1,036 research outputs found
E-XCELLENCE NEXT Report Review-at-a-distance MESI (Moscow) and MESI BRANCHES (Minsk, Yaroslav, Tver, Yerevan)
E-XCELLENCE NEXT Report Review-at-a-distance MESI (Moscow) and MESI BRANCHES (Minsk, Yaroslav, Tver, Yerevan)
E-XCELLENCE NEXT Report Local seminar Portugal
Wagemans, L. J. J. M., & Boon, M. J. J. P. M. (2012). E-XCELLENCE NEXT Report Local seminar Portugal. Heerlen: EADTU.E-learning has become mainstream provision in European higher education and is essential in supporting lifelong learning and internationalisation. By becoming integral part of higher education, e-learning should also be integral part of the QA systems, internal and external, with related innovative and appropriate criteria.
In the E-xcellence project (EADTU) an instrument is developed under the e-learning programme that creates an opportunity for the existing channels in QA to adopt new quality guidelines for increased quality, accessibility and attractiveness. As the E-xcellence instrument supplements existing QA systems with e-learning specific issues and addresses directly the higher education and adult education sector, it can be integrated within the existing QA frameworks.
In the past 2 stages in which E-xcellence was developed and promoted by and within open and blended universities and QA agencies, it has proven to be a valuable and valued open source tool. In a third step EADTU wants to serve universities Europe wide with an open and updated “quality assurance in e-learning” instrument.
One of the institutions where the E-xcellence instrument is introduced, is the Portugese Universidade Aberta (UAb). The report describes the introduction of the E-xcellence instrument in a Local seminar of two days with presentations given by representatives of the different programs, discussions and feedback of the Review team
Determining Ages of APOGEE Giants with Known Distances
We present a sample of local red giant stars observed using the New Mexico
State University 1 m telescope with the APOGEE spectrograph, for which we
estimate stellar ages and the age distribution from the high-resolution
spectroscopic stellar parameters and accurate distance measurements from
Hipparcos. The high-resolution (R ~ 23,000), near infrared (H-band, 1.5-1.7
micron) APOGEE spectra provide measurements of the stellar atmospheric
parameters (temperature, surface gravity, [M/H], and [alpha/M]). Due to the
smaller uncertainties in surface gravity possible with high-resolution spectra
and accurate Hipparcos distance measurements, we are able to calculate the
stellar masses to within 40%. For red giants, the relatively rapid evolution of
stars up the red giant branch allows the age to be constrained based on the
mass. We examine methods of estimating age using both the mass-age relation
directly and a Bayesian isochrone matching of measured parameters, assuming a
constant star formation history (SFH). To improve the prior on the SFH, we use
a hierarchical modeling approach to constrain the parameters of a model SFH
from the age probability distribution functions of the data. The results of an
alpha dependent Gaussian SFH model shows a clear relation between age and
[alpha/M] at all ages. Using this SFH model as the prior for an empirical
Bayesian analysis, we construct a full age probability distribution function
and determine ages for individual stars. The age-metallicity relation is flat,
with a slight decrease in [M/H] at the oldest ages and a ~ 0.5 dex spread in
metallicity. For stars with ages < 1 Gyr we find a smaller spread, consistent
with radial migration having a smaller effect on these young stars than on the
older stars.Comment: 14 page, 18 figures, accepted to ApJ with minor revisions, full
electronic table of data available upon publicatio
Issues Related to Academic Support and Performance of Division I Student-Athletes: A Case Study at the University of Minnesota
Environmental chemistry: A twenty year perspective: Air quality management
Anniversary article in ECG Bulleti
Excellentie van online leren
Boon, J., & Wagemans, L. J. J. M. (2013). Excellentie van online leren. OnderwijsInnovatie (1), 17-24.Dit artikel gaat over het evalueren van kwaliteit van e-learning. In het project E-xcellence is een globaal raamwerk ontwikkeld waarin zes domeinen onderscheiden worden die belangrijk zijn voor de kwaliteit van e-learning. Elk domein wordt concreter omschreven door een aantal benchmarks.
Door het uitvoeren van een quick scan kunnen teams van medewerkers in hoger onderwijsinstellingen een beeld krijgen van de kwaliteit van e-learning in hun organisatie, faculteit of in een cursus, in vergelijk met andere onderwijsinstellingen. Tevens kan aan de hand van een zelf uitgevoerde scan of aan de hand van een extern advies een plan gemaakt worden voor verbetering.: EU Lifelong Learning, Transversal Programme KA 4 Valorisatio
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