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Learning and Knowledge Analytics - Analyzing what can be connected

Learning and Knowledge Analytics - Analyzing what can be connected
Stanford Learning Analytics Summer Institute Posted by George Siemens on June 27, 2013 Looking forward to an exciting week discussing learning analytics next week! We (SoLAR, IEDMS and others) are organizing a Learning Analytics Summer Institute (LASI). A call for attendance was held earlier this year and the event was/is (massively) oversubscribed. We were only able to accept 100 attendees due to space and cost constraints.

Related:  Learning Analytics

Learning Analytics: The New Black Melanie Booth is Dean, Learning & Assessment, at Marylhurst University. Learning analytics is the "measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs," according to the 1st International Conference on Learning Analytics and Knowledge.1 The NMC Horizon Report: 2012 Higher Education Edition notes that this promising set of practices and tools aims to "harness the power of advances in data mining, interpretation, and modeling to improve understandings of teaching and learning, and to tailor education to individual students more effectively."2 Finally, George Siemens and Phil Long have even proposed that learning analytics should ultimately be focused on disruption and transformation in education, changing the very nature of teaching, learning, and assessment as we know it.3 Where We've Been Where We're Going Assessment [Learning Analytics] has most effect when:

Knowledge Media Institute Tech Report kmi-11-01 Abstract Social Learning AnalyticsTechreport ID: kmi-11-01Date: 2011Author(s): Simon Buckingham Shum,Rebecca Ferguson 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.

Learning analytics Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs.[1] A related field is educational data mining. For general audience introductions, see: The Educause Learning Initiative Briefing [2]The Educause Review on Learning analytics [3]And the UNESCO "Learning Analytics Policy Brief" (2012)[4] What is Learning Analytics?[edit] MOOCs prompt some faculty members to refresh teaching styles CAMBRIDGE, Mass. -- Amid the various influences that massive open online courses have had on higher education in their short life so far -- the topic of a daylong conference here Monday -- this may be among the more unexpected: The courses may be prompting some faculty to pay more attention to their teaching styles than they ever have before. The conference, organized Monday in Cambridge by Harvard University and the Massachusetts Institute of Technology, featured academics and administrators from elite North American universities and other players in the world of MOOCs discussing the rise of online courses and the future of residential colleges and universities. The new attention to teaching methods and learning sciences is coming from two directions: faculty who want to make sure their teaching is up to snuff for a wider audience, and technology that allows new levels of interaction with students, and new understanding of students' strengths and weaknesses.

Adam Cooper’s Work Blog » A Seasonal Sociogram for Learning Analytics Research SoLAR, the Society for Learning Analytics Research has recently made available a dataset covering research publications in learning analytics and educational data mining and issued the LAK Data Challenge, challenging the community to use the dataset to answer the question: What do analytics on learning analytics tell us? How can we make sense of this emerging field’s historical roots, current state, and future trends, based on how its members report and debate their research?

Open Learning Analytics Network - Summit Europe 2014 What is Open Learning Analytics? Learning Analytics is rightly identified as being a potent enabler of change in formal and informal education and training, in educational establishments and in the workplace. Open technical architectures and Open Standards are a critical requirement for achieving results at scale; they provide a conceptual and technical framework to allow both proprietary and Open Source software providers to innovate in their particular niche. These are two pillars of the idea of an Open Learning Analytics framework, a technical and conceptual basis for multiple real-world platforms, which would be: Open, with processes, algorithms, and technologies being accessible and changeable. This is important for innovation and meeting the varying contexts of implementation.

Reflections on the Knowledge Society » Pedagogy and the Learning Analytics model I received valuable feedback on the proposed design framework for Learning Analytics. A key question people asked was where pedagogy was in the model. Here is how I see it: Pedagogic strategies and learning activities as such are not part of the analytics process but are implicitly contained in the input datasets that encapsulate the pedagogic behaviour of users. As we know, this behaviour depends a great deal on the platform and the pedagogic vision the developers built in (cf.

JEDM - Journal of Educational Data Mining The Journal of Educational Data Mining (JEDM; ISSN 2157-2100 ) is an international and interdisciplinary forum of research on computational approaches for analysing electronic repositories of student data to answer educational questions. Educational Data Mining is an emerging discipline, concerned with developing methods for exploring the unique types of data that come from educational settings, and using those methods to better understand students, and the settings in which they learn. The journal welcomes basic and applied papers describing mature work involving computational approaches of educational data mining. Specifically, it welcomes high-quality original work including but not limited to the following topics: