Networking is a key skill in professional careers, supporting the individual’s growth and learning. However, little is known about how professionals intentionally manage the connections in their personal networks and which factors influence their decisions in connecting with others for the purpose of learning. In this article, we present a model of personal professional networking for creating a personal learning network, based on an investigation through a literature study, semi-structured interviews and a survey.

Internationalisation has been a key theme in higher education (HE) for decades. Multiple initiatives across the world have contributed to creating offerings of high-quality online education, with collaborations across national borders. Two of the concepts that have proved to be influential are Virtual Mobility (VM) and Open Education (OE). Virtual mobility refers to study activities that students enrolled in HE in one country undertake online in other countries without physically moving. Such activities are certified and mutually acknowledged by participating institutions. Open education covers global initiatives increasing access to free online quality education, without or with alternative forms of certification. The research presented in this article identifies the learner skills and competences that are supported by Open Virtual Mobility (OpenVM), a new trend in online education that builds upon these two concepts. A group concept mapping study based on the contributions of experts in both VM and OE resulted in defining seven learner skills and competence areas including: intercultural skills and attitudes; networked learning; active self-regulated learner skills; media and digital literacy; autonomy-driven learning, interactive and collaborative learning in an authentic international environment and open-mindedness. The study provided input for further conceptualising of OpenVM as a bridge between VM and OE.

By nature, learning is social. The interactions by which we learn from others inherently form a network of relationships among people, but also between people and resources. This paper gives an overview of the potential social network analysis (SNA) may have for social learning. It starts with an overview of the history of social learning and how SNA may be of value. The core of the paper outlines the state-of-art of SNA for technology-enhanced learning (TEL), by means of four possible types of SNA applications: visualisation, analysis, simulation, and interventions. In an outlook, future directions of SNA research for TEL are provided.

People recommenders are a widespread feature of social networking sites and educational social learning platforms alike. However, when these systems are used to extend learners' P ersonal L earning N etworks, they often fall short of providing recommendations of learning value to their users. This paper proposes a design of a people recommender based on content‐based user profiles, and a matching method based on dissimilarity therein. It presents the results of an experiment conducted with curators of the content curation site S coop.it!, where curators rated personalized recommendations for contacts. The study showed that matching dissimilarity of interpretations of shared interests is more successful in providing positive experiences of breakdown for the curator than is matching on similarity. The main conclusion of this paper is that people recommenders should aim to trigger constructive experiences of breakdown for their users, as the prospect and potential of such experiences encourage learners to connect to their recommended peers.