The modern classroom is becoming increasingly diverse, with many countries seeking to develop teacher self-efficacy in multicultural classrooms (TSMC) to effectively teach diverse students by offering professional development in multicultural education (PDME). Using the Teaching and Learning International Survey 2018, we examine whether the teachers’ experience in PDME improves TSMC, as well as whether TSMC mediates the relationship between PDME and teachers’ perceptions of school climate in secondary schools in the United States and South Korea. We find a significant positive relationship between PDME and TSMC and that TSMC plays a mediating role between PDME and school climate. The findings suggest that PDME not only plays a key role in enhancing TSMC but also promotes a positive school climate.

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With the development of big data and deep learning technology, big data and deep learning technology have also been applied to the marketing field, which was a part of business administration. Customer churn management is one of the most important areas of marketing. In this paper, we proposed a method to prevent customer churn and increase purchase conversion rate by issuing customized discount coupons to customers with high churn rate based on big data in real time. In this paper, we proposed a method to prevent customer cancellation and increase purchase conversion rate by issuing customized discount coupons to customers with high cancellation rates in real time based on big data. After segmenting customer segments with two-dimensional segment analysis, a real-time churn rate estimation model based on clickstream data was generated for each segment. After that, we issued customized coupons to our customers. Finally, we tested the conversion rate and sales growth. A two-dimensional cluster analysis-based churn rate estimation combined with a recommendation system was found to be significantly more useful than the respective simple models. Using this proposed model, it is possible to increase sales by automatically estimating the customer’s cancellation probability and shopping propensity without the burden of marketing costs in the online shopping mall.

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