The promises of educational technology: a reassessment

The claims made for educational technology have not always been realized. Many programmes in education based on media and technology have produced useful documentation and supportive research; others have failed. The current, comprehensive definition of educational technology is a helpful key to understanding how a problem-solving orientation is necessary to approach teaching/learning designs. The process of educational technology begins with an analysis of the problem, rather than with the medium as a solution. Examples of appropriate applications come from open universities and primary schools where distance, time, insufficient personnel, and inadequate facilities have led to a search for alternative means for teaching and learning. Less successful programmes tended to have confused goals and an emphasis on one medium. They also lacked: support services, staff training, quality software and a system focus. The threads which run through the more successful programmes are described. The lessons learned from fifty years of media and technology development in education and training are discussed with an eye toward the future. It is clear that educational technology as a problem-solving process will lead the field into the twenty-first century

Determinants of Point-of-Sale System Adoption: A Survey among Small Retailers in The Netherlands

Several threats affect the survival of small, independent retail companies. Adoption and use of Point-of-Sale (POS) systemsmay offer important benefits to counter these threats. POS systems are not widely used by these retailers, however. Thisresearch investigates the determinants of the adoption of POS systems using a conceptual model based on existing adoptiontheories. Based on this, a survey has been held among 37 Dutch small, independent retailers, to answer the question what themost important determinants for POS system adoption are. This study furthers theory on IT adoption, specifically for smallorganisations. The practical relevance is that its findings may help in improving POS system adoption

Design research in mathematics education : the case of an ict-rich learning arrangement for the concept of function

The concept of function is a central but difficult topic in secondary school mathematics curricula, which encompasses a transition from an operational to a structural view. The question in this paper is how to design and evaluate a technology-rich learning arrangement that may foster this transition. With domain-specific pedagogical knowledge on the learning of function as a starting point, and the notions of emergent modeling and instrumentation as design heuristics, such a learning arrangement was designed for grade 8 students and field tested. The results suggest that these design heuristics provide fruitful guidelines for the design of both a hypothetical learning trajectory and concrete tasks, and can be generalized to other design processes

Time-varying effective EEG source connectivity: the optimization of model parameters*

Adaptive estimation methods based on general Kalman filter are powerful tools to investigate brain networks dynamics given the non-stationary nature of neural signals. These methods rely on two parameters, the model order p and adaptation constant c, which determine the resolution and smoothness of the time-varying multivariate autoregressive estimates. A sub-optimal filtering may present consistent biases in the frequency domain and temporal distortions, leading to fallacious interpretations. Thus, the performance of these methods heavily depends on the accurate choice of these two parameters in the filter design. In this work, we sought to define an objective criterion for the optimal choice of these parameters. Since residual- and information-based criteria are not guaranteed to reach an absolute minimum, we propose to study the partial derivatives of these functions to guide the choice of p and c. To validate the performance of our method, we used a dataset of human visual evoked potentials during face perception where the generation and propagation of information in the brain is well understood and a set of simulated data where the ground truth is available

Estimating EEG Source Dipole Orientation Based on Singular-value Decomposition for Connectivity Analysis.

In the last decade, the use of high-density electrode arrays for EEG recordings combined with the improvements of source reconstruction algorithms has allowed the investigation of brain networks dynamics at a sub-second scale. One powerful tool for investigating large-scale functional brain networks with EEG is time-varying effective connectivity applied to source signals obtained from electric source imaging. Due to computational and interpretation limitations, the brain is usually parcelled into a limited number of regions of interests (ROIs) before computing EEG connectivity. One specific need and still open problem is how to represent the time- and frequency-content carried by hundreds of dipoles with diverging orientation in each ROI with one unique representative time-series. The main aim of this paper is to provide a method to compute a signal that explains most of the variability of the data contained in each ROI before computing, for instance, time-varying connectivity. As the representative time-series for a ROI, we propose to use the first singular vector computed by a singular-value decomposition of all dipoles belonging to the same ROI. We applied this method to two real datasets (visual evoked potentials and epileptic spikes) and evaluated the time-course and the frequency content of the obtained signals. For each ROI, both the time-course and the frequency content of the proposed method reflected the expected time-course and the scalp-EEG frequency content, representing most of the variability of the sources (~ 80%) and improving connectivity results in comparison to other procedures used so far. We also confirm these results in a simulated dataset with a known ground truth

A Translational Model for Repeated Episodes of Joint Inflammation : Welfare, Clinical and Synovial Fluid Biomarker Assessment

This study investigates repeated low-dose lipopolysaccharide (LPS) injections in equine joints as a model for recurrent joint inflammation and its impact on animal welfare. Joint inflammation was induced in eight horses by injecting 0.25 ng of LPS three times at two-week intervals. Welfare scores and clinical parameters were recorded at baseline and over 168 h post-injection. Serial synoviocentesis was performed for the analysis of a panel of synovial fluid biomarkers of inflammation and cartilage turnover. Clinical parameters and a final synoviocentesis were also performed eight weeks after the last sampling point to assess the recovery of normal joint homeostasis. Statistical methods were used to compare the magnitude of response to each of the 3 LPS inductions and to compare the baseline and final measurements. Each LPS injection produced consistent clinical and biomarker responses, with minimal changes in welfare scores. General matrix metalloproteinase (MMP) activity and joint circumference showed greater response to the second LPS induction, but response to the third was comparable to the first. Gylcosaminoglycans (GAG) levels showed a significantly decreased response with each induction, while collagen-cleavage neoepitope of type II collagen (C2C) and carboxypropetide of type II collagen epitope (CPII) showed quicker responses to the second and third inductions. All parameters were comparable to baseline values at the final timepoint. In conclusion, a consistent, reliable intra-articular inflammatory response can be achieved with repeated injections of 0.25 ng LPS, with minimal impact on animal welfare, suggesting potential as a refined translational model of recurrent joint inflammation

Affinity purification of erythropoietin from cell culture supernatant combined with MALDI-TOF-MS analysis of erythropoietin N-glycosylation

Proteomic

Porosity of silica Stöber particles determined by spin-echo small angle neutron scattering.

Stöber silica particles are used in a diverse range of applications. Despite their widespread industrial and scientific uses, information on the internal structure of the particles is non-trivial to obtain and is not often reported. In this work we have used spin-echo small angle neutron scattering (SESANS) in conjunction with ultra small angle X-ray scattering (USAXS) and pycnometry to study an aqueous dispersion of Stöber particles. Our results are in agreement with models which propose that Stöber particles have a porous core, with a significant fraction of the pores inaccessible to solvent. For samples prepared from the same master sample in a range of H2O : D2O ratio solutions we were able to model the SESANS results for the solution series assuming monodisperse, smooth surfaced spheres of radius 83 nm with an internal open pore volume fraction of 32% and a closed pore fraction of 10%. Our results are consistent with USAXS measurements. The protocol developed and discussed here shows that the SESANS technique is a powerful way to investigate particles much larger than those studied using conventional small angle scattering methods