52,620 research outputs found
Innovative teaching strategies: enhancing the soft-skilloriented approach through integrated onsite-online learning environments
ABSTRACT
The integration of ICT in Higher Education requires reflective design by
teachers. In particular, from recent international research on the subject, it
emerges that the perspective of the TPCK framework (Technological, Pedagogical,
Content Knowledge) can favour an effective design reasoning of
teachers. Teaching practice requires the implementation of innovative organizational
models for the creation of learning environments that offer continuity
between classroom and distance learning (Hybrid Instruction
Solution). The empirical mix-method research involved a group of volunteer
teachers of different teachings. The objective was to design and implement
innovative teaching solutions using ICT in onsite/online environments to enhance
specific soft skills in students. The results of a questionnaire (CAWI)
given to incoming and outgoing teachers from the experience of designing
and conducting the didactic action will be presented. the TPCK perspective
design of integrated learning environments and the reasoned choice of coherent
methodologies seem to make a soft-skilloriented didactics feasible
Teacher education for effective technology integration
About a decade ago, several researchers used Shulman's (1986) framework about Pedagogical Content Knowledge (PCK) - a body of knowledge that constitutes a special amalgam of content, pedagogy, learners, and context - as a theoretical basis for developing TPCK or TPACK: a framework for guiding teachers' cognition about technology integration in teaching and learning (Angeli, Valanides, & Christodoulou, 2016). Different models of TPCK/TPACK are proposed in the literature, each with a different focus (on practice, instructional design, context, etc.) and with a different theoretical interpretation about the nature and development of the knowledge that teachers need to have to be able to teach with technology (e.g., Angeli & Valanides, 2005, 2009, 2013; Koehler & Mishra, 2008; Niess, 2005).In this direction, research is being carried out to identify TPCK design procedures for initial teacher education. In teaching, when transferring TPCK to design and methodological practices, there is a need to consider a number of factors, especially: the different modes of adopting technologies; the integration of tool affordances, content and pedagogy; the implementation of learning environments; the operationalization of knowledge; and detailed analysis of teaching models and approache
Hybrid spherical approximation
In this paper a local approximation method on the sphere is presented. As
interpolation scheme we consider a partition of unity method, such as the
modified spherical Shepard's method, which uses zonal basis functions (ZBFs)
plus spherical harmonics as local approximants. Moreover, a spherical zone
algorithm is efficiently implemented, which works well also when the amount of
data is very large, since it is based on an optimized searching procedure.
Numerical results show good accuracy of the method, also on real geomagnetic
data
Saturation Assumption and Finite Element Method for a One-Dimensional Model
In this paper we refer to the hierarchical finite element method and stabilization techniques for convectionâdiffusion equations. In particular, the aim is to outline an application of saturation assumption to a posteriori error estimates for such problems. We consider here a simple oneâdimensional model; the inequality is proved from an analitical point of view for the stabilized finite element solutions in two cases: artificial diffusion and SUPG stabilization techniques
Present and future trajectories towards a possible valid and useful diagnosis of ADHD
To date, diagnosing Attention Defi cit Hyperactivity Disorder remains indeed one of the most controversial issues in contemporary psychiatry and behavioural sciences. Most of the conceptual problems regarding the validity of this diagnostic category arise from the heterogeneity of syndromal pictures and the high rate of comorbidity observed in subjects diagnosed with ADHD at all stages of the longitudinal course of the disorder. In this regard, DSM 5 increased complexity by allowing a diagnosis of comorbidity between ADHD and autism spectrum disorders while these two diagnoses were mutually exclusive in DSM-IV-TR
A trivariate interpolation algorithm using a cube-partition searching procedure
In this paper we propose a fast algorithm for trivariate interpolation, which
is based on the partition of unity method for constructing a global interpolant
by blending local radial basis function interpolants and using locally
supported weight functions. The partition of unity algorithm is efficiently
implemented and optimized by connecting the method with an effective
cube-partition searching procedure. More precisely, we construct a cube
structure, which partitions the domain and strictly depends on the size of its
subdomains, so that the new searching procedure and, accordingly, the resulting
algorithm enable us to efficiently deal with a large number of nodes.
Complexity analysis and numerical experiments show high efficiency and accuracy
of the proposed interpolation algorithm
Adaptive meshless refinement schemes for RBF-PUM collocation
In this paper we present an adaptive discretization technique for solving
elliptic partial differential equations via a collocation radial basis function
partition of unity method. In particular, we propose a new adaptive scheme
based on the construction of an error indicator and a refinement algorithm,
which used together turn out to be ad-hoc strategies within this framework. The
performance of the adaptive meshless refinement scheme is assessed by numerical
tests
Time-Varying Quantiles
A time-varying quantile can be fitted to a sequence of observations by formulating a time series model for the corresponding population quantile and iteratively applying a suitably modified state space signal extraction algorithm. Quantiles estimated in this way provide information on various aspects of a time series, including dispersion,
asymmetry and, for financial applications, value at risk. Tests for the constancy of quantiles, and associated contrasts, are constructed using indicator variables; these tests have a similar form to stationarity tests and, under the null hypothesis, their asymptotic distributions belong to the Cramér von Mises family. Estimates of the quantiles at the end of the series provide the basis for forecasting. As such they offer an alternative to conditional quantile autoregressions and, at the same time, give some insight into their structure and potential drawbacks
Quantiles, Expectiles and Splines
A time-varying quantile can be fitted to a sequence of observations by formulating a time series model for the corresponding population quantile and iteratively applying a suitably modified state space signal extraction algorithm. It is shown that such time-varying quantiles satisfy the defining property of fixed quantiles in having the appropriate number of observations above and below. Expectiles are similar to quantiles except that they are defined by tail expectations. Like quantiles, time varying expectiles can be estimated by a state space signal extraction algorithm and they satisfy properties that generalize the moment conditions associated with fixed expectiles. Time-varying quantiles and expectiles provide information on various aspects of a time series, such as dispersion and asymmetry, while estimates at the end of the series provide the basis for forecasting. Because the state space form can handle irregularly spaced observations, the proposed algorithms can be easily adapted to provide a viable means of computing spline-based non-parametric quantile and expectile regressions
Efficient computation of partition of unity interpolants through a block-based searching technique
In this paper we propose a new efficient interpolation tool, extremely
suitable for large scattered data sets. The partition of unity method is used
and performed by blending Radial Basis Functions (RBFs) as local approximants
and using locally supported weight functions. In particular we present a new
space-partitioning data structure based on a partition of the underlying
generic domain in blocks. This approach allows us to examine only a reduced
number of blocks in the search process of the nearest neighbour points, leading
to an optimized searching routine. Complexity analysis and numerical
experiments in two- and three-dimensional interpolation support our findings.
Some applications to geometric modelling are also considered. Moreover, the
associated software package written in \textsc{Matlab} is here discussed and
made available to the scientific community
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