Search results for "e learning"
showing 10 items of 2703 documents
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…
Dynamic Functional Connectivity Captures Individuals’ Unique Brain Signatures
2020
Recent neuroimaging evidence suggest that there exists a unique individual-specific functional connectivity (FC) pattern consistent across tasks. The objective of our study is to utilize FC patterns to identify an individual using a supervised machine learning approach. To this end, we use two previously published data sets that comprises resting-state and task-based fMRI responses. We use static FC measures as input to a linear classifier to evaluate its performance. We additionally extend this analysis to capture dynamic FC using two approaches: the common sliding window approach and the more recent phase synchrony-based measure. We found that the classification models using dynamic FC pa…
Assessing the Level of Collaborative Writing in a Wiki-Based Environment: A Case Study in Teacher Education
2016
Wikis have received the last few years a growing interest as tools for supporting collaborative writing in teacher education. This paper reports on results from a case study that aimed at assessing the level of collaborative writing among teacher students. Taking advantages of wiki affordances, the proposed theoretical framework uses a taxonomy of category actions that can be carried out on wiki. These provide a powerful instrument to analyze students’ individual contributions to the wiki and level of collaborative writing among students as well. Implications for teacher preparation and professional development are drawn from the results and future research actions are envisaged to enhance …
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.
A Clustering approach for profiling LoRaWAN IoT devices
2019
Internet of Things (IoT) devices are starting to play a predominant role in our everyday life. Application systems like Amazon Echo and Google Home allow IoT devices to answer human requests, or trigger some alarms and perform suitable actions. In this scenario, any data information, related device and human interaction are stored in databases and can be used for future analysis and improve the system functionality. Also, IoT information related to the network level (wireless or wired) may be stored in databases and can be processed to improve the technology operation and to detect network anomalies. Acquired data can be also used for profiling operation, in order to group devices according…
Towards multilingual competence: examining beliefs and agency in first year university students’ language learner biographies
2021
As working life across the world is increasingly multilingual, multicultural and multidisciplinary, higher education language teaching is faced with a challenge of how to prepare students for it. Many universities have recently developed multilingual pedagogies but central to their success is learners’ perceptions of these practices. To fill this gap, this article explores first year university students’ language learner biographies to gain insight into how learners construct their linguistic realities. The biographies were studied with discourse analytical methods to examine the participants’ beliefs about language learning and their sense of agency in it. The results reveal that participa…
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…
Migrant women, work, and investment in language learning : Two success stories
2019
Abstract In the media, migrant mothers are often portrayed as uneducated, having trouble learning a new language, and preferring to stay at home rather than entering paid employment. This article offers a contrasting point of view as a result of examining how two migrant women narrativize their experiences of language learning and working-life-related integration during a three-year period. Specific attention is paid to how the women make sense of their language use over time, and how this may have contributed to their integration into working life and the wellbeing of their families. Interview data was analyzed using the short story analytical approach, focusing on both the content and the…
Multi-class Text Complexity Evaluation via Deep Neural Networks
2019
Automatic Text Complexity Evaluation (ATE) is a natural language processing task which aims to assess texts difficulty taking into account many facets related to complexity. A large number of papers tackle the problem of ATE by means of machine learning algorithms in order to classify texts into complex or simple classes. In this paper, we try to go beyond the methodologies presented so far by introducing a preliminary system based on a deep neural network model whose objective is to classify sentences into more of two classes. Experiments have been carried out on a manually annotated corpus which has been preprocessed in order to make it suitable for the scope of the paper. The results sho…