This article addresses the pressing issue of training and mediation for conflict resolution among employees within a corporate setting. Employing a methodology that includes literature analysis, comparative studies, and surveys, we explore various strategies and their effectiveness in mitigating workplace conflicts. Through a comprehensive comparison with metrics and conclusions from other scholarly works, we provide a nuanced understanding of the current landscape of conflict resolution practices. As a result of our research, we implemented a tailored training program focused on conflict resolution for employees within a mobile company, alongside the development of a competency framework designed to enhance conflict resolution skills. This framework comprises five integral components: emotional, operational, motivational, behavioral, and regulatory. Our findings suggest that training in each of these competencies is essential for fostering a healthy workplace environment and must be integrated into organizational practices. The importance of this initiative cannot be overstated; effective conflict resolution skills are not only vital for individual employee wellbeing but also crucial for the overall efficiency and productivity of the organization. By investing in these competencies, companies can reduce turnover, enhance team cohesion, and create a more positive and collaborative workplace culture.

The curriculum reform in 2022 puts forward new requirements for the professional literacy cultivation of primary science teachers, and the cultivation of primary science classroom teaching skills is an important aspect of the professional literacy cultivation of science education teachers, mainly including subject knowledge and teaching theory, teaching design and preparation, teaching methods and strategies. On the basis of following the principle of combining theory and practice, diversified teaching and student subjectivity, the training strategies of group cooperative learning, observing the teaching process of excellent teachers, and strengthening the effect of micro-grid teaching are proposed, and in addition to the expected evaluation, it provides a certain theoretical basis for the cultivation of normal students in science education.

This study aims to explore the relationship between classroom anxiety and self-efficacy among Chinese Korean language learners and the impact of these variables on learning outcomes. Utilizing a quantitative research approach, the study conducted a questionnaire survey with 300 learners to assess their levels of Korean language learning classroom anxiety and self-efficacy. The questionnaire comprised two parts: one for assessing learning anxiety and the other for self-efficacy. Data were analyzed using descriptive statistical analysis, Pearson correlation coefficients, and multiple regression analysis. The results indicate a significant negative correlation between classroom anxiety and self-efficacy. That is, higher levels of classroom anxiety in Korean language learners correspond to lower levels of self-efficacy. Additionally, self-efficacy played a partial mediating role between classroom anxiety and learning outcomes. The study also found that teaching strategies offering positive feedback and encouragement can effectively reduce learners’ classroom anxiety and enhance their self-efficacy, thereby improving learning outcomes. This research is significant for understanding the psychological characteristics of Chinese Korean language learners and their impact on the learning process. The findings underscore the need to focus on learners’ psychological states in language teaching and provide strategies for teachers on how to improve teaching effectiveness by alleviating classroom anxiety and enhancing self-efficacy.

Scientific inquiry activities are the process of children finding, analyzing and solving problems. Children's real inquiry begins with the search for answers to questions, which is actually the process of seeking answers to the questions they are interested in with direct perception, personal experience and practical operation. At the same time, in the process of children's SI, teachers should effectively use the interactive strategies of grasping the generation of questions, using questions to promote inquiry and using questions to revitalize inquiry, so as to support and promote children's in-depth learning and inquiry.

The major goal of decisions made by a business organization is to enhance business performance. These days, owners, managers and other stakeholders are seeking for opportunities of modelling and automating decisions by analysing the most recent data with the help of artificial intelligence (AI). This study outlines a simple theoretical model framework using internal and external information on current and potential clients and performing calculations followed by immediate updating of contracting probabilities after each sales attempt. This can help increase sales efficiency, revenues, and profits in an easily programmable way and serve as a basis for focusing on the most promising deals customising personal offers of best-selling products for each potential client. The search for new customers is supported by the continuous and systematic collection and analysis of external and internal statistical data, organising them into a unified database, and using a decision support model based on it. As an illustration, the paper presents a fictitious model setup and simulations for an insurance company considering different regions, age groups and genders of clients when analysing probabilities of contracting, average sales and profits per contract. The elements of the model, however, can be generalised or adjusted to any sector. Results show that dynamic targeting strategies based on model calculations and most current information outperform static or non-targeted actions. The process from data to decision-making to improve business performance and the decision itself can be easily algorithmised. The feedback of the results into the model carries the potential for automated self-learning and self-correction. The proposed framework can serve as a basis for a self-sustaining artificial business intelligence system.