Mengyao Cheng

China's aging population and the emergence of smart elderly care present significant pedagogical challenges for gerontology education. Current experimental teaching approaches in this recently established undergraduate field frequently misalign with industry requirements. This research introduces an innovative "industry-education integration and AI technology dual-driven" teaching model. By examining pedagogical limitations and industry developments, we develop a "three-tier progressive, four-dimensional integration" framework for experimental curriculum reform. Our model seeks to connect theoretical learning with practical applications, developing students' competencies for technology-enhanced elderly care environments.

Using data from the 2000, 2010, and 2020 National Population Census of China, this study uncovers evolving trends in the experiences of children in family structures reshaped by China's massive internal migration. We develop a new framework to examine family structures from the census data, which facilitates a detailed exploration of family splits as a result of migration. Our results show a significant surge in the proportion of children in migrant families and the trend of children on the move. While the number of left‐behind children far exceeded that of migrant children in 2000, the picture became the opposite in 2020, signifying an enhanced capacity and inclination for migrant parents to bring their children to migration destinations. This shift has also engendered a more heterogeneous population of children in migrant families. Notably, a subgroup warranting particular attention is that of “left‐behind child migrants,” those moving to proximate towns or cities without both parents. This emergence blurs the traditional urban–rural dichotomies and underscores the intricacies of a family split within the migrant population. Finally, we reflect on the significant role of educational aspirations and obstacles that influence these migratory patterns.

Most previous studies of return migration have defined return migration as a return to the place of birth (or village of origin). In this paper, we reconceptualize return migrants as consisting of two groups: those returning to their place of birth (“local returnees”) and those returning to a nearby town, county, or city (“regional returnees”). Using a nationally representative sample from the 2014 China Labor Dynamics Survey, we carry out a systematic comparison and analysis of these two groups of return migrants, along with migrants at their destination and non-migrants at their origin. Our results challenge previous views of the negative socioeconomic selectivity of return migration. Both local returnees and regional returnees play an important role in non-farm economic activities. More importantly, we find that regional returnees have more favorable outcomes than local returnees in terms of income and economic activities. As China makes significant progress in upgrading its transportation infrastructure, and with the growing availability of digital technology for businesses, the proportion of regional returnees should grow over time. We argue that this new form of return migration represents a promising pattern of development and urbanization in China and deserves more attention from scholars and policymakers.