Large-scale international assessments increasingly shape how teaching quality, professional development, and teacher well-being are evaluated at the system level. International studies such as TIMSS provide standardized teacher questionnaire data that allow for cross-national comparison and monitoring over time.

Within TIMSS, teaching practices, professional development, and teacher well-being are operationalized through self-reported items and composite indicators, which function as indicator-based measures of complex professional phenomena. These indicators offer structured and comparable representations of teaching conditions, while at the same time raising important questions regarding construct alignment, internal coherence, and interpretive validity. Understanding whether such indicators form coherent measurement structures, and how they combine at the level of individual teachers, is therefore essential for the valid interpretation of findings derived from large-scale assessment data.

This study contributes to research in assessment, evaluation, and measurement by examining the coherence and interpretive structure of TIMSS teacher indicators related to STEM teaching. Using data from the TIMSS 2019 and TIMSS 2023 teacher context questionnaires, the study focuses on middle school mathematics and science teachers in Romania. Romania provides a relevant case for this analysis, as TIMSS indicators point to persistent issues related to teacher workload, participation in professional development, and workforce ageing—topics frequently referenced in system-level evaluation and policy discussions across European education systems.

Previous research using TIMSS teacher data has examined relationships among teacher-reported constructs such as job satisfaction, working conditions, and instructional context, providing evidence that these indicators capture related but distinct dimensions of teachers’ professional experiences. For example, Toropova et al. (2021) found that teacher job satisfaction is systematically associated with perceived working conditions, while not reducible to a single underlying construct, highlighting partial coherence among measured indicators. Similarly, Eriksson et al. (2018) questioned the extent to which TIMSS instructional practice items can be interpreted as stable measures, emphasizing the need for caution when using such indicators across cycles.

Other studies have adopted person-centred approaches to TIMSS data in order to examine heterogeneity underlying aggregate measures. Cheng and Hsu (2017) used latent cluster analysis to identify distinct profiles of instructional practices, demonstrating that teachers with similar average scores may nonetheless belong to qualitatively different patterns of reported practice. Likewise, Teig and Nilsen (2022) applied latent class approaches to show that instructional quality indicators cluster into distinct profiles, underscoring the limitations of system-level averages for representing teaching conditions.

Building on this body of research, the present study integrates indicator coherence analysis and profile-based analysis within a single measurement-oriented framework. The overarching objective is to examine what TIMSS teacher indicators can—and cannot—tell us about STEM teaching conditions over time, and to reflect on the implications of using such indicators for system-level interpretation and evaluation

The study employs a quantitative, descriptive, and comparative research design, using data from the TIMSS 2019 and TIMSS 2023 teacher context questionnaires. The analytical sample includes eighth-grade mathematics and science teachers in Romania. All analyses apply TIMSS sampling weights and account for the complex sample design to ensure nationally representative estimates and appropriate measures of uncertainty. The analysis focuses on teacher-reported indicators related to job satisfaction and sense of professional purpose, perceived workload and time constraints, participation in professional development activities, and selected instructional practice indicators. The study is guided by the following research questions: RQ1. To what extent do TIMSS teacher indicators related to STEM teaching practices, professional development, and well-being form a coherent measurement structure? RQ2. How do key TIMSS teacher indicators combine to form distinct measurement-based profiles of STEM teachers? RQ3. What are the implications of indicator coherence and profile heterogeneity for interpreting and using TIMSS teacher data in system-level evaluation of STEM teaching conditions? Indicator coherence is examined using weighted correlations and group comparisons to explore relationships among key teacher indicators. This analysis assesses whether indicators behave as parts of a coherent measurement structure, providing insight into construct alignment and potential tensions between measured dimensions. Teacher profile analysis is conducted to illustrate how multiple indicators combine at the individual level. Teachers are grouped based on selected indicators (e.g., job satisfaction and workload) to identify distinct measurement-based profiles. The distribution and characteristics of these profiles are examined descriptively, with particular attention to how high levels of professional satisfaction may coexist with differing levels of workload and professional development participation. Comparisons between the 2019 and 2023 cycles are used to examine the stability of indicator relationships and profile distributions over time. Given the repeated cross-sectional design of TIMSS, the analysis does not aim to establish causal relationships or individual change, but rather to assess the interpretability of measured patterns and differences at the system level.

Preliminary analyses indicate that TIMSS teacher indicators related to STEM teaching conditions exhibit moderate internal coherence. For example, job satisfaction is consistently associated with perceived workload and participation in professional development, suggesting that these indicators capture related but distinct aspects of teachers’ professional experiences rather than a single unified construct. The profile-based analysis further reveals heterogeneity among STEM teachers that is not visible in aggregate statistics. A substantial proportion of teachers report high professional satisfaction despite experiencing high workload and limited professional development participation, while other profiles combine lower satisfaction with high strain or more favorable conditions. These findings highlight the complexity of interpreting high average satisfaction scores and caution against simplistic evaluative conclusions based on single indicators. Comparisons between TIMSS 2019 and 2023 suggest that both indicator relationships and profile distributions are largely stable over time, with only modest shifts. This stability supports the use of TIMSS indicators for system monitoring, while also underscoring the importance of cautious interpretation, particularly in light of contextual disruptions such as the COVID-19 pandemic. From an assessment and evaluation perspective, the findings demonstrate that TIMSS teacher indicators are valuable for identifying broad patterns and tensions in STEM teaching conditions, but that their interpretive power depends on examining relationships between indicators and acknowledging underlying heterogeneity. The study underscores the need to treat large-scale teacher questionnaire data as partial and structured representations of professional reality, informing evaluation while explicitly recognizing measurement limits.

Cheng, Y. C., & Hsu, H. Y. (2017). Profiles of instructional practices in mathematics classrooms: A latent class analysis using TIMSS data. Educational Research and Evaluation, 23(3–4), 123–145. Eriksson, K., Helenius, O., & Ryve, A. (2018). Using TIMSS items to study instructional practices: Measurement issues and implications. Studies in Educational Evaluation, 59, 104–114. Teig, N., & Nilsen, T. (2022). Instructional quality profiles and student achievement: A latent class approach using TIMSS data. Learning and Instruction, 78, 101523. Toropova, A., Myrberg, E., & Johansson, S. (2021). Teacher job satisfaction: The importance of school working conditions and teacher characteristics. Educational Review, 73(1), 71–97. TIMSS. (2019). Encyclopedia: Education Policy and Curriculum in Mathematics and Science, Romania. https://timssandpirls.bc.edu/timss2019/encyclopedia/romania.html TIMSS. (2019). Assessment Frameworks. https://timssandpirls.bc.edu/timss2019/frameworks/