Brian S McGowan, PhD, Author at ArcheMedX

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

Posted on 15 Jan 2013
By Brian S McGowan, PhD
In Education Technology, Informatics & Analysis, Manuscript, Medical Education, Online Learning, Resources

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

Posted on 15 Jan 2013
By Brian S McGowan, PhD
In Education Technology, Informatics & Analysis, Manuscript, Medical Education, Online Learning, Resources

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.

Posted on 15 Jan 2013
By Brian S McGowan, PhD
In Informatics & Analysis, Medical Education, Resources

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.

Posted on 15 Jan 2013
By Brian S McGowan, PhD
In Informatics & Analysis, Medical Education, Online Learning, Resources, Social Media & Medical Education

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

Posted on 15 Jan 2013
By Brian S McGowan, PhD
In Education Technology, Manuscript, Medical Education, Online Learning, Resources, Social Media & Medical Education

MANUSCRIPT: Automated Detection of Adverse Events Using Natural Language Processing of Discharge Summaries

A b s t r a c t Objective: To determine whether natural language processing (NLP) can effectively detect adverse events defined in the New York Patient Occurrence Reporting and Tracking System (NYPORTS) using discharge summaries.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1174890/pdf/448.pdf

Posted on 14 Jan 2013
By Brian S McGowan, PhD
In Informatics & Analysis, Manuscript, Resources

MANUSCRIPT: Large-scale evaluation of automated clinical note de-identification and its impact on information extraction

ABSTRACT
Objective (1) To evaluate a state-of-the-art natural language processing (NLP)-based approach to automatically de-identify a large set of diverse clinical notes. (2) To measure the impact of de-identification on the performance of information extraction algorithms on the de-identified documents.

http://jamia.bmj.com/content/20/1/84.full.pdf html

Posted on 14 Jan 2013
By Brian S McGowan, PhD
In Informatics & Analysis, Manuscript, Resources

MANUSCRIPT: eQuality for All: Extending Automated Quality Measurement of Free Text Clinical Narratives

Introduction: Electronic quality monitoring (eQuality) from clinical narratives may advance current manual quality measurement techniques. We evaluated automated eQuality measurement tools on clinical narratives of veterans’ disability examinations.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2656015/pdf/amia-0071-s2008.pdf

Posted on 14 Jan 2013
By Brian S McGowan, PhD
In Informatics & Analysis, Manuscript, Resources

MANUSCRIPT: Mapping Physician Networks with Self- Reported and Administrative Data

Objective: To assess whether connections between physicians based on shared patients in administrative data correspond with professional relationships between physicians.
Data Sources/Study Setting: Survey of physicians affiliated with a large academic and community physicians’ organization and 2006 Medicare data from a 100 percent sample of patients in the Boston Hospital referral region.

http://humannaturelab.net/wp-content/themes/human-nature-lab/media/pdf/publications/articles/122.pdf

Posted on 14 Jan 2013
By Brian S McGowan, PhD
In Informatics & Analysis, Manuscript, Rapid Learning Healthcare System, Resources

MANUSCRIPT: Physician Patient-sharing Networks and the Cost and Intensity of Care in US Hospitals

Background: There is substantial variation in the cost and intensity of care delivered by US hospitals. We assessed how the structure of patient-sharing networks of physicians affiliated with hospitals might contribute to this variation.

http://humannaturelab.net/wp-content/themes/human-nature-lab/media/pdf/publications/articles/128.pdf

Posted on 14 Jan 2013
By Brian S McGowan, PhD
In Informatics & Analysis, Manuscript, Rapid Learning Healthcare System, Resources

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Author: Brian S McGowan, PhD

REPORT: Expanding Evidence Approaches for Learning in a Digital World

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

Learning analytics for better learning content | Ed Tech Now

MANUSCRIPT: Automated Detection of Adverse Events Using Natural Language Processing of Discharge Summaries

MANUSCRIPT: Large-scale evaluation of automated clinical note de-identification and its impact on information extraction

MANUSCRIPT: eQuality for All: Extending Automated Quality Measurement of Free Text Clinical Narratives

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