2,537 research outputs found

    Connectivism: a knowledge learning theory for the digital age?

    Get PDF
    <b>Background</b> The emergence of the internet, particularly Web 2.0 has provided access to the views and opinions of a wide range of individuals opening up opportunities for new forms of communication and knowledge formation. Previous ways of navigating and filtering available information are likely to prove ineffective in these new contexts. Connectivism is one of the most prominent of the network learning theories which have been developed for e-learning environments. It is beginning to be recognised by medical educators. This paper aims to examine connectivism and its potential application.<p></p> <b>Content</b> The conceptual framework and application of connectivism are presented along with an outline of the main criticisms. Its’ potential application in medical education is then considered.<p></p> <b>Conclusions</b> While connectivism provides a useful lens through which teaching and learning using digital technologies can be better understood and managed, further development and testing is required. There is unlikely to be a single theory that will explain learning in technological enabled networks. Educators have an important role to play in online network learning

    Understanding Communication Patterns in MOOCs: Combining Data Mining and qualitative methods

    Full text link
    Massive Open Online Courses (MOOCs) offer unprecedented opportunities to learn at scale. Within a few years, the phenomenon of crowd-based learning has gained enormous popularity with millions of learners across the globe participating in courses ranging from Popular Music to Astrophysics. They have captured the imaginations of many, attracting significant media attention - with The New York Times naming 2012 "The Year of the MOOC." For those engaged in learning analytics and educational data mining, MOOCs have provided an exciting opportunity to develop innovative methodologies that harness big data in education.Comment: Preprint of a chapter to appear in "Data Mining and Learning Analytics: Applications in Educational Research

    Supporting professional learning in a massive open online course

    Get PDF
    Professional learning, combining formal and on the job learning, is important for the development and maintenance of expertise in the modern workplace. To integrate formal and informal learning, professionals have to have good self-regulatory ability. Formal learning opportunities are opening up through massive open online courses (MOOCs), providing free and flexible access to formal education for millions of learners worldwide. MOOCs present a potentially useful mechanism for supporting and enabling professional learning, allowing opportunities to link formal and informal learning. However, there is limited understanding of their effectiveness as professional learning environments. Using self-regulated learning as a theoretical base, this study investigated the learning behaviours of health professionals within Fundamentals of Clinical Trials, a MOOC offered by edX. Thirty-five semi-structured interviews were conducted and analysed to explore how the design of this MOOC supported professional learning to occur. The study highlights a mismatch between learning intentions and learning behaviour of professional learners in this course. While the learners are motivated to participate by specific role challenges, their learning effort is ultimately focused on completing course tasks and assignments. The study found little evidence of professional learners routinely relating the course content to their job role or work tasks, and little impact of the course on practice. This study adds to the overall understanding of learning in MOOCs and provides additional empirical data to a nascent research field. The findings provide an insight into how professional learning could be integrated with formal, online learning

    Student engagement in massive open online courses

    Get PDF
    Completion rates in Massive Open Online Courses (MOOCs) are disturbingly low. Existing analysis has focused on patterns of resource access and prediction of drop-out using learning analytics. In contrast, the effectiveness of teaching programs in traditional Higher Education (HE) settings internationally is increasingly assessed by surveys measuring student engagement. The conceptualisation of engagement used is much richer and more informative than the way the term is currently interpreted in the context of MOOCs. This paper considers MOOC participation, learning and drop-out in the context of this richer conceptualisation of student engagement. MOOC pedagogy and practice are examined and we evaluate how far HE engagement measures can be successfully used in the MOOC context. We identify the need for a MOOC engagement model and suggest recommendations for basic, initial steps which MOOC developers can make towards improving engagement
    • 

    corecore