Help · FAQ
Frequently Asked Questions
Answers to common questions about anonymity, submissions, and how to use Wondering Staffroom to compare international teacher salary packages.
About Wondering Staffroom
A quick overview of what the platform is (and what it is not).
- What is Wondering Staffroom?
- Wondering Staffroom is a community-driven platform where international educators can anonymously share and compare salary and benefits packages across international schools worldwide.
- Is Wondering Staffroom affiliated with schools or recruiters?
- No. Wondering Staffroom is independent and is not owned by a recruiter, agency, or school group.
- Is this a school review or ranking site?
- No. The goal is salary and package transparency, not employer ratings. Data is presented to help users compare ranges and typical benefits.
Anonymity and privacy
How anonymity works and what the site does (and does not) collect.
- Is Wondering Staffroom really anonymous?
- Yes. Salary submissions are anonymous and are not linked to names, emails, or user accounts. The site is designed to avoid collecting personal identifiers as part of the submission process.
- Do I need an account to browse salary data?
- No. You can browse the dataset without creating an account.
- Can I request my data or an entry to be removed?
- Yes. If you believe an entry should be reviewed or removed, you can contact the site and request a review.
Submitting a salary package
How to contribute and what kind of entries are most helpful.
- How do I submit an international teaching salary package?
- Use the Submit page and complete as much detail as you can. You can submit current packages, past packages, or job offers you’ve received.
- Can I submit more than one package?
- Yes. Multiple entries (past, present, and offers) help build a richer dataset and make comparisons more useful.
- What should I include to make my submission useful?
- Benefits matter as much as salary. Housing, flights, tuition, healthcare, bonuses, and tax situation can significantly change the value of a package.
Ready to contribute? Submit a package.
Accuracy and how to interpret the data
How reliable the data is and how to use it responsibly.
- Is the data verified?
- No — submissions are community-provided. The goal is transparency and pattern spotting, not perfect auditing. Use the dataset to compare ranges and trends rather than relying on a single entry.
- How do you reduce fake or misleading entries?
- The dataset can be reviewed for obvious outliers and patterns. However, the site cannot guarantee accuracy, so users should treat the data as indicative rather than definitive.
- What’s the best way to compare two offers?
- Compare total package value, not just base salary. Consider housing, insurance, tax, tuition, flights, location costs, and contract terms. Two equal salaries can produce very different real-world outcomes.
Want to explore patterns? Browse the dataset.
Downloads and reuse
Questions about exporting data and using it elsewhere.
- Can I download the salary dataset?
- Not currently. The priority is protecting anonymity, preventing misuse, and keeping the focus on community benefit. This may change as the platform evolves.
- Can I use the data for research or a blog post?
- If you want to reference aggregated insights, please contact the site first so we can help ensure context, anonymity, and accuracy are handled responsibly.
Help and support
Fixes, suggestions, and getting in touch.
- I found a mistake or have a suggestion — what should I do?
- Please contact the site with details. Suggestions and corrections help improve the quality of the dataset and the usefulness of the platform.
- I want a specific page or country added — can I request it?
- Yes. If there’s a country or comparison you’d like to see, send a suggestion via the contact page.
Next steps
Useful next steps and related pages.
About the project
Why Wondering Staffroom exists and how anonymity is protected.
Browse salaries
Explore packages by country, role, benefits and more.
Submit a salary package
Add an anonymous entry to strengthen the dataset for everyone.
Contact
Report an issue, request a review/removal, or suggest improvements.
