25,666 research outputs found

    Dialogue as Data in Learning Analytics for Productive Educational Dialogue

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    This paper provides a novel, conceptually driven stance on the state of the contemporary analytic challenges faced in the treatment of dialogue as a form of data across on- and offline sites of learning. In prior research, preliminary steps have been taken to detect occurrences of such dialogue using automated analysis techniques. Such advances have the potential to foster effective dialogue using learning analytic techniques that scaffold, give feedback on, and provide pedagogic contexts promoting such dialogue. However, the translation of much prior learning science research to online contexts is complex, requiring the operationalization of constructs theorized in different contexts (often face-to-face), and based on different datasets and structures (often spoken dialogue). In this paper, we explore what could constitute the effective analysis of productive online dialogues, arguing that it requires consideration of three key facets of the dialogue: features indicative of productive dialogue; the unit of segmentation; and the interplay of features and segmentation with the temporal underpinning of learning contexts. The paper thus foregrounds key considerations regarding the analysis of dialogue data in emerging learning analytics environments, both for learning-science and for computationally oriented researchers

    Analytics and complexity: learning and leading for the future

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    There is growing interest in the application of learning analytics to manage, inform and improve learning and teaching within higher education. In particular, learning analytics is seen as enabling data-driven decision making as universities are seeking to respond a range of significant challenges that are reshaping the higher education landscape. Experience over four years with a project exploring the use of learning analytics to improve learning and teaching at a particular university has, however, revealed a much more complex reality that potentially limits the value of some analytics-based strategies. This paper uses this experience with over 80,000 students across three learning management systems, combined with literature from complex adaptive systems and learning analytics to identify the source and nature of these limitations along with a suggested path forward

    Broadening the Scope and Increasing the Usefulness of Learning Analytics: The Case for Assessment Analytics

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    This paper argues that the role that assessment could play within a learning analytics strategy is both significant and, as yet, underdeveloped and underexplored. It proposes that assessment analytics has the potential to make a valuable contribution to the field of learning and academic analytics by both broadening its scope and increasing its usefulness. In doing so it considers issues of operationalization and then moves on to define what we might understand as assessment analytics

    Immersive Telepresence: A framework for training and rehearsal in a postdigital age

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    Digital communities: context for leading learning into the future?

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    In 2011, a robust, on-campus, three-element Community of Practice model consisting of growing community, sharing of practice and building domain knowledge was piloted in a digital learning environment. An interim evaluation of the pilot study revealed that the three-element framework, when used in a digital environment, required a fourth element. This element, which appears to happen incidentally in the face-to-face context, is that of reflecting, reporting and revising. This paper outlines the extension of the pilot study to the national tertiary education context in order to explore the implications for the design, leadership roles, and selection of appropriate technologies to support and sustain digital communities using the four-element model
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