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Author: Brian S McGowan, PhD

ABSTRACT: Social media in vascular surgery. [J Vasc Surg. 2013] – PubMed – NCBI

Abstract
There has been a tremendous growth in the use of social media to expand the visibility of various specialties in medicine. The purpose of this paper is to describe the latest updates on some current applications of social media in the practice of vascular surgery as well as existing limitations of use. This investigation demonstrates that the use of social networking sites appears to have a positive impact on vascular practice, as is evident through the incorporation of this technology at the Cleveland Clinic and by the Society for Vascular Surgery into their approach to patient care and physician communication. Overall, integration of social networking technology has current and future potential to be used to promote goals, patient awareness, recruitment for clinical trials, and professionalism within the specialty of vascular surgery.

via Social media in vascular surgery. [J Vasc Surg. 2013] – PubMed – NCBI.

ABSTRACT: A centralized research data repository enhances retrospective outcomes research capacity: a case report — Hruby et al. — Journal of the American Medical Informatics Association

Abstract
This paper describes our considerations and methods for implementing an open-source centralized research data repository (CRDR) and reports its impact on retrospective outcomes research capacity in the urology department at Columbia University. We performed retrospective pretest and post-test analyses of user acceptance, workflow efficiency, and publication quantity and quality (measured by journal impact factor) before and after the implementation. The CRDR transformed the research workflow and enabled a new research model. During the pre- and post-test periods, the department’s average annual retrospective study publication rate was 11.5 and 25.6, respectively; the average publication impact score was 1.7 and 3.1, respectively. The new model was adopted by 62.5% (5/8) of the clinical scientists within the department. Additionally, four basic science researchers outside the department took advantage of the implemented model. The average proximate time required to complete a retrospective study decreased from 12 months before the implementation to <6 months after the implementation. Implementing a CRDR appears to be effective in enhancing the outcomes research capacity for one academic department.

via A centralized research data repository enhances retrospective outcomes research capacity: a case report — Hruby et al. — Journal of the American Medical Informatics Association.

SLIDESHARE: A snapshot of MOOCs in Higher Education

Massive Open Online Courses (MOOCs) have been the hottest topic in Higher Education this year. Educating tens of thousands of students in one online course subtends some exciting opportunities but also a raft of pedagogical, logistical, and systemic challenges. This presentation summarises the key issues at stake and outlines a direction forward for Massive Open Online Courses in Higher Education.

Kenney, J.L. & Bower, M. (2012). Massive Open Online Courses (MOOCs): A snapshot. Presented at Expanding Horizons, L&T Week, Macquarie University, Sydney, Australia, 18 September.

Audio available from: http://tinyurl.com/moocs-snapshot

 

RESOURCE: Online courses need human element to educate – CNN.com

Finally, education does not happen in isolation.Whether it’s philosophy students arguing in a dorm about what Hegel meant, or fledgling Java programmers inspecting one another’s code, people learn best as part of a cohort. The course material is almost secondary to the engagement. We go to college for the people.Likewise, the best of MOOCs should be able bring together ideal, heterogeneous groupings of students based on their profiles and past performance, and also create ample opportunities for them to engage with one another in the spirit of learning.

via Online courses need human element to educate – CNN.com.

REPORT: Expanding Evidence Approaches for Learning in a Digital World

The report discusses the promise of sophisticated digital learning systems for collecting and analyzing very large amounts of fine-grained data (“big data”) as users interact with the systems. It proposes that this data can be used by developers and researchers to improve these learning systems and strive to discover more about how people learn. It discusses the potential of developing more sophisticated ways of measuring what learners know and adaptive systems that can personalize learners’ experiences.

http://www.ed.gov/edblogs/technology/files/2012/12/Expanding_Evidence_Approaches_DRAFT.pdf

REPORT: Enhancing Teaching and Learning through Educational Data Mining and Learning Analytics

Big data is everywhere—even in education. Researchers and developers of online learning, intelligent tutoring systems, virtual labs, simulations, and learning management systems are exploring ways to better understand and use learning analytics to improve teaching and learning.

http://www.ed.gov/edblogs/technology/files/2012/03/edm-la-brief.pdf

Learning analytics for better learning content | Ed Tech Now

We thought you needed:

  • large quantities of data (volume);
  • varied sources of data (variety);
  • semantically meaningful data (which is a similar to validity), the latter being  about accuracy and the former being about having a meaningful standard in the first place, against which that accuracy can be measured. This is a complex topic which touches on structured, unstructured and semi-structured data which deserves another article in the future.

via Learning analytics for better learning content | Ed Tech Now.

RESOURCE: MOOCs and other ed-tech bubbles | Ed Tech Now

“analytics is predicated on “big data” but in education, big data will not exist until we sort out the current failure of interoperability”

By spotting patterns in the data produced by students’ online learning activity, learning analytics systems should be able to help:

  • predict student progress;
  • inform adaptive learning strategies (sequencing digital learning activities or recommending human interventions);
  • profile a student’s current capabilities;
  • automatically group students, depending on their learning needs;
  • identify the most effective learning strategies in different situations;
  • aggregate and present complex data in ways which helps administrators, teachers and students manage instructional processes.

via MOOCs and other ed-tech bubbles | Ed Tech Now.

MANUSCRIPT: Making Sense of MOOCs: Musings in a Maze of Myth, Paradox and Possibility

During my time as a Fellow at the Korea National Open University (KNOU) in September 2012 media and web coverage of Massive Open Online Courses (MOOCs) was intense. Since one of the requirements of the fellowship was a research paper, exploring the phenomenon of MOOCs seemed an appropriate topic. This essay had to be submitted to KNOU on 25 September 2012 but the MOOCs story is still evolving rapidly. I shall continue to follow it.

‘What is new is not true, and what is true is not new’. Hans Eysenck on Freudianism

http://www.tonybates.ca/wp-content/uploads/Making-Sense-of-MOOCs.pdf