Research related to the “teacher characteristics” dimension of teacher quality has proven inconclusive and weakly related to student success, and addressing the teaching contexts may be crucial for furthering this line of inquiry. International large-scale assessments are well positioned to undertake such questions due to their systematic sampling of students, schools, and education systems. However, researchers are frequently prohibited from answering such questions due to measurement invariance related issues. This study uses the traditional multiple group confirmatory factor analysis (MGCFA) and an alignment optimization method to examine measurement invariance in several constructs from the teacher questionnaires in the Trends in International Mathematics and Science Study (TIMSS) 2015 across 46 education systems. Constructs included mathematics teacher’s Job satisfaction, School emphasis on academic success, School condition and resources, Safe and orderly school, and teacher’s Self-efficacy. The MGCFA results show that just three constructs achieve invariance at the metric level. However, an alignment optimization method is applied, and results show that all five constructs fall within the threshold of acceptable measurement non-invariance. This study therefore presents an argument that they can be validly compared across education systems, and a subsequent comparison of latent factor means compares differences across the groups. Future research may utilize the estimated factor means from the aligned models in order to further investigate the role of teacher characteristics and contexts in student outcomes.

与教师素质的“教师特征”维度相关的研究已被证明是结论性的，与学生的成功关系不大，解决教学环境对于推进这一探究线可能至关重要。由于对学生，学校和教育系统进行了系统抽样，因此国际大规模评估很容易回答此类问题。但是，由于与测量不变性相关的问题，经常禁止研究人员回答此类问题。这项研究使用传统的多组验证性因子分析（MGCFA）和比对优化方法，通过46个教育系统中的《国际数学和科学研究趋势（TIMSS）2015》中的教师问卷调查了几种构造的度量不变性。工作满意度，学校注重学业成功，学校条件和资源，安全有序的学校以及教师的自我效能感。MGCFA结果表明，只有三个构造在度量水平上实现了不变性。然而，应用了比对优化方法，结果表明所有五个构建体均在可接受的测量不变性的阈值之内。因此，本研究提出了一个论点，即可以在各个教育系统之间对它们进行有效地比较，随后对潜在因素的比较意味着可以比较各组之间的差异。未来的研究可能会使用对齐模型中的估计因子平均值，以进一步调查教师特征和情境在学生成绩中的作用。