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The purpose of this paper is to propose a design of online-merge-offline (OMO) classroom for open education with design principles related to practical issues of teachers’ teaching, students’ learning and schools’ management.

Three stages were covered: drafted an OMO classroom framework, built a sample classroom and explored end-users’ experience. First, authors searched for and reviewed previous studies and related cases to draft an OMO framework. Second, a classroom, consisted of wireless devices, cloud-based services, Internet of Things terminals, ergonomics furniture, and comprehensive data management and analysis services, was built in Shanghai Open University. Third, invited 11 students’, 18 teachers’ and 9 school managers’ perspectives were collected and analysed by surveys and interviews.

All student participants responded positively in terms of learning experience in the classroom. They not only engaged in classroom activities such, but also accessed needed learning materials and interacted with teachers and peers anytime anywhere via mobile devices. Similarly, most teachers (90 per cent) made positive responses because of flexibility of teaching strategies and learning activities and expressed willingness to use the classroom in the future (94.4 per cent). In addition, more than 78 per cent of managers positively commented on the design of classroom, interaction effects and effective management. Visualised data allowed them to timely monitor status of facilities, comprehensively understand users’ behaviour and issues, make necessary decision with scientific evidence.

The framework and classroom not only provide teachers, students, school managers and researcher with a better understanding of innovative open education, but also indicate the key role of objective-oriented and data-driven issues for further work.

To meet needs of teachers, students, managers and researchers in today’s open education, an OMO classroom was built in Shanghai Open University based on the proposed Objective-Oriented Pedagogy-Space-Technology (OPST) framework. The framework provides readers (especially teachers and administrators of open-education institutes, staff of information centres and ed-tech researchers) with a better understanding of innovative instruction and effective management, and the originally designed classroom can be a practical and illuminating example.

With the continuous increase of users, resources and tags, social tagging systems gradually present the characteristics of “big data” such as large number, fast growth, complexity and unreliable quality, which greatly increases the complexity of recommendation. The contradiction between the efficiency and effectiveness of recommendation service in social tagging is increasingly becoming prominent. The purpose of this study is to incorporate topic optimization into collaborative filtering to enhance both the effectiveness and the efficiency of personalized recommendations for social tagging.

Combining the idea of optimization before service, this paper presents an approach that incorporates topic optimization into collaborative recommendations for social tagging. In the proposed approach, the recommendation process is divided into two phases of offline topic optimization and online recommendation service to achieve high-quality and efficient personalized recommendation services. In the offline phase, the tags' topic model is constructed and then used to optimize the latent preference of users and the latent affiliation of resources on topics.

Experimental evaluation shows that the proposed approach improves both precision and recall of recommendations, as well as enhances the efficiency of online recommendations compared with the three baseline approaches. The proposed topic optimization–incorporated collaborative recommendation approach can achieve the improvement of both effectiveness and efficiency for the recommendation in social tagging.

With the support of the proposed approach, personalized recommendation in social tagging with high quality and efficiency can be achieved.