This study evaluates the effectiveness of human resources (HR) practices on teaching and learning outcomes in primary education. The research was guided by four research questions and two research hypotheses. The study utilized a survey design via Google Forms for efficient data collection on human resources practices’ effectiveness in primary education. The questionnaire, validated by experts, garnered 60 responses within a month. Data analysis in Statistical Package for the Social Sciences (SPSS) included descriptive statistics and analysis of variance (ANOVA) techniques, adhering to ethical standards. The findings highlight the importance of HR practices that accommodate diversity, support inclusivity, and foster a sense of belonging for all students. Challenges in implementing inclusive HR practices are also identified, emphasizing the need for ongoing efforts to promote inclusivity and equity in primary education. The study concludes by advocating for the development and implementation of effective HR strategies to enhance teaching and learning outcomes in primary education.

Corporate finance courses are increasingly adopting data-driven teaching methods. Modern corporate finance courses are focusing more on students' career development. Through simulation practice and career planning guidance, students are better prepared to face challenges in the workplace after graduation. Students need to learn how to utilize data analysis tools and techniques to extract useful information from large datasets and make more accurate decisions. Data-driven teaching is a significant innovation in current curriculum reforms. In recent years, with the development of technology and the emergence of financial innovation, corporate finance courses have been undergoing continuous changes and innovations. These courses have started to emphasize emerging areas such as digital finance, blockchain technology, and sustainable development. Taking the example of corporate finance, this paper integrates the demands of skill development in the era of digital finance, focusing on aspects like teaching methods, reform methodologies, practical experiments, feedback mechanisms, and data analysis.

With the gradual penetration of artificial intelligence technology into various fields of society, it has brought many deeper and broader impacts, gradually improving the status of artificial intelligence in talent cultivation and education to adapt to the current development of social intelligence technology. Therefore, as the core course of artificial intelligence education in universities, machine learning needs to deeply analyze and explore the main factors that affect its development, in order to better mobilize students' learning enthusiasm and teachers' educational innovation, enhance the teaching and learning effectiveness of the course, and maximize the exploration of the educational achievements of artificial intelligence.

In the context of big data, the teaching of financial accounting for vocational undergraduate students needs to be continuously optimized and innovated. This article provides a brief analysis of the current situation of financial accounting teaching for vocational undergraduate students. It also analyzes the phenomena of outdated teaching concepts, outdated teaching content, and unreasonable teaching objectives in the current teaching of financial accounting for vocational undergraduate students. It proposes the idea of innovating teaching concepts in current teaching work, clarifying teaching objectives, integrating flipped classroom reform teaching mode, and introducing project-based teaching method to improve teaching efficiency, so as to achieve more efficient teaching guidance for students.

Professional identity among faculty members in private higher education institutions plays a vital role in shaping the quality and sustainability of these institutions. This research aims to investigate the factors influencing the professional identity of teachers in Chengdu's private higher education institutions. The study employs a theoretical framework centered on "identification" with behavior intention, behavior attitude, and sense of belonging as fundamental dimensions. Data were collected through questionnaire surveys and analyzed using SPSS 23.0. The study hypothesizes that behavior intention, behavior attitude, and sense of belonging have a significant positive impact on professional identity among faculty members. Additionally, behavior attitude, subjective norms, and perceived behavioral control are expected to have a significant positive influence on behavior intention, and subjective norms and perceived usefulness may positively affect sense of belonging. The results are expected to provide valuable insights for enhancing the professional satisfaction and educational quality of faculty in private higher education institutions.

This paper discusses the construction strategy of innovation and entrepreneurship education path for college students under the background of digital economy. Firstly, this paper analyzes the characteristics of digital economy and its influence on higher education, and then puts forward four core construction paths for college students' innovation and entrepreneurship education: integrating digital skills and knowledge, promoting practice and innovative thinking, interdisciplinary integration and collaborative learning, and linking industry and academia. Each path discusses the specific implementation and expected effect in detail. The purpose of this study is to provide higher education institutions with effective methods and strategies to cultivate students with innovative spirit and entrepreneurial ability in the era of digital economy.