Search results for "Genre"

2020

To validly assess teachers’ pedagogical content knowledge (PCK), performance-based tasks with open-response formats are required. Automated scoring is considered an appropriate ap-proach to reduce the resource-intensity of human scoring and to achieve more consistent scor-ing results than human raters. The focus is on the comparability of human and automated scor-ing of PCK for economics teachers. The answers of (prospective) teachers (N=852) to six open-response tasks from a standardized and validated test were scored by two trained human raters and the engine "Educational SCoRIng TOolkit" (ESCRITO). The average agreement between human and computer ratings, κw = .66, suggests a convergent …

Cell state prediction through distributed estimation of transmit power

2019

Determining the state of each cell, for instance, cell outages, in a densely deployed cellular network is a difficult problem. Several prior studies have used minimization of drive test (MDT) reports to detect cell outages. In this paper, we propose a two step process. First, using the MDT reports, we estimate the serving base station’s transmit power for each user. Second, we learn summary statistics of estimated transmit power for various networks states and use these to classify the network state on test data. Our approach is able to achieve an accuracy of 96% on an NS-3 simulation dataset. Decision tree, random forest and SVM classifiers were able to achieve a classification accuracy of…

Attention-based Model for Evaluating the Complexity of Sentences in English Language

2020

The automation of text complexity evaluation (ATCE) is an emerging problem which has been tackled by means of different methodologies. We present an effective deep learning- based solution which leverages both Recurrent Neural and the Attention mechanism. The developed system is capable of classifying sentences written in the English language by analysing their syntactical and lexical complexity. An accurate test phase has been carried out, and the system has been compared with a baseline tool based on the Support Vector Machine. This paper represents an extension of a previous deep learning model, which allows showing the suitability of Neural Networks to evaluate sentence complexity in tw…

Deep neural attention-based model for the evaluation of italian sentences complexity

2020

In this paper, the Automatic Text Complexity Evaluation problem is modeled as a binary classification task tackled by a Neural Network based system. It exploits Recurrent Neural Units and the Attention mechanism to measure the complexity of sentences written in the Italian language. An accurate test phase has been carried out, and the system has been compared with state-of-art tools that tackle the same problem. The computed performances proof the model suitability to evaluate sentence complexity improving the results achieved by other state-of-the-art systems.

The interpreter as a citizen diplomat

2019

Abstract The article presents a case of interpretation as a political activity during the Cold War. In the 1980s and 1990s, a grassroots citizen diplomacy movement was initiated by the Californian Esalen Institute, the center of the American Human Potential Movement. In and around its Soviet-American exchange program, numerous individuals, NGOs and organizations established personal relationships and professional exchange with citizens of the two super powers and travelled in both directions. Interpreters had a complex and crucial role in this exchange which was different from both the professional experience of conference and of communal interpreting.

Mitigation and boosting as face-protection functions

2020

Abstract Mitigation is undeniably and necessarily linked with the social aspect of communication. No speaker mitigates an utterance without a goal in mind, which makes mitigation a means to an end and not an end in itself. Even though the various definitions of mitigation do not assign the same aims to this phenomenon, the social impact it has on the participants in the communication is generally agreed upon throughout the literature (Fraser, 1980; Meyer-Hermann, 1988; Bazzanella et al., 1991; Briz, 1998, 2003; Caffi, 1999; Thaler, 2012; Briz and Albelda, 2013; Schneider, 2013; Albelda et al., 2014; Albelda, 2016, 2018). In this paper, the mitigating and boosting strategies in relationship …

Interpreter-mediated Interactions: Parent Participation in Individualized Education Plan Meetings for Deaf Students from Multilingual Homes

2020

This paper examines the ways in which parents of multilingual deaf children (are able to) participate in annual individualized education plan (IEP) meetings mediated by both signed and spoken langu...

Risks in neural machine translation

2020

Abstract The new paradigm of neural machine translation is leading to profound changes in the translation industry. Surprisingly good results have led to high expectations; however, there are substantial risks that have not yet been sufficiently taken into account. Risks exist on three levels: first, what kind of damage can clients and end users incur in safety-critical domains if the NMT result contains errors; second, who is liable for damage caused by the use of NMT; third, what cyber risks can the use of NMT entail, especially when free online engines are used. When establishing sustainable measures to reduce such risks, we also need to consider general principles of human behaviour if …

Training the translator trainers : an introduction

2019

This is an Accepted Manuscript of an article published by Taylor & Francis in [The Interpreter and Translator Trainer] on [09 Oct 2019], available online: http://www.tandfonline.com/10.1080/1750399X.2019.1647821

Why Digital Games Can Be Advantageous in Vocabulary Learning

2021

Vocabulary learning is an integral part of language learning; however, it is difficult. Although there are many techniques proposed for vocabulary learning and teaching, researchers still strive to find effective methods. Recently, digital games have shown potentials in enhancing vocabulary acquisition. A majority of studies in digital game-based vocabulary learning (DGBVL) literature investigate the effectiveness of DGBVL tasks. In other words, there are enough answers to what questions in DGBVL literature whereas why questions are rarely answered. Finding such answers help us learn more about the structure of the DGBVL tasks and their effects on vocabulary learning. Hence, to achieve this…