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The assessment of a country's education quality lies in the productivity level of public education in relation to the country's development through education. Generally, the government conscientiously provides education to the citizens by providing sufficient resources to build human capital development. The study reveals Chinese government funds the education expenditures of all 31 provinces, including the municipalities. The result indicates that each year China government budgets more money for education. The correlation analysis proves that there are (0.9311), i.e., 93% of total expenditure (TE) on education from 1992 to 2017. This implies seriousness in fostering sustainability in investing in education across the country by China's leadership. In addition, government appropriation expenditure (GAE) and public expenditure (PE) are significantly and strongly correlated at 0.9990 (99.9%) and 0.9983 (99.8%), respectively. The summary of returns to education was qualitatively reviewed in tabular form to highlight the phases and progress which China's education has recorded. Though the literature buttresses the gradual progress to education returns, remarkable achievements have been made in the present administration in his plans on education. Besides, the study highlighted other possible means for education expenditure and funding, such as research, tuition, donations from organizations and agencies, tax revenues.

Objectives:Machine Learning (ML) and Artificial Intelligence (AI) remain crucial in education research and pedagogical development. The study provides an overview of ML and AI in education and research.Methods:In order to explore the field of ML and AI, a bibliometric approach was employed to extract and analyze data from the Scopus database. Bibliometrics analysis tools, VOS Viewer, Bibliometrics, and R packages were used to analyze the retrieved data.Results:A total of 1138 documents retrieved were written by 2800 authors, and published in 635 journals from 2000 to 2022, with average citations per document of 5.984 from 62 countries.Conclusion:The study identified an interesting gap that the previously published articles did not address: the implications of ML and AI in classroom learning activities and other pedagogical-related programmes.