Towards a Social Trust-Aware Recommender for Teachers

Fazeli, S., Drachsler, H., Brouns, F., & Sloep, P. B. (2014). Towards a Social Trust-aware Recommender for Teachers. In N. Manouselis, H. Drachsler, K. Verbert & O. C. Santos (Eds.), Recommender Systems for Technology Enhanced Learning (pp. 177-194): Springer New York.Online communities and networked learning provide teachers with social learning opportunities, allowing them to interact and collaborate with others in order to develop their personal and professional skills. However, with the large number of learning resources produced everyday, teachers need to find out what are the most suitable ones for them. In this paper, we introduce recommender systems as a potential solution to this . The setting is the Open Discovery Space (ODS) project. Unfortunately, due to the sparsity of the educational datasets most educational recommender systems cannot make accurate recommendations. To overcome this problem, we propose to enhance a trust-based recommender algorithm with social data obtained from monitoring the activities of teachers within the ODS platform. In this article, we outline the re-quirements of the ODS recommender system based on experiences reported in related TEL recommender system studies. In addition, we provide empirical ev-idence from a survey study with stakeholders of the ODS project to support the requirements identified from a literature study. Finally, we present an agenda for further research intended to find out which recommender system should ul-timately be deployed in the ODS platform.NELLL, EU 7th framework Open Discovery Spac

Technology-enhanced Professional Learning

Societal and technological changes are transforming the ways people work and learn. As work roles evolve, learning for work becomes continual and personalised. These transformations evidenced in work and learning practices are partly governed by advances in technology. Consideration of work practices, professional learning processes and technologies mediating work and learning within a single domain of "Technology-enhanced Professional Learning" enables analysis of the dialectical relationship between technology and practice. This chapter begins by presenting a single framework that integrates perspectives across the domains of work practices, learning processes and digital technologies. Key trends are outlined from the literature within each domain. Using a framework for TEPL as an analytical lens, emerging work and technology practices and their implications for professional learning both in and for work are examined. Finally, the chapter outlines the implications of these developments for work and learning

Annales

Crucial in any learning process are the activities that learners undertake: reading, thinking, discussing, exploring, problem solving, etc. When learners are passive you cannot expect them to learn much. The primary role of any instructional agent, whether it is a teacher, the learners themselves or a computer, is to stimulate the performance of learning activities that will gradually result in the attainment of the learning objectives. The instructional agent defines the tasks, provides the contexts and resources to perform the tasks, supports the learner during task performance and provides feedback about the results. The learning activities that are needed to obtain some learning objectives are in most cases carefully sequenced according to some pedagogical principles. This sequence of learning activities that learners undertake to attain some learning objectives, including the resources and support mechanisms required to help learners to complete these activities, is called a learning design