A Preliminary Study of the Aggregation of Micro-Course Learning Resources for Senior Citizens in Grassroots Communities: From the Perspective of Learning Sciences
Abstract
In order to effectively cope with the national strategy of population ageing, the relevant plans of the State Council in the 14th Five-Year Plan require the innovative development of education for the elderly, the integration of learning resources, and the narrowing of the “digital divide” between urban and rural areas. The capacity of grass-roots community resource construction is insufficient. Therefore, we should consider how to achieve high-quality convergence of learning resources for the elderly, so as to effectively revitalize the application ecology of learning resources in grass-roots communities, from the perspective of maximizing utilization, avoiding duplicate construction, and integrating optimization and intensive cost. This paper will analyze the current state of micro-course learning materials for the elderly in grassroots communities, as well as the issues that they face. Based on learning scientific theories, this paper believes that the aggregation of micro-course learning resources for the elderly in grassroots communities should be scientifically and effectively realized. Furthermore, when gathering, we should focus on the elderly in the community and accurately locate their characteristics; propose simplified practical standards for high-quality micro-courses to serve as a guide for the gathering of micro-courses in grass-roots communities; use introduction, transformation, self-build and exchange methods to achieve multi-source aggregation of micro-courses for the elderly. Moreover, we should investigate the practical path of the entire process of aggregation and implementation of micro-course resources for the elderly in grass-roots communities, systematize the management of micro-course resources, build a multi-dimensional resource service system, and form a digital learning community for the elderly from the standpoint of learning scientific theory. Empirical procedures that are repeatable and scalable.
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DOI: http://dx.doi.org/10.3968/12581
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