This plan addresses the five essential components of learning powered by technology: Learning, Assessment, Teaching, Infrastructure, and Productivity.
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
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.
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
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.
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.
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.
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.
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.
BACKGROUND: Specialty referral patterns can affect health care costs as well as clinical outcomes. For a given clinical problem, referring physicians usually have a choice of several physicians to whom they can refer. Once the decision to refer is made, the choice of individual physician may have important downstream effects. OBJECTIVE: To examine the reasons why