Learning technologies offer new opportunities to meet the rapidly growing demand for new, constructivist ways of learning (such as competencybased, collaborative or adaptive learning). They have the potential to act as catalysts for more effective exchange and reuse of learning objects to enable personalised learning. This article examines the extent to which current learning technology specifications contribute to educational change -to actual sharing and reuse in educational practice. Furthermore, the article describes the need for an Educational Modelling Language centred on learning activities to give instructional meaning to learning objects.To date, specifications for learning objects have primarily been designed to ensure interoperability at a rather low infrastructural level (e.g., test items, meta-data), focusing on technology issues and reuse of learning objects. We argue that more widespread adoption of e-learning specifications and standards calls for a pedagogical framework at a higher infrastructural level (e.g., a complete course), focusing on the instructional value and reuse of learning activities. Such a framework is offered by the new Learning Design (LD) specification. LD enables the description of both learning content and processes from a variety of pedagogical perspectives, both objectivist and constructivist.

Nowadays there is a huge demand for flexible, independent learning without the constraints of time and place. Various trends in the field of education and training are the bases for the development of new technologies for education. This article describes the development of a learning technology specification, which supports these new demands for learning challenging the new technological possibilities. This specification is named Educational Modelling Language (EML) and is developed by the Open University of the Netherlands.

Lifelong learning puts learner self-direction centre-stage. However, increased responsibility should not come at the price of over-burdening or abandonment of learners as they progress along their learning journey. This paper introduces an approach to wayfinding support for lifelong learners based on selforganisation theory. It describes an architecture which supports the recording, processing and presentation of collective learner behaviour designed to create a feedback loop informing learners of successful paths towards the attainment of learning goals. The approach is presented as an alternative to methods of achieving adaptation in hypermedia-based learning environments which involve learner modelling. The article concludes with a discussion of the questions being addressed in our ongoing research.

A first exploration of an inductive analysis approach for detecting learning design patterns.

The large-scale production, collection, aggregation, and processing of information from various learning platforms and online environments have led to ethical and privacy concerns regarding potential harm to individuals and society. In the past, these types of concern have impacted on areas as diverse as computer science, legal studies and surveillance studies. Within a European consortium that brings together the EU project LACE, the SURF SIG Learning Analytics, the Apereo Foundation and the EATEL SIG dataTEL, we aim to understand the issues with greater clarity, and to find ways of overcoming the issues and research challenges related to ethical and privacy aspects of learning analytics practice. This interactive workshop aims to raise awareness of major ethics and privacy issues. It will also be used to develop practical solutions to advance the application of learning analytics technologies.