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George Bradford

Journal of Learning Analytics - 0 views

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    Journal of learning analytics
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    Journal of learning analytics
George Bradford

The Connected Learning Analytics (CLA) Toolkit - 0 views

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    "Connected Learning is a modern pedagogical approach holding that knowledge and learning is distributed across a social, conceptual network. It holds that when people forge, negotiate and nurture connections for themselves (between people, information, knowledge, ideas and concepts), learning is more powerful and sustainable.

    Ideally, such learning could happen anywhere. People would create Personal Learning Networks within a Community of Inquiry. They would use whatever tools they consider relevant to this process, and connect with whoever they consider relevant to their network... However, this open connectivism is difficult to achieve in our current educational paradigms. How can we help people to teach "in the wild"? Learning Management Systems maintain a dominant position in the education sector, which means that technical support is generally provided only for those teachers who choose safety over openness."
George Bradford

Developing Student Learning Outcomes - Tool Box - Assessment - CSU, Chico - 0 views

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    "Developing Student Learning Outcomes

    Student learning outcome (SLO) statements take the program learning goals and focus on how students can demonstrate that the goals are being met. In other words, SLOs answer the question: how can graduates from this program demonstrate they have the needed/stated knowledge, skills, and/or values. SLOs are clear, concise statements that describe how students can demonstrate their mastery of program learning goals. Each student learning outcome statement must be measurable. Measures are applied to student work and may include student assignments, work samples, tests, etc. measuring student ability/skill, knowledge, or attitude/value."
George Bradford

Software | Learning Emergence - 0 views

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    Learning Emergence
    deep learning | complex systems | transformative leadership | knowledge media
George Bradford

Conference Proceedings, Networked Learning Conference 2012, Lancaster University UK - 0 views

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    Conference Papers - Networked Learning Conference

    Symposia

    Symposium Number Symposium Details
bcby c

Recordings | Learning and Knowledge Analytics - 1 views

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    Training course on learning analytics by George Siemens et al.
bcby c

Spring Focus Session Community Ideas - Google Docs - 0 views

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    educause learning initiative
    2012 online spring focus session: learning analytics
    Teaching and Learning Community's ideas
bcby c

(7) Eli 2012 Sensemaking Analytics - 0 views

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    George Siemens's PPT at ELI focus group
George Bradford

Open Research Online - Social Learning Analytics: Five Approaches - 0 views

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    This paper proposes that Social Learning Analytics (SLA) can be usefully thought of as a subset of learning analytics approaches. SLA focuses on how learners build knowledge together in their cultural and social settings. In the context of online social learning, it takes into account both formal and informal educational environments, including networks and communities. The paper introduces the broad rationale for SLA by reviewing some of the key drivers that make social learning so important today. Five forms of SLA are identified, including those which are inherently social, and others which have social dimensions. The paper goes on to describe early work towards implementing these analytics on SocialLearn, an online learning space in use at the UK's Open University, and the challenges that this is raising. This work takes an iterative approach to analytics, encouraging learners to respond to and help to shape not only the analytics but also their associated recommendations.
George Bradford

Open Research Online - Learning dispositions and transferable competencies: pedagogy, m... - 0 views

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    Theoretical and empirical evidence in the learning sciences substantiates the view that deep engagement in learning is a function of a complex combination of learners' identities, dispositions, values, attitudes and skills. When these are fragile, learners struggle to achieve their potential in conventional assessments, and critically, are not prepared for the novelty and complexity of the challenges they will meet in the workplace, and the many other spheres of life which require personal qualities such as resilience, critical thinking and collaboration skills. To date, the learning analytics research and development communities have not addressed how these complex concepts can be modelled and analysed, and how more traditional social science data analysis can support and be enhanced by learning analytics. We report progress in the design and implementation of learning analytics based on a research validated multidimensional construct termed "learning power". We describe, for the first time, a learning analytics infrastructure for gathering data at scale, managing stakeholder permissions, the range of analytics that it supports from real time summaries to exploratory research, and a particular visual analytic which has been shown to have demonstrable impact on learners. We conclude by summarising the ongoing research and development programme and identifying the challenges of integrating traditional social science research, with learning analytics and modelling.
George Bradford

About | Learning Emergence - 0 views

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    CORE IDEAS
    We decided on the name Learning Emergence because we are very much learning about emergence and complex systems phenomena ourselves, even as we develop our thinking on learning as an emergent, systemic phenomenon in different contexts.

    We must shift to a new paradigm for learning in schools, universities and the workplace which addresses the challenges of the 21st Century. Society needs learners who can cope with intellectual, ethical and emotional complexity of an unprecedented nature.

    Learning Emergence partners share an overarching focus on deep, systemic learning and leadership - the pro-active engagement of learners and leaders in their own authentic learning journey, in the context of relationship and community. We work at the intersection of (1) deep learning and sensemaking, (2) leadership, (3) complex systems, and (4) technology:
George Bradford

From the Semantic Web to social machines: A research challenge for AI on the World Wide... - 0 views

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    From the Semantic Web to social machines: A research challenge for AI on the World Wide Web
    Jim Hendler, Tim Berners-Lee

    Abstract
    The advent of social computing on the Web has led to a new generation of Web applications that are powerful and world-changing. However, we argue that we are just at the beginning of this age of "social machines" and that their continued evolution and growth requires the cooperation of Web and AI researchers. In this paper, we show how the growing Semantic Web provides necessary support for these technologies, outline the challenges we see in bringing the technology to the next level, and propose some starting places for the research.
George Bradford

[!!!!] Social Learning Analytics - Technical Report (pdf) - 0 views

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    Technical Report KMI-11-01
    June 2011
    Simon Buckingham Shum and Rebecca Ferguson

    Abstract: We propose that the design and implementation of effective Social Learning Analytics presents significant challenges and opportunities for both research and enterprise, in three important respects. The first is the challenge of implementing analytics that have pedagogical and ethical integrity, in a context where power and control over data is now of primary importance. The second challenge is that the educational landscape is extraordinarily turbulent at present, in no small part due to technological drivers. Online social learning is emerging as a significant phenomenon for a variety of reasons, which we review, in order to motivate the concept of social learning, and ways of conceiving social learning environments as distinct from other social platforms. This sets the context for the third challenge, namely, to understand different types of Social Learning Analytic, each of which has specific technical and pedagogical challenges. We propose an initial taxonomy of five types. We conclude by considering potential futures for Social Learning Analytics, if the drivers and trends reviewed continue, and the prospect of solutions to some of the concerns that institution-centric learning analytics may provoke. 
George Bradford

A unified framework for multi-level analysis of distributed learning - 0 views

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    A unified framework for multi-level analysis of distributed learning
    Full Text: PDF
    Authors: Daniel Suthers University of Hawaii, Honolulu, HI
    Devan Rosen School of Communications, Ithaca College, Ithaca, NY

    Learning and knowledge creation is often distributed across multiple media and sites in networked environments. Traces of such activity may be fragmented across multiple logs and may not match analytic needs. As a result, the coherence of distributed interaction and emergent phenomena are analytically cloaked. Understanding distributed learning and knowledge creation requires multi-level analysis of the situated accomplishments of individuals and small groups and of how this local activity gives rise to larger phenomena in a network. We have developed an abstract transcript representation that provides a unified analytic artifact of distributed activity, and an analytic hierarchy that supports multiple levels of analysis. Log files are abstracted to directed graphs that record observed relationships (contingencies) between events, which may be interpreted as evidence of interaction and other influences between actors. Contingency graphs are further abstracted to two-mode directed graphs that record how associations between actors are mediated by digital artifacts and summarize sequential patterns of interaction. Transitive closure of these associograms creates sociograms, to which existing network analytic techniques may be applied, yielding aggregate results that can then be interpreted by reference to the other levels of analysis. We discuss how the analytic hierarchy bridges between levels of analysis and theory.
George Bradford

Learning and Knowledge Analytics - Analyzing what can be connected - 0 views

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    Learning and Knowledge Analytics
    Analyzing what can be connected
George Bradford

Many Eyes - 0 views

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    Try yourself:

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George Bradford

Many Eyes : Browsing visualizations - 0 views

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    Listing visualizations of data. IBM Research and the IBM Cognos experiment.
George Bradford

Learning Dispositions and Transferable Competencies: Pedagogy, Modelling, and Learning ... - 0 views

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    Simon Buckingham Shum
    Ruth Deakin Crick
    2012 (In review)

    Theoretical and empirical evidence in the learning sciences 
    substantiates the view that deep engagement in learning is a 
    function of a  combination of learners' dispositions,  values, 
    attitudes and skills. When these are fragile, learners struggle to 
    achieve their potential in conventional assessments, and critically, 
    are not prepared for the novelty and complexity of the challenges 
    they will meet in the workplace, and the many other spheres of 
    life which require personal qualities such as resilience, critical 
    thinking and collaboration skills. To date, the learning analytics 
    research and development communities have not addressed how 
    these complex concepts can be modelled and analysed. We report 
    progress in the design and implementation of learning analytics 
    based on an empirically validated  multidimensional construct 
    termed  "learning power". We describe a  learning analytics 
    infrastructure  for gathering data at scale, managing stakeholder 
    permissions, the range of analytics that it supports from real time 
    summaries to exploratory research, and a particular visual analytic
    which has been shown to have demonstrable impact on learners. 
    We conclude by  summarising the ongoing research and 
    development programme.
George Bradford

Learning Analytics: Ascilite 2011 Keynote - 0 views

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    Learning Analytics: Dream, Nightmare, or Fairydust?

    From today's keynote at Ascilite 2011, here's the podcast plus the slides. I am grateful to Gary, Renee and everyone else at Ascilite for their understanding and flexibility, since after months of planning this trip, unfortunately I could not be there in person after my father passed away last weekend.

    For those of you who like to download and watch offline: podcast [Hi-Res version: 93.3Mb] + slides [PPTX/PDF]

    For detailed descriptions of work presented here, see other posts tagged learning analytics and the references below.
George Bradford

QUT | Learning and Teaching Unit | REFRAME - 0 views

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    REFRAME

    REFRAME is a university-wide project reconceptualising QUT's evaluation of learning and teaching.

    REFRAME is fundamentally reconsidering QUT's overall approach to evaluating learning and teaching. Our aim is to develop a sophisticated risk-based system to gather, analyse and respond to data along with a broader set of user-centered resources. The objective is to provide individuals and teams with the tools, support and reporting they need to meaningfully reflect upon, review and improve teaching, student learning and the curriculum. The approach will be informed by feedback from the university community, practices in other institutions and the literature, and will, as far as possible, be 'future-proofed' through awareness of emergent evaluation trends and tools.

    Central to REFRAME is the consideration of the purpose of evaluation and the features that a future approach should consider.
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