Given that little is known about the correlations between teachers' mindset and their pedagogical strategies, in this article, we explore Chinese and Finnish teachers' mindsets and their pedagogical strategies from the perspective of praise and adaptive teaching. This study was conducted in two Chinese schools (N = 50) and one Finnish school (N = 77) with instruments of the mindset inventory, praise scale and adaptive learning scale (PALS). The results reveal that Chinese and Finnish teachers' preferences for pedagogical strategies differ even though they hold the same growth mindset, which confirms that teachers do not necessarily utilize growth mindset messages even though they endorse a growth mindset. While Finnish teachers prefer pedagogical methods in accordance with growth mindset pedagogy, Chinese teachers seem to apply mixed strategies reflecting both growth and fixed mindsets. The results imply differences within Finnish and Chinese teacher education regarding the internalization of the principles of growth mindset pedagogy.
Analyzing the potential for green development and its influencing factors is an important part of the energy savings and low-carbon economic growth of China’s iron and steel industry (ISI). Many studies have concentrated on improving the ISI’s energy use and pollution control efficiencies, analyzing the influencing factors from the perspectives of regions and firms. However, no study has focused on measuring the provincial green development efficiency (GDE) in the ISI. The selected driving forces of the GDE do not consider regional or industrial characteristics. In this study, based on provincial panel data for 2006–2015 in China, the GDE of the Chinese ISI was evaluated using the super-slack-based measure (super-SBM) model. China’s 28 provinces were divided into different groups through cluster analysis. Then, a Tobit model was constructed to explore the factors influencing the GDE. The key results show the following: (1) The GDE values decline, fluctuating from 0.628 in 2006 to 0.571 in 2015, decreasing by 1.1% annually. Among the provinces, wide differences exist in the GDE values for the ISI, with the highest average GDE value being observed in Beijing and the lowest in Shanxi. (2) The provinces with high R&D expenditure inputs and high GDE values are mostly located in the eastern region, while the provinces with low R&D expenditure inputs and low GDE values are located in the central and western regions. (3) The export demand, property structure, and capital investment have significant positive effects on the ISI’s GDE in the eastern and western regions, while the energy consumption structure and industry scale have negative impacts on the improvement of the GDE in the central region. (4) Specific policy recommendations for sustainable development in the ISI mainly include further strengthening investment in R&D, expanding exports, adjusting energy consumption structures, and deepening the reform of stated-own enterprises.
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