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George Bradford

Learning networks, crowds and communities - 1 views

    Learning networks, crowds and communities
    Full Text: PDF
    Author: Caroline Haythornthwaite University of British Columbia, Vancouver, BC

    Who we learn from, where and when is dramatically affected by the reach of the Internet. From learning for formal education to learning for pleasure, we look to the web early and often for our data and knowledge needs, but also for places and spaces where we can collaborate, contribute to, and create learning and knowledge communities. Based on the keynote presentation given at the first Learning Analytics and Knowledge Conference held in 2011 in Banff, Alberta, this paper explores a social network perspective on learning with reference to social network principles and studies by the author. The paper explores the ways a social network perspective can be used to examine learning, with attention to the structure and dynamics of online learning networks, and emerging configurations such as online crowds and communities.
bcby c

Recordings | Learning and Knowledge Analytics - 1 views

    Training course on learning analytics by George Siemens et al.
George Bradford

Stunning Infographics and Data Visualization - Noupe - 1 views

    Creating an effective infographic requires both artistic sense and a clear vision of what to tell the audience. The following are some cool infographics we have collected. Some are colorful, some are simple, but all are informative and visually pleasing. Not only do they provide information in a format that is easy to understand, but they are also artistic creations in their own right.
George Bradford

University builds 'course recommendation engine' to steer students toward completion | ... - 0 views

    Recommended for You
    March 16, 2012 - 3:00am
    Steve Kolowich
    Completing assignments and sitting through exams can be stressful. But when it comes to being graded the waiting is often the hardest part. This is perhaps most true at the end of a semester, as students wait for their instructors to reduce months of work into a series of letter grades that will stay on the books forever.
    But at Austin Peay State University, students do not have to wait for the end of a semester to learn their grade averages. Thanks to a new technology, pioneered by the university's provost, they do not even have to wait for the semester to start.
George Bradford

Open Research Online - Learning analytics to identify exploratory dialogue within synch... - 0 views

    While generic web analytics tend to focus on easily harvested quantitative data, Learning Analytics will often seek qualitative understanding of the context and meaning of this information. This is critical in the case of dialogue, which may be employed to share knowledge and jointly construct understandings, but which also involves many superficial exchanges. Previous studies have validated a particular pattern of "exploratory dialogue" in learning environments to signify sharing, challenge, evaluation and careful consideration by participants. This study investigates the use of sociocultural discourse analysis to analyse synchronous text chat during an online conference. Key words and phrases indicative of exploratory dialogue were identified in these exchanges, and peaks of exploratory dialogue were associated with periods set aside for discussion and keynote speakers. Fewer individuals posted at these times, but meaningful discussion outweighed trivial exchanges. If further analysis confirms the validity of these markers as learning analytics, they could be used by recommendation engines to support learners and teachers in locating dialogue exchanges where deeper learning appears to be taking place.
George Bradford

Open Research Online - Discourse-centric learning analytics - 0 views

    Drawing on sociocultural discourse analysis and argumentation theory, we motivate a focus on learners' discourse as a promising site for identifying patterns of activity which correspond to meaningful learning and knowledge construction. However, software platforms must gain access to qualitative information about the rhetorical dimensions to discourse contributions to enable such analytics. This is difficult to extract from naturally occurring text, but the emergence of more-structured annotation and deliberation platforms for learning makes such information available. Using the Cohere web application as a research vehicle, we present examples of analytics at the level of individual learners and groups, showing conceptual and social network patterns, which we propose as indicators of meaningful learning.
George Bradford

Open Research Online - Contested Collective Intelligence: rationale, technologies, and ... - 0 views

    We propose the concept of Contested Collective Intelligence (CCI) as a distinctive subset of the broader Collective Intelligence design space. CCI is relevant to the many organizational contexts in which it is important to work with contested knowledge, for instance, due to different intellectual traditions, competing organizational objectives, information overload or ambiguous environmental signals. The CCI challenge is to design sociotechnical infrastructures to augment such organizational capability. Since documents are often the starting points for contested discourse, and discourse markers provide a powerful cue to the presence of claims, contrasting ideas and argumentation, discourse and rhetoric provide an annotation focus in our approach to CCI. Research in sensemaking, computer-supported discourse and rhetorical text analysis motivate a conceptual framework for the combined human and machine annotation of texts with this specific focus. This conception is explored through two tools: a social-semantic web application for human annotation and knowledge mapping (Cohere), plus the discourse analysis component in a textual analysis software tool (Xerox Incremental Parser: XIP). As a step towards an integrated platform, we report a case study in which a document corpus underwent independent human and machine analysis, providing quantitative and qualitative insight into their respective contributions. A promising finding is that significant contributions were signalled by authors via explicit rhetorical moves, which both human analysts and XIP could readily identify. Since working with contested knowledge is at the heart of CCI, the evidence that automatic detection of contrasting ideas in texts is possible through rhetorical discourse analysis is progress towards the effective use of automatic discourse analysis in the CCI framework.
George Bradford

About | SNAPP - Social Networks Adapting Pedagogical Practice - 3 views

    "The Social Networks Adapting Pedagogical Practice (SNAPP) tool performs real-time social network analysis and visualization of discussion forum activity within popular commercial and open source Learning Management Systems (LMS). SNAPP essentially serves as a diagnostic instrument, allowing teaching staff to evaluate student behavioral patterns against learning activity design objectives and intervene as required a timely manner.

    Valuable interaction data is stored within a discussion forum but from the default threaded display of messages it is difficult to determine the level and direction of activity between participants. SNAPP infers relationship ties from the post-reply data and renders a social network diagram below the forum thread. The social network visualization can be filtered based upon user activity and social network data can be exported for further analysis in NetDraw. SNAPP integrates seamlessly with a variety of Learning Management Systems (Blackboard, Moodle and Desire2Learn) and must be triggered while a forum thread is displayed in a Web browser."
George Bradford

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

    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

    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

Times Higher Education - Satisfaction and its discontents - 0 views

    Satisfaction and its discontents

    8 March 2012
    The National Student Survey puts pressure on lecturers to provide 'enhanced' experiences. But, argues Frank Furedi, the results do not measure educational quality and the process infantilises students and corrodes academic integrity

    One of the striking features of a highly centralised system of higher education, such as that of the UK, is that the introduction of new targets and modifications to the quality assurance framework can have a dramatic impact in a very short space of time. When the National Student Survey was introduced in 2005, few colleagues imagined that, just several years down the road, finessing and managing its implementation would require the employment of an entirely new group of quality-assurance operatives. At the time, the NSS was seen by many as a relatively pointless public-relations exercise that would have only a minimal effect on academics' lives. It is unlikely that even its advocates would have expected the NSS to acquire a life of its own and become one of the most powerful influences on the form and nature of the work done in universities.
George Bradford

Wmatrix corpus analysis and comparison tool - 0 views

    Wmatrix is a software tool for corpus analysis and comparison. It provides a web interface to the USAS and CLAWS corpus annotation tools, and standard corpus linguistic methodologies such as frequency lists and concordances. It also extends the keywords method to key grammatical categories and key semantic domains.

    Wmatrix allows the user to run these tools via a web browser such as Opera, Firefox or Internet Explorer, and so will run on any computer (Mac, Windows, Linux, Unix) with a web browser and a network connection. Wmatrix was initially developed by Paul Rayson in the REVERE project, extended and applied to corpus linguistics during PhD work and is still being updated regularly. Earlier versions were available for Unix via terminal-based command line access (tmatrix) and Unix via Xwindows (Xmatrix), but these only offer retrieval of text pre-annotated with USAS and CLAWS.
George Bradford

Browse Maps - Places & Spaces: Mapping Science - 0 views

    Data Visualizations - Organized by KATY BÖRNER
George Bradford

Cohere >>> make the connection - 0 views

    About Cohere

    The Web is about IDEAS+PEOPLE.

    Cohere is a visual tool to create, connect and share Ideas.

    Back them up with websites. Support or challenge them. Embed them to spread virally.
    Discover who - literally - connects with your thinking.

    Publish ideas and optionally add relevant websites
    Weave webs of meaningful connections between ideas: your own and the world's
    Discover new ideas and people
    We experience the information ocean as streams of media fragments, flowing past us in every modality.

    To make sense of these, learners, researchers and analysts must organise them into coherent patterns.

    Cohere is an idea management tool for you to annotate URLs with ideas, and weave meaningful connections between ideas for personal, team or social use.

    Key Features

    Annotate a URL with any number of Ideas, or vice-versa.
    Visualize your network as it grows
    Make connections between your Ideas, or Ideas that anyone else has made public or shared with you via a common Group
    Use Groups to organise your Ideas and Connections by project, and to manage access-rights
    Import your data as RSS feeds (eg. bookmarks or blog posts), to convert them to Ideas, ready for connecting
    Use the RESTful API services to query, edit and mashup data from other tools
    Learn More

    Subscribe to our Blog to track developments as they happen.

    Read this article to learn more about the design of Cohere to support dialogue and debate.
George Bradford

People | Knowledge Media Institute | The Open University - 0 views

    People | Member | Simon Buckingham Shum
    Snr Lecturer in Knowledge Media

    I am fundamentally interested in technologies for sensemaking, specifically, which structure discourse to assist reflection and analysis. Examples: D3E, Compendium, ClaiMaker and Cohere.
George Bradford

IBM Solidifies Academic Analytics Investments - Datanami - 0 views

    December 22, 2011

    IBM Solidifies Academic Analytics Investments

    Datanami Staff

    As their own detailed report in conjunction with MIT Sloan made clear, IBM is keenly aware of the dramatic talent shortfall that could keep the future of big data analytics in check. Accordingly, the company is stepping in to boost analytics-driven programs at universities around the world.

    A report out of India this week indicated that Big Blue is firming up its investments at a number of academic institutions worldwide in the hopes of readying a new generation of analytics graduates. This effort springs from the company's Academic Initiative, which is the IBM-led effort to partner with universities to extend the capabilities of institutions to provide functional IT training and research opportunities.
bcby c

(7) Eli 2012 Sensemaking Analytics - 0 views

    George Siemens's PPT at ELI focus group
George Bradford

Learning process analytics - EduTech Wiki - 1 views


    In this discussion paper, we define learning process analytics as a collection of methods that allow teachers and learners to understand what is going on in a' 'learning scenario, i.e. what participants work(ed) on, how they interact(ed), what they produced(ed), what tools they use(ed), in which physical and virtual location, etc. Learning analytics is most often aimed at generating predictive models of general student behavior. So-called academic analytics even aims to improve the system. We are trying to find a solution to a somewhat different problem. In this paper we will focus on improving project-oriented learner-centered designs, i.e. a family of educational designs that include any or some of knowledge-building, writing-to-learn, project-based learning, inquiry learning, problem-based learning and so forth.
    We will first provide a short literature review of learning process analytics and related frameworks that can help improve the quality of educational scenarios. We will then describe a few project-oriented educational scenarios that are implemented in various programs at the University of Geneva. These examples illustrate the kind of learning scenarios we have in mind and help define the different types of analytics both learners and teachers need. Finally, we present a provisional list of analytics desiderata divided into "wanted tomorrow" and "nice to have in the future"."
George Bradford

Analytics in Higher Education - Benefits, Barriers, Progress, and Recommendations (EDUC... - 0 views

    Jacqueline Bichsel - 2012

    Many colleges and universities have demonstrated that analytics can help significantly advance an institution in such strategic areas as resource allocation, student success, and finance. Higher education leaders hear about these transformations occurring at other institutions and wonder how their institutions can initiate or build upon their own analytics programs. Some question whether they have the resources, infrastructure, processes, or data for analytics. Some wonder whether their institutions are on par with other in their analytics endeavors. It is within that context that this study set out to assess the current state of analytics in higher education, outline the challenges and barriers to analytics, and provide a basis for benchmarking progress in analytics.
George Bradford

College Degrees, Designed by the Numbers - Technology - The Chronicle of Higher Education - 0 views

  • Arizona State's retention rate rose to 84 percent from 77 percent in recent years, a change that the provost credits largely to eAdvisor.
  • Mr. Lange and his colleagues had found that by the eighth day of class, they could predict, with 70-percent accuracy, whether a student would score a C or better. Mr. Lange built a system, rolled out in 2009, that sent professors frequently updated alerts about how well each student was predicted to do, based on course performance and online behavior.
  • Rio Salado knows from its database that students who hand in late assignments and don't log in frequently often fail or withdraw from a course. So the software is more likely to throw up a red flag for current students with those characteristics.
  • ...5 more annotations...
  • And in a cautionary tale about technical glitches, the college began sharing grade predictions with students last summer, hoping to encourage those lagging behind to step up, but had to shut the alerts down in the spring. Course revisions had skewed the calculations, and some predictions were found to be inaccurate. An internal analysis found no increase in the number of students dropping classes. An improved system is promised for the fall.
  • His software borrows a page from Netflix. It melds each student's transcript with thousands of past students' grades and standardized-test scores to make suggestions. When students log into the online portal, they see 10 "Course Suggestions for You," ranked on a five-star scale. For, say, a health-and-human-performance major, kinesiology might get five stars, as the next class needed for her major. Physics might also top the list, to satisfy a science requirement in the core curriculum.
  • Behind those recommendations is a complex algorithm, but the basics are simple enough. Degree requirements figure in the calculations. So do classes that can be used in many programs, like freshman writing. And the software bumps up courses for which a student might have a talent, by mining their records—grades, high-school grade-point average, ACT scores—and those of others who walked this path before.
  • The software sifts through a database of hundreds of thousands of grades other students have received. It analyzes the historical data to figure out how much weight to assign each piece of the health major's own academic record in forecasting how she will do in a particular course. Success in math is strongly predictive of success in physics, for example. So if her transcript and ACT score indicate a history of doing well in math, physics would probably be recommended over biology, though both satisfy the same core science requirement.
  • Every year, students in Tennessee lose their state scholarships because they fall a hair short of the GPA cutoff, Mr. Denley says, a financial swing that "massively changes their likelihood of graduating."
    July 18, 2012
    College Degrees,
    Designed by the Numbers
    By Marc Parry

    Illustration by Randy Lyhus for The Chronicle

    Campuses are places of intuition and serendipity: A professor senses confusion on a student's face and repeats his point; a student majors in psychology after a roommate takes a course; two freshmen meet on the quad and eventually become husband and wife.

    Now imagine hard data substituting for happenstance.

    As Katye Allisone, a freshman at Arizona State University, hunkers down in a computer lab for an 8:35 a.m. math class, the Web-based course watches her back. Answers, scores, pace, click paths-it hoovers up information, like Google. But rather than personalizing search results, data shape Ms. Allisone's class according to her understanding of the material.
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