The continuous generation and evolution of digital learning resources is important for promoting open learning and meeting the personalized needs of learners. In the Web 2.0 era, open and collaborative authoring is becoming a popular method by which to create vast personalized learning resources in open knowledge communities (OKCs). However, the essence of openness of OKCs also gives rise to concerns regarding the knowledge quality and non-orderliness of resource evolution. In this study, we design a resource evolution support system (RESS) called learning cell system (LCS) in one OKC. Two key issues, namely, the intelligent control of content evolution and the dynamic semantic associations between resources, are addressed by combining technologies of semantics, trust evaluation, rule-based reasoning, and association rule mining. One typical case is taken to illustrate the actual evolution process of learning resources assisted by RESS in LCS. The operating effect of this system shows that RESS can control content evolution and effectively build semantic associations among resources. Finally, the academic contribution to the OKCs, implications for educational practice, limitations, and future research plans are presented.