OER can help institutions provide higher education to rapidly increasing numbers of students and lifelong learners. Traditional colleges and universities, with their experience and reputation, are in a good position to further develop online teaching and testing, learning communities and certification. Those that produce high-quality knowledge, teaching, and students have little to fear, and much to gain, from OER. This movement has challenged the traditional value chain by employing new methods to deliver high-quality educational content. In this new paradigm for educational content consumption, OER are expected to play a decisive role for learning. Thus, OER are becoming a popular topic for new research techniques, and significant challenges meet to be addressed.

This special issue will focus on innovative experiences using OCW/OER to demonstrate the theory and practice of electrical and computer engineering, presenting both scientific and educational studies using OER-based novel educational research techniques such as Social Web, Semantic Web, Linked Data, and the like that are within the scope of interest of the IEEE TRANSACTION ON EDUCATION. The target audience will be educators and researchers across the field of electrical and computer engineering, as well as practitioners wanting an insight into the future of OCW and the overall OER value chain.

The IEEE TRANSACTION ON EDUCATION solicits original and unpublished contributions for a Special Issue that must clearly OCW/OER and one or more of the following topic areas:

studies of creativity in the use of OCW/OER in teaching and learning for the future-in particular those that combine the theory and practice of electrical and computer engineering;
prospective visions for OCW/OER and technology-based teaching and learning;
content modeling and metadata for next generation of OCW/OER;
case studies of implementing Mobile technologies applications, Social Web, Semantic Web or Linked Data in OCW/OER traditional approaches;
improving traditional OCW/OER approaches with the help of ethical, educational, and economic aspects of Linked Data;
recommender systems for OCW/OER supported by Social or Semantic Web;
quality and evaluation metrics for OCW/OER