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Previous research investigating the use of technology in school has focused mainly on the frequency of use of digital tools during lessons rather than investigating how technology is integrated with respect to different kinds of learning activities. Since the impact of technology use on learning depends on how it is used and on what activities supported by technology are implemented in lessons, a measurement instrument assessing how technology is integrated into learning activities is necessary to investigate its impact on teaching and learning processes. According to the interactive, constructive, active, and passive (ICAP) framework, which distinguishes four different learning activities based on the level of students’ cognitive engagement, we developed the 12-item ICAP Technology Scale (ICAP-TS) that accounts for all four dimensions of technology integration in lessons. We used confirmatory factor analysis to validate the four-factor structure of the ICAP-TS with a sample of 1059 upper-secondary school teachers from Switzerland. We also examined reliability using classical test theory and Rasch model analysis to assess the scale’s psychometric characteristics. We then analyzed the associations between the ICAP-TS and a general use frequency measure of 12 educational technologies to test the criterion validity. The results confirmed the four-factor structure of the ICAP-TS and revealed good instrument accuracy. The most difficult items to endorse are those describing the integration of technology into interactive learning activities. Furthermore, all 12 items significantly correlated with the frequency of use of 12 educational technologies. We recommend the ICAP-TS as a short and reliable measurement scale for assessing how technology is integrated into lessons, considering different learning activities based on the ICAP theoretical model.

We are interested in building schemes for the compressible Euler equations that are also locally conserving the angular momentum. We present a general framework, describe a few examples of schemes and show results. These schemes can be of arbitrary order.

Many researchers have investigated how barriers to technology integration affect the use of digital technologies in teaching and learning. However, the results have varied across educational contexts and countries. Large-scale assessment studies have described barriers only on a descriptive level instead of analyzing the effects of barriers on actual indicators of technology integration, such as technology use. Therefore, this study investigated the effects of barriers on technology use through the lens of the “will, skill, tool” model (WST model) in different European countries while taking the countries’ technological development level into account. A regression analysis showed that barriers had only a minor impact on the frequency of technology use in the classroom in the large majority of countries. In accordance with theoretical expectations, we found country-specific patterns, with a higher negative impact of technological barriers in less technologically developed countries and teacher-belief related barriers prevalent in developed countries. These findings may help policy makers identify needed interventions in different contexts.

Invasive Brain-Computer Interfaces (BCIs) are extensively used in medical application scenarios to record, stimulate, or inhibit neural activity with different purposes. An example is the stimulation of some brain areas to reduce the effects generated by Parkinson’s disease. Despite the advances in recent years, cybersecurity on BCIs is an open challenge since attackers can exploit the vulnerabilities of invasive BCIs to induce malicious stimulation or treatment disruption, affecting neuronal activity. In this work, we design and implement a novel neuronal cyberattack called Neuronal Jamming (JAM), which prevents neurons from producing spikes. To implement and measure the JAM impact, and due to the lack of realistic neuronal topologies in mammalians, we have defined a use case using a Convolutional Neural Network (CNN) trained to allow a simulated mouse to exit a particular maze. The resulting model has been translated to a biological neural topology, simulating a portion of a mouse’s visual cortex. The impact of JAM on both biological and artificial networks is measured, analyzing how the attacks can both disrupt the spontaneous neural signaling and the mouse’s capacity to exit the maze. Besides, another contribution of the work focuses on comparing the impacts of both JAM and FLO (an existing neural cyberattack), demonstrating that JAM generates a higher impact in terms of neuronal spike rate. As a final contribution, we discuss whether and how JAM and FLO attacks could induce the effects of neurodegenerative diseases if the implanted BCI had a comprehensive electrode coverage of the targeted brain regions.

In the present work, a method for solving partial differential equations with uncertainties is presented. A multiresolution method, permitting to compute statistics for the entire solution and in presence of a whatever form of the probability density function, is extended to perform an adaptation in both physical and stochastic spaces. The efficiency of this strategy, in terms of refinement/coarsening capabilities, is demonstrated on several test-cases by comparing with respect to other more classical techniques, namely Monte Carlo (MC) and Polynomial Chaos (PC). Finally, the proposed strategy is applied to the heat equation showing very promising results in terms of accuracy, convergence and regularity.

This paper provides the status of the Sentinel -1B performance as at a few weeks after launch.

Technological Pedagogical Content Knowledge (TPACK) is regarded as one of the most important models describing teachers' competencies for successfully teaching with technology. TPACK is most frequently assessed by means of self-report questionnaires, which beside their inherent methodological limitations present constraints related either to the validity, reliability, or practical applicability of existing instruments. Furthermore, the internal structure of the TPACK framework is a topic of debate. The two goals of this study were (1) to develop a valid and reliable short questionnaire for measuring TPACK (TPACK.xs), and (2) to use this instrument to investigate TPACK's internal relations, assessing whether the framework reflects an integrative or a transformative view regarding how the TPACK knowledge domains interact. An initial questionnaire of 42 items was administered to 117 pre-service upper secondary school teachers. Reliability analysis and confirmatory factor analysis were used to reduce the number of items per subscale and fit the model. Structural equation modelling investigated the internal relations between components. Results show that the final TPACK.xs questionnaire, consisting of 28 items, can be considered a valid and reliable instrument for assessing pre-service teachers' TPACK. Furthermore, the internal relations of knowledge components support a transformative view of the TPACK model.

We present a highly parallelizable and flexible computational method to solve high-dimensional stochastic dynamic economic models. Solving such models often requires the use of iterative methods, like time iteration or dynamic programming. By exploiting the generic iterative structure of this broad class of economic problems, we propose a parallelization scheme that favors hybrid massively parallel computer architectures. Within a parallel nonlinear time iteration framework, we interpolate policy functions partially on GPUs using an adaptive sparse grid algorithm with piecewise linear hierarchical basis functions. GPUs accelerate this part of the computation one order of magnitude thus reducing overall computation time by 50%. The developments in this paper include the use of a fully adaptive sparse grid algorithm and the use of a mixed MPI-Intel TBB-CUDA/Thrust implementation to improve the interprocess communication strategy on massively parallel architectures. Numerical experiments on “Piz Daint” (Cray XC30) at the Swiss National Supercomputing Centre show that high-dimensional international real business cycle models can be efficiently solved in parallel. To the best of our knowledge, this performance on a massively parallel petascale architecture for such nonlinear high-dimensional economic models has not been possible prior to present work.

In this work we give three small spiking neural P systems. We begin by constructing a universal spiking neural P system with extended rules and only 4 neurons. This is the smallest possible number of neurons for a universal system of its kind. We prove this by showing that the set of problems solved by spiking neural P systems with 3 neurons is bounded above by NLNL, and so there exists no such universal system with 3 neurons. If we generalise the output technique we immediately find a universal spiking neural P system with extended rules that has only 3 neurons. This is also the smallest possible number of neurons for a universal system of its kind. Finally, we give a universal spiking neural P system with standard rules and only 7 neurons. In addition to giving a significant improvement in terms of reducing the number of neurons, our systems also offer an exponential improvement on the time and space overheads of the small universal spiking neural P systems of other authors.

Maximum distance profile codes are characterized by the property that two trajectories which start at the same state and proceed to a different state will have the maximum possible distance from each other relative to any other convolutional code of the same rate and degree. In this paper we use methods from systems theory to characterize maximum distance profile codes algebraically. Tha main result shows that maximum distance profile codes form a generic set inside the variety which parametrizes the set of convolutional codes of a fixed rate and a fixed degree., Comment: 15 pages, submitted to Systems and Control Letters, corrected date

Information and communication technologies are in the process of transforming the way business is conducted in a large number of industries. The impact of this change is not well understood. This paper develops a research agenda that helps to investigate the implications of information and communication technology on selected management fields. In particular, the implications are investigated for strategic management, demand and supply chain management, logistics, organization and leadership, and management education. The research agenda is developed by first identifying impacts of information and communication technologies in the domains discussed. From these impacts, research needs are derived.