STEM education increasingly relies on technology-enhanced environments that utilize data-driven strategies, digital tools, and adaptable learning models. To support the evaluation of contemporary STEM teaching methods, this study proposes a multi-criteria analytical framework based on expert assessment. Semi-structured interviews were conducted with 41 experienced teachers from Bulgarian schools (N = 41), who evaluated six key indicators (m = 6) of STEM integration: Effectiveness, Engagement, Applicability, Flexibility, Validity, and Accessibility. The qualitative data were transformed into numerical values and analyzed using the Target Parameter Ranking method. The degree of expert agreement was assessed through the Morris–Kendall coefficient, yielding a statistically significant moderate agreement (wk = 0.137; χ2 = 28.085, df = 5, p = 3.50 × 10−5 (p < 0.001)). The results indicate that Engagement (Wj = 0.206), Flexibility (Wj = 0.188), and Effectiveness (Wj = 0.186) are the most highly weighted criteria, reflecting teachers’ prioritization of active participation, learning outcomes, and adaptability in technology-rich STEM environments. In comparison, Applicability and Accessibility show higher variability, highlighting their dependence on contextual factors such as infrastructure and resource availability. The proposed framework provides a structured, data-driven basis for evaluating and refining STEM teaching practices and can be integrated into educational decision-support systems.
Trichkova-Kashamova et al. (Mon,) studied this question.