This study aimed at providing learners with an opportunity not only to bring together their core and disciplinary knowledge to acquire major skills of learning English as a foreign language (EFL), and the intellectual challenge of these issues at the interface of media, language and religion, but also help the materials generators to produce suitable types of content to be delivered through the...

Modeling informal inference in natural language is very challenging. With the recent availability of large annotated data, it has become feasible to train complex models such as neural networks to perform natural language inference (NLI), which have achieved state-of-the-art performance. Although there exist relatively large annotated data, can machines learn all knowledge needed to perform NLI...

We present a novel deep learning architecture to address the natural language inference (NLI) task. Existing approaches mostly rely on simple reading mechanisms for independent encoding of the premise and hypothesis. Instead, we propose a novel dependent reading bidirectional LSTM network (DR-BiLSTM) to efficiently model the relationship between a premise and a hypothesis during encoding and in...

Our efforts in the 2013 NLI shared task focused on the potential benefits of external corpora. We show that including training data from multiple corpora is highly effective at robust, cross-corpus NLI (i.e. open-training task 1), particularly when some form of domain adaptation is also applied. This method can also be used to boost performance even when training data from the same corpus is av...

This paper presents an ensemble system combining the output of multiple SVM classifiers to native language identification (NLI). The system was submitted to the NLI Shared Task 2017 fusion track which featured students essays and spoken responses in form of audio transcriptions and iVectors by non-native English speakers of eleven native languages. Our system competed in the challenge under the...

Neuroimaging studies of audiovisual speech processing have exclusively addressed listeners' native language (L1). Yet, several behavioural studies now show that AV processing plays an important role in non-native (L2) speech perception. The current fMRI study measured brain activity during auditory, visual, audiovisual congruent and audiovisual incongruent utterances in L1 and L2. BOLD response...

Digital divide can be considered a macro economical index representing the social differences and the separation between the North and the South of the world. Since the first definition of digital divide, it has been shown that it is also a great and unrecognized problem in the developed countries, especially in the field of education. “Digital disconnection” is a key problem for School and Uni...

In this paper, we explore spelling errors as a source of information for detecting the native language of a writer, a previously under-explored area. We note that character n-grams from misspelled words are very indicative of the native language of the author. In combination with other lexical features, spelling error features lead to 1.2% improvement in accuracy on classifying texts in the TOE...

With growing exposure of children to handheld and mobile devices, there is an increasing interest in exploring the use of mobile technology for educational purposes. In particular, touch-based devices seem to promise great potential in this domain. In this paper, we present Math Tutor – an Android-based application designed to help children learn and practice early numeracy addition and subtrac...