Search results for "e learning"
showing 10 items of 2703 documents
Secondary school students’ collaboration during dyadic debates face-to-face and through computer chat
2009
Communicative competence needed in today's constructive learning environments both in virtual and physical classrooms requires most of all critical and argumentative thinking skills as well as abilities to use reciprocal and collaborative language. This study clarifies the quality of secondary school students' collaboration in dyadic face-to-face and computer chat debates during argumentative discussions. The speech acts produced in 24 debates were first classified into either on-task or off-task categories. The on-task speech acts were then further classified into six collaborative and two non-collaborative categories. The students commonly presented questions and made requests for clarifi…
Why we need TI-Oriented Language Learning and Teaching
2021
The teaching of foreign languages to students in Translation and Interpreting (TI) programmes should be framed within the field of Language for Specific Purposes (LSP). This would make it possible to pinpoint specific curricular content and methodological traits that contribute to the enhancement of the communicative competence and initial development of TI competences. This paper analyses the students’ perspectives on L2 teaching in a TI programme and how it should be undertaken to best comply with the linguistic demands imposed by translation and interpreting. A thematic analysis of 117 open questionnaires returned by students from Austria, Slovenia and Spain identified five areas to whic…
Practice and assessment of oral skills in developing online preparatory materials through the InGenio authoring shell
2012
The practice of oral skills is a basic requirement of learning or teaching a new language, as one of the main goals in the field of language learning is developing oral communicative competence, especially needed in contexts where the students¿ L2 is the vehicular language and therefore the main means of interaction. The InGenio online authoring tool allows designers of new materials, as well as language teachers and students, to rethink and imagine new ways of dealing with practice and assessment of listening and speaking skills thanks to the flexibility of its templates, resources and tools. This article explores the ways in which the InGenio utilities, solutions and learning materials ar…
Transformative Teaching and Learning Through Engaged Practice : Lecturers’ and Students’ Experiences in a University and Underserved Community Partne…
2018
peer-reviewed The Community Wellness, Empowerment, Leadership and Lifeskills (CWell) program is a two-year community-driven program developed in partnership between an underserved-community in Limerick City, and staff at the University of Limerick (UL), Ireland. This paper explores the transformative teaching and learning experiences that arose throughout the duration of the progam for the lecturers and students. Data were collected through interviews and focus groups with lecturers and students involved in the program. Students supported the notion of “learning differently” and focused around prior learning and attitude to learning, learning about learning and impact of learning. Lecturers…
Incremental Generalized Discriminative Common Vectors for Image Classification.
2015
Subspace-based methods have become popular due to their ability to appropriately represent complex data in such a way that both dimensionality is reduced and discriminativeness is enhanced. Several recent works have concentrated on the discriminative common vector (DCV) method and other closely related algorithms also based on the concept of null space. In this paper, we present a generalized incremental formulation of the DCV methods, which allows the update of a given model by considering the addition of new examples even from unseen classes. Having efficient incremental formulations of well-behaved batch algorithms allows us to conveniently adapt previously trained classifiers without th…
On the Online Classification of Data Streams Using Weak Estimators
2016
In this paper, we propose a novel online classifier for complex data streams which are generated from non-stationary stochastic properties. Instead of using a single training model and counters to keep important data statistics, the introduced online classifier scheme provides a real-time self-adjusting learning model. The learning model utilizes the multiplication-based update algorithm of the Stochastic Learning Weak Estimator (SLWE) at each time instant as a new labeled instance arrives. In this way, the data statistics are updated every time a new element is inserted, without requiring that we have to rebuild its model when changes occur in the data distributions. Finally, and most impo…
Day-ahead forecasting for photovoltaic power using artificial neural networks ensembles
2016
Solar photovoltaic plants power output forecasting using machine learning techniques can be of a great advantage to energy producers when they are implemented with day-ahead energy market data. In this work a model was developed using a supervised learning algorithm of multilayer perceptron feedforward artificial neural network to predict the next twenty-four hours (day-ahead) power of a solar facility using fetched weather forecast of the following day. Each set of tested network configuration was trained by the historical power output of the plant as a target. For each configuration, one hundred networks ensembles was averaged to give the ability to generalize a better forecast. The train…
Towards more Valid Assessment of Learning from Animations
2020
Animated explanations have become an ubiquitous feature of modern educational practice. They provide a distinctive, non-verbal means of presenting information that is particularly appropriate for dynamic subject matter. However, the prevailing approaches used to assess learning from educational animations are almost exclusively verbal. There is thus a clear disconnect between the form of representation students encounter during their learning activity and the very different form of representation used to assess the resulting learning outcomes. This fundamental inconsistency undermines the validity of current assessment approaches and signals the need for a fresh look at how learning from an…
Local operators to detect regions of interest
1997
The performance of a visual system is strongly influenced by the information processing that is done in the early vision phase. The need exists to limit the computation on areas of interest to reduce the total amount of data and their redundancy. This paper describes a new method to drive the attention during the analysis of complex scenes. Two new local operators, based on the computation of local moments and symmetries, are combined to drive the selection. Experimental results on real data are also reported. © 1997 Elsevier Science B.V.
Approximation of functions over manifolds : A Moving Least-Squares approach
2021
We present an algorithm for approximating a function defined over a $d$-dimensional manifold utilizing only noisy function values at locations sampled from the manifold with noise. To produce the approximation we do not require any knowledge regarding the manifold other than its dimension $d$. We use the Manifold Moving Least-Squares approach of (Sober and Levin 2016) to reconstruct the atlas of charts and the approximation is built on-top of those charts. The resulting approximant is shown to be a function defined over a neighborhood of a manifold, approximating the originally sampled manifold. In other words, given a new point, located near the manifold, the approximation can be evaluated…