desk rejected or administrative reject
Withdrawn
Still under review
Prefer not to say
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24.
[A5] Please rate your author experience for the selected submission.
Strongly disagree
Disagree
Neither agree nor disagree
Agree
Strongly agree
Not applicable / insufficient experience
Submission instructions were clear
Submission instructions were clear
The submission system was easy to use
The submission system was easy to use
The review timeline was reasonable
The review timeline was reasonable
Editorial communication was clear and timely
Editorial communication was clear and timely
Reviewers appeared to have appropriate expertise
Reviewers appeared to have appropriate expertise
Reviewers understood the interdisciplinary contribution
Reviewers understood the interdisciplinary contribution
Reviews were specific and actionable
Reviews were specific and actionable
Reviews were constructive and professional in tone
Reviews were constructive and professional in tone
Reviewer comments were reasonably consistent with each other
Reviewer comments were reasonably consistent with each other
The decision letter clearly explained the basis for the decision
The decision letter clearly explained the basis for the decision
Reproducibility/data/code expectations were clear
Reproducibility/data/code expectations were clear
25.
[A6] Which issues, if any, did you experience as an author? Select all that apply.
[Multiple]
Long waiting time
Unclear status updates
Reviews were too vague
Reviews were contradictory
Reviewers appeared outside the paper expertise
Interdisciplinary contribution was misunderstood
Excessive or unrealistic revision requests
Concerns about fairness or bias
Unprofessional or discouraging tone
Insufficient guidance on data/code/reproducibility
Technical platform or submission-system difficulty
Formatting or administrative burden
No major issue
Other
26.
[A7] What one change would most improve the author review experience for this venue?
Recommended length: up to 500 characters. Please do not include manuscript IDs, paper titles, reviewer or editor names, or confidential information from active or unpublished submissions.
27.
[A8] Even if the decision was negative, the review feedback helped improve the paper or future research.
If your paper was desk-rejected or you received no external reviews, you may skip this question unless you wish to answer based on other relevant feedback. You may also select Not applicable / insufficient experience.
Strongly disagree
Disagree
Neither agree nor disagree
Agree
Strongly agree
Not applicable / insufficient experience
28.
[A9] For interdisciplinary submissions, reviewers should be explicitly asked to evaluate both domain contribution and methodological validity.
Strongly disagree
Disagree
Neither agree nor disagree
Agree
Strongly agree
Not applicable / insufficient experience
29.
[A10] What guidance would have helped you as an author before submission?
[Multiple]
Clearer scope examples
Venue-specific review criteria
Reproducibility checklist
Data/code availability guidance
Example of constructive reviewer comments
Expected timeline and status definitions
Revision-response template
Interdisciplinary contribution statement template
More transparent criteria for desk reject or conference rejection
Other
Reviewer experience
Reviewer experience
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30.
[R1] For which IEEE ITSS venues have you served as a reviewer in the last three years? Select all that apply.
[Multiple]
IEEE OJ-ITS
IEEE T-ITS
IEEE T-IV
IEEE ITS Magazine
ITSC
IV
Other IEEE ITSS venue
Not sure
*
31.
[R2] How often do you receive IEEE ITSS review invitations that are outside your core expertise?
Never
Rarely
Sometimes
Often
Very often
Not applicable / insufficient experience
32.
[R3] When deciding whether to accept a review invitation, which factors matter most? Select up to five.
[Choose at most 5 items]
Fit with expertise
Deadline length
Current workload
Paper abstract/keywords clarity
Conflict-of-interest clarity
Editorial reputation/venue
Opportunity to learn
Recognition or certificate
Ability to involve a mentored co-reviewer
Expected length/complexity of paper
Prior positive experience with the venue
Other
33.
[R4] Why have you declined IEEE ITSS review invitations, if applicable? Select all that apply.
[Multiple]
No time
Deadline too short
Topic mismatch
Potential conflict of interest
Not enough information in invitation
Too many invitations from the same venue
Lack of recognition
Lack of confidence reviewing interdisciplinary papers
Not familiar with review expectations
Platform difficulty
I have not declined
Other
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34.
[R5] Please rate your reviewer workflow experience.
Strongly disagree
Disagree
Neither agree nor disagree
Agree
Strongly agree
Not applicable / insufficient experience
Invitations contain enough information to decide
Invitations contain enough information to decide
Deadlines are reasonable
Deadlines are reasonable
The paper-management system is easy to use
The paper-management system is easy to use
Review forms are well structured
Review forms are well structured
Editorial instructions are clear
Editorial instructions are clear
Criteria for contribution/novelty/technical quality are clear
Criteria for contribution/novelty/technical quality are clear
Guidance for interdisciplinary assessment is sufficient
Guidance for interdisciplinary assessment is sufficient
Guidance for reproducibility/data/code checks is sufficient
Guidance for reproducibility/data/code checks is sufficient
It is clear how much detail is expected in a review
It is clear how much detail is expected in a review
Communication with editors/TPC is effective
Communication with editors/TPC is effective
Reviewer contributions are appropriately recognized
Reviewer contributions are appropriately recognized
35.
[R6] Which issues, if any, have you experienced as a reviewer? Select all that apply.
[Multiple]
Expertise mismatch
Insufficient review rubric
Unclear decision criteria
Too many simultaneous review requests
Insufficient deadline
Difficulty judging interdisciplinary work
Difficulty evaluating AI/ML/CV/VLM methods
Difficulty evaluating transportation/control/human-factors aspects
Lack of reproducibility guidance
Unclear expectations for data/code checks
No feedback on review quality after decision
Paper-management system issues
Lack of recognition
No major issue
Other
36.
[R7] How confident are you in evaluating the following aspects of an interdisciplinary ITS paper?
Not confident
Slightly confident
Moderately confident
Very confident
Extremely confident
Not applicable
Transportation-system relevance
Transportation-system relevance
AI/ML/CV/VLM method validity
AI/ML/CV/VLM method validity
Control/optimization approach
Control/optimization approach
Experimental or simulation design
Experimental or simulation design
Statistical analysis and baselines
Statistical analysis and baselines
Safety/risk assessment
Safety/risk assessment
Human factors or behavioral claims
Human factors or behavioral claims
Urban planning or policy implications
Urban planning or policy implications
Reproducibility of data/code/model/simulation artifacts
Reproducibility of data/code/model/simulation artifacts
Ethical/privacy considerations
Ethical/privacy considerations
37.
[R8] Which reviewer-training topics would be most useful to you? Select up to six.
[Choose at most 6 items]
Writing constructive reviews
Efficient review workflow
Assessing novelty and contribution
Interdisciplinary review rubric
Evaluating AI/ML/CV/VLM methods
Evaluating transportation theory and simulation
Evaluating control/robotics methods
Evaluating human factors/behavioral studies
Reproducibility and open-science checks
Ethics, bias, and conflicts of interest
Reviewing conference papers efficiently
Mentored/shadow-review practice
Other
38.
[R9] Would a short standardized reviewer checklist make your reviews more efficient and consistent?
Yes
Maybe
No
Not sure
39.
[R10] Would you be willing to join or update your profile in an ITSS reviewer database if invited?
Yes
Maybe
No
Need more information
40.
[R11] What is your realistic annual reviewing capacity for IEEE ITSS venues?
0
1-2 papers
3-5 papers
6-10 papers
>10 papers
It depends on topic and deadline
41.
[R12] What recognition would most motivate high-quality, timely reviews? Select up to three.
[Choose at most 3 items]
Annual reviewer certificate
Public recognition list
Best reviewer award
IEEE/ITSS digital badge
Discount or recognition at ITSC/IV
Mentorship/certification credential
Feedback from editors on review quality
No recognition needed
Other
Editor and conference organizer experience
Editor and conference organizer experience
*
42.
[E1] Which editorial or conference-role experience have you had with IEEE ITSS venues? Select all that apply.
[Multiple]
Editor-in-Chief
Associate Editor
Guest Editor
Editorial Board member
Conference General Chair, Program Chair, Area Chair, Technical Program Committee (TPC) member
Special issue organizer
None of these
Other
*
43.
[E2] For the venue or role you know best, how serious are the following review-management challenges?
Not a challenge
Minor challenge
Moderate challenge
Serious challenge
Critical challenge
Not applicable
Finding enough available reviewers
Finding enough available reviewers
Finding reviewers with appropriate interdisciplinary expertise
Finding reviewers with appropriate interdisciplinary expertise
Late reviews
Late reviews
Reviewers accepting but not submitting
Reviewers accepting but not submitting
Conflicting reviewer recommendations
Conflicting reviewer recommendations
Low-quality or superficial reviews
Low-quality or superficial reviews
Identifying conflicts of interest
Identifying conflicts of interest
Handling reproducibility/data/code issues
Handling reproducibility/data/code issues
Platform/tool limitations
Platform/tool limitations
Communicating consistent expectations to reviewers
Communicating consistent expectations to reviewers
44.
[E3] For difficult interdisciplinary submissions, approximately how many invitations are typically needed to secure enough reviewers?
1-5
6-10
11-20
21-30
More than 30
Not sure
Not applicable
45.
[E4] Which expertise areas are hardest to find among available reviewers? Select all that apply.
[Multiple]
Mixed traffic and automated driving
Intelligent vehicles
AI/ML/deep learning
Computer vision/sensor fusion
VLM/foundation models
Control/optimization/robotics
Traffic flow theory
Simulation/testbeds
Human factors/behavior
Urban planning/policy
Safety/risk/ethics
Data/code/reproducibility
Industry deployment
Other
46.
[E5] Which reviewer-database features would be most useful? Select up to six.
[Choose at most 6 items]
Methodological and technical expertise tags
Past reviewing experience and performance
Publication and keyword matching
Topics reviewers prefer not to review / exclusion areas
Availability/capacity
Recent reviewing workload
Conflict-of-interest flags
Career stage and mentorship status
Willingness to review interdisciplinary papers
Reproducibility/open-science expertise
Preferred venues
Prefered manuscript types or methods (e.g., empirical, methodological, surveys/reviews, datasets, software papers, interdisciplinary work)
Geographic/time-zone information
Integration with paper-management systems
Verified identity and ORCID/profile integration
Automatic profile updating from publications
Other
47.
[E6] What guidance or tools would most improve review quality and consistency?
[Multiple]
Standard reviewer rubric
Venue-specific reviewer templates
Reproducibility checklist
Reviewer onboarding module
Examples of high-quality reviews
Short mentor training for Early Career Researcher (ECR) reviewers
Better reviewer matching tools
Editor / Technical Program Committee (TPC) dashboard for delays
Post-decision reviewer feedback
Other
48.
[E7] Please describe one practical improvement that could be implemented within 2026-2027.
Recommended length: up to 500 characters. Please do not include manuscript IDs, paper titles, reviewer or editor names, or confidential information from active or unpublished submissions.
Review-system quality and venue feedback
Review-system quality and venue feedback
*
49.
[S1] Thinking about your primary venue selected in V2, please rate the current review system.
Very dissatisfied
Dissatisfied
Neutral
Satisfied
Very satisfied
Not applicable / insufficient experience
Overall review experience
Overall review experience
Timeliness
Timeliness
Reviewer expertise matching
Reviewer expertise matching
Fairness and objectivity
Fairness and objectivity
Constructiveness of feedback
Constructiveness of feedback
Consistency across reviews
Consistency across reviews
Clarity of decision communication
Clarity of decision communication
Ease of using the paper-management system
Ease of using the paper-management system
Professional tone
Professional tone
Reproducibility/open-science guidance
Reproducibility/open-science guidance
Suitability for interdisciplinary research
Suitability for interdisciplinary research
50.
[S2] Which IEEE ITSS venue currently needs the most urgent review-process improvement, based on your experience or perception?
IEEE OJ-ITS
IEEE T-ITS
IEEE T-IV
IEEE ITS Magazine
ITSC
IV
Other IEEE ITSS venue
Not sure
All equally
Not enough information
51.
[S3] For each venue you know, indicate whether you have specific suggestions.
No suggestion
I have a suggestion
Not enough experience
IEEE OJ-ITS
IEEE OJ-ITS
IEEE T-ITS
IEEE T-ITS
IEEE T-IV
IEEE T-IV
IEEE ITS Magazine
IEEE ITS Magazine
ITSC
ITSC
IV
IV
52.
[S4_1] Please provide suggestions for IEEE OJ-ITS.
Please do not include manuscript IDs, paper titles, reviewer or editor names, or confidential information from active or unpublished submissions.
53.
[S4_2] Please provide suggestions for IEEE T-ITS.
Please do not include manuscript IDs, paper titles, reviewer or editor names, or confidential information from active or unpublished submissions.
54.
[S4_3] Please provide suggestions for IEEE T-IV.
Please do not include manuscript IDs, paper titles, reviewer or editor names, or confidential information from active or unpublished submissions.
55.
[S4_4] Please provide suggestions for IEEE ITS Magazine.
Please do not include manuscript IDs, paper titles, reviewer or editor names, or confidential information from active or unpublished submissions.
56.
[S4_5] Please provide suggestions for ITSC.
Please do not include manuscript IDs, paper titles, reviewer or editor names, or confidential information from active or unpublished submissions.
57.
[S4_6] Please provide suggestions for IV.
Please do not include manuscript IDs, paper titles, reviewer or editor names, or confidential information from active or unpublished submissions.
*
58.
[S5] How important are the following improvements for IEEE ITSS review systems?
Not important
Slightly important
Moderately important
Very important
Essential
Not applicable
Shorter time to first decision
Shorter time to first decision
Better reviewer expertise matching
Better reviewer expertise matching
Clearer review rubrics
Clearer review rubrics
More transparent status updates
More transparent status updates
Stronger guidance for interdisciplinary papers
Stronger guidance for interdisciplinary papers
Stronger reproducibility/data/code guidance
Stronger reproducibility/data/code guidance
Reviewer training for PhD students and ECRs
Reviewer training for PhD students and ECRs
More recognition for reviewers
More recognition for reviewers
Better paper-management-system usability
Better paper-management-system usability
More consistent desk-screening criteria
More consistent desk-screening criteria
Improved revision-response guidance
Improved revision-response guidance
Mechanisms to handle vague or unprofessional reviews
Mechanisms to handle vague or unprofessional reviews
*
59.
[S6] Which three improvements should be prioritized first in 2026-2027?
[Please select 3 item and sort them]
Select exactly three improvements and rank them from first to third priority.
Shorter time to first decision
Better reviewer expertise matching
Clearer review rubrics
More transparent status updates
Stronger guidance for interdisciplinary papers
Stronger reproducibility/data/code guidance
Reviewer training for PhD students and ECRs
More recognition for reviewers
Better paper-management-system usability
More consistent desk-screening criteria
Improved revision-response guidance
Mechanisms to handle vague or unprofessional reviews
60.
[S7] Should IEEE ITSS journals and conferences use a more standardized review rubric while preserving venue-specific flexibility?
Yes, strongly support
Yes, somewhat support
Neutral
No, somewhat oppose
No, strongly oppose
Not sure
61.
[S8] Please add any other feedback on the current review process that was not covered above.
Recommended length: up to 750 characters. Please do not include manuscript IDs, paper titles, reviewer or editor names, or confidential information from active or unpublished submissions.
Interdisciplinary review and reproducibility
Interdisciplinary review and reproducibility
*
62.
[G1] How often do you observe the following reproducibility or transparency issues in ITS-related papers?
Never
Rarely
Sometimes
Often
Very often
Not applicable / insufficient experience
Data are not available and limitations are not explained
Data are not available and limitations are not explained
Code or model implementation is unavailable
Code or model implementation is unavailable
Simulation settings are incomplete
Simulation settings are incomplete
Baselines are weak or not comparable
Baselines are weak or not comparable
Evaluation metrics are unclear or inconsistent
Evaluation metrics are unclear or inconsistent
Statistical uncertainty or sensitivity analysis is missing
Statistical uncertainty or sensitivity analysis is missing
Dataset collection/annotation details are insufficient
Dataset collection/annotation details are insufficient
Trained models or model cards are unavailable when relevant
Trained models or model cards are unavailable when relevant
Hardware/sensor setup is not described sufficiently
Hardware/sensor setup is not described sufficiently
Privacy/ethics considerations are unclear
Privacy/ethics considerations are unclear
Claims exceed what the evaluation supports
Claims exceed what the evaluation supports
*
63.
[G2] Which items should reviewers be encouraged to check when relevant?
[Multiple]
Data availability statement
Code availability statement
Simulation/testbed configuration
Benchmark and baseline selection
Evaluation metrics and statistical validation
Ablation or sensitivity analysis
Model weights or deployment details when applicable
Dataset documentation
Ethical/privacy statement
Limitations statement
Industry/proprietary-data explanation
None of these
Other
64.
[G3] For each artifact type, what level of expectation is reasonable for IEEE ITSS venues?
Required when applicable
Recommended but not required
Optional
Not appropriate for most papers
Not sure
Data
Data
Code
Code
Simulation configurations
Simulation configurations
Trained models or model weights
Trained models or model weights
Benchmark scripts
Benchmark scripts
Detailed experimental protocols
Detailed experimental protocols
Ethics/privacy statement
Ethics/privacy statement
Limitations statement
Limitations statement
65.
[G4] What are the main barriers to stronger reproducibility in ITS papers? Select all that apply.
[Multiple]
Proprietary data
Privacy restrictions
Safety/security restrictions
Large storage or compute needs
Commercial software dependencies
Lack of standard benchmarks
Lack of time before submission
Lack of author incentives
Lack of reviewer capacity to check artifacts
Unclear venue expectations
Intellectual property (patent) restrictions on code, data, or algorithms
Other
66.
[G5] How comfortable would you be reviewing reproducibility materials for a paper in your area?
Not comfortable
Slightly comfortable
Moderately comfortable
Very comfortable
Extremely comfortable
Not applicable
67.
[G6] A short reproducibility checklist embedded in the review form would improve review quality without creating excessive burden.
Strongly disagree
Disagree
Neither agree nor disagree
Agree
Strongly agree
Not applicable / insufficient experience
68.
[G7] What should be included in an ITSS reproducibility checklist, especially for mixed-traffic, intelligent vehicle, and automated-driving research?
Recommended length: up to 750 characters. Please do not include manuscript IDs, paper titles, reviewer or editor names, or confidential information from active or unpublished submissions.
69.
[G8] Please identify any reproducibility practices already working well in ITSS venues.
Recommended length: up to 500 characters. Please do not include manuscript IDs, paper titles, reviewer or editor names, or confidential information from active or unpublished submissions.
Reviewer training and reviewer-pool interest
Reviewer training and reviewer-pool interest
*
70.
[H1] How interested are you in the following Reviewer Incubator activities?
Not interested
Slightly interested
Moderately interested
Very interested
Extremely interested
Not applicable
Virtual Next-Gen Reviewer masterclass
Virtual Next-Gen Reviewer masterclass
Short modules on constructive reviewing
Short modules on constructive reviewing
Short modules on reproducibility checks
Short modules on reproducibility checks
Interdisciplinary review rubric training
Interdisciplinary review rubric training
Mentored or shadow-review opportunities
Mentored or shadow-review opportunities
Reviewer certification or completion credential
Reviewer certification or completion credential
Joining an ITSS reviewer database
Joining an ITSS reviewer database
Serving as a mentor for ECR reviewers
Serving as a mentor for ECR reviewers
71.
[H2] If you are an Early Career Researcher (ECR) or PhD student, which support would make you more willing to serve as a reviewer?
[Multiple]
Select Not applicable if you are not a PhD student or early-career researcher.
Clear review template (assessment criteria or review checklist)
Mentor feedback
Shadow-review opportunity
Recognition certificate
Example reviews
Structured reviewer training or workshop
Training on confidentiality and ethics
Training on interdisciplinary assessment
Longer first-review deadline
Co-review policy guidance
Feedback from the editor on the completed review
Guidance on responsible use of AI tools in peer review
Language or academic-writing support for review reports
Not applicable
Other
72.
[H3] What format would you prefer for reviewer training?
[Multiple]
One 90-minute masterclass
Two 60-minute sessions
Self-paced short videos
Written checklist and examples
Live Q&A with editors
Small-group mentoring
Hands-on mock review
Other
73.
[H4] Which certification approach would be most appropriate for the review training program?
This question asks about preferences; any certification would be subject to ITSS approval.
Completion certificate only
Tiered certification based on training and quality of (mock) review
Digital badge
Recognition without certification
No certification
Not sure
74.
[H5] Would you be willing to be contacted separately about reviewer training, reviewer database participation, or future ITSS activities?
Yes
Maybe
No
75.
[H6] Which expertise tags should the ITSS reviewer database include? Select all that apply.
[Multiple]
Application domain
Methods/technical domain
Data type
Simulation/testbed type
Geographical/system context
Human subjects/human factors
Safety/ethics/privacy
Reproducibility/open science
Review languages
Availability/capacity
Career stage
Mentoring interests
Other
76.
[H7] What would make an ITSS reviewer database trustworthy and acceptable to the community?
[Multiple]
Opt-in participation
Ability to update expertise tags
Transparent use policy
Ability to pause invitations
Privacy protection
Editor-only access
Clear conflict-of-interest handling
Recognition for high-quality reviews
Other
77.
[H8] Please suggest one topic that the November 2026 reviewer masterclass (planned in late November) should definitely cover.
Recommended length: up to 300 characters. Please do not include manuscript IDs, paper titles, reviewer or editor names, or confidential information from active or unpublished submissions.
Final feedback and confirmation
Final feedback and confirmation
78.
[F1] In one sentence, what is the most important change IEEE ITSS could make to improve author experience?
Recommended length: up to 300 characters. Please do not include manuscript IDs, paper titles, reviewer or editor names, or confidential information from active or unpublished submissions.
79.
[F2] In one sentence, what is the most important change IEEE ITSS could make to improve reviewer experience?
Recommended length: up to 300 characters. Please do not include manuscript IDs, paper titles, reviewer or editor names, or confidential information from active or unpublished submissions.
80.
[F3] In one sentence, what is the most important change IEEE ITSS could make to improve interdisciplinary and reproducibility review quality?
Recommended length: up to 300 characters. Please do not include manuscript IDs, paper titles, reviewer or editor names, or confidential information from active or unpublished submissions.
*
81.
[F4] May the organizing team quote your open-text comments anonymously in internal reports or presentations?
Yes
No
*
82.
[F5] Please confirm that your open-text answers did not include manuscript IDs, paper titles, reviewer names, editor names, or confidential information from unpublished work.
Confirmed
I may have included confidential details
*
83.
I consent to be contacted about IEEE ITSS reviewer-training or reviewer-pool activities.
Yes, please fill the contact form at the link below:
https://v.wjx.cn/vm/hNUpN6l.aspx
No
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IEEE ITSS Peer Review Experience Survey
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