Measures during data collection

• Purpose of the quality control program
  • Ensured data validity and international comparability across countries/territories
  • Monitored adherence to TALIS technical standards and survey procedures
  • Documented survey implementation quality and identified issues
  • Supported consistent administration across languages, countries, and modes (online/paper)
• Core components of the program
  • International Quality Observation Programme (IQOs)
    • Independent observers monitored survey administration
    • Activities included
      • Visiting national centres and interviewing NPMs
      • Reviewing translated manuals against international versions
      • Interviewing around 20 school/ECEC co-ordinators per component
    • Collected data on preparation, communication, adherence, and challenges
  • Additional Quality Control Questions
    • Collected respondent feedback on selection procedures, time, confidentiality, and issues
    • Administered to around 20% of the subsample
    • Findings
      • High response rates (70–100%)
      • Few issues, lack of time most common
  • National Quality Observation Programmes
    • School/ECEC visits and observations
    • Conducted by national centres during field trial and main survey
    • Focused on administration, communication, and procedural implementation
    • Common challenges
      • Length of questionnaires
      • Perceived workload for schools
      • Limited understanding of TALIS in some cases
  • Survey Activities Questionnaire (SAQ)
    • Post-survey reporting by National Project Managers
    • Online questionnaire (71 questions, 10 sections)
    • Covered sampling, recruitment, instruments, translation, administration, technical issues
    • Used to inform improvements for future survey cycles

Measures during data processing and cleaning

• National centers were responsible for ensuring that all collected data were complete, accurate, and correctly documented before submission to the International Study Centre (ISC).
• National adaptations to survey instruments had to be fully documented in codebooks and aligned with the international data structure and coding schemes to maintain cross-country comparability.
• Standardized software tools (e.g. WinW3S, Study Expert and Data Management Expert) were used to support sampling, track participation, capture data and validate entries.
• Data from paper questionnaires had to be entered exactly as recorded by respondents (“as is”), without interpretation or correction during the data-entry stage.
• Automated validation procedures identified problems such as invalid identification numbers, inconsistent records and out-of-range values during data entry.
• National centers were required to conduct double data entry for a sample of questionnaires (at least 5% or a minimum of 100 cases) to verify the reliability of data entry.
• A data-entry error rate above 1% triggered further review and potential re-entry of the data to ensure data quality.
• Before submission, national centers performed mandatory verification checks to identify duplicate identifiers, invalid codes and missing information, and resolved issues by consulting the original questionnaires.
• After submission, the ISC conducted further quality control through structured processes including data integration, structural checks, identification and linkage cleaning, and automated consistency checks.
• Logical inconsistencies, implausible responses and conflicting answers were corrected or recoded according to standardized cleaning rules applied consistently across all participating countries.
• All data corrections and cleaning actions were documented and reviewed in collaboration with national centers before finalization of the international datasets.
• Multiple interim data versions were released to national centers and the OECD Secretariat to allow additional validation and plausibility checks before producing the final international database. 
• Key confidentiality measures
  • Direct personal identifiers (such as names in tracking forms) were removed or redacted before data were submitted for international processing.
  • Respondent identifiers used during data collection were replaced with randomly generated IDs to prevent identification of individuals. 
  • Sensitive or identifying variables and some quality control variables were removed or suppressed in public datasets. 
  • Two versions of the international database were produced: a restricted-use file for authorized users under confidentiality agreements and a public-use file with reduced detail to minimize re-identification risks. 
  • Disclosure avoidance measures such as variable suppression, aggregation, and ID scrambling were applied in accordance with OECD data protection rules and relevant national legislation.