This paper explores the development of an intelligent translation system for spoken English using Recurrent Neural Network (RNN) models. The fundamental principles of RNNs and their advantages in processing sequential data, particularly in handling time-dependent natural language data, are discussed. The methodology for constructing the…

The paper discusses the implications of recent advances in artificial intelligence for knowledge workers, focusing on possible complementarities and substitution between machine translation tools and language professionals. The emergence of machine translation tools could enhance social welfare through enhanced opportunities for inter-language…

This study aims to investigate the manifestations of instrumental translation competence (ITC) in translator training programs in six Saudi universities. It explores students' knowledge and skills in ITC in terms of training and translation courses, translation tools, and usage patterns, drawing on the PACTE group of translation competence. In…

Recent developments in machine translation (MT) might have led some people to believe that soon professional translation will not be needed, but most translator trainers are aware of the high demand for the quality that MT systems cannot deliver without human intervention. It is thus important that professional translators, trainers and their…

The use of translation and interpreting (T&I) in the language learning classroom is commonplace, serving various pedagogical and assessment purposes. Previous utilization of T&I exercises is driven largely by their potential to enhance language learning, whereas the latest trend has begun to underscore T&I as a crucial skill to be…

The rapid adoption of online technologies to deliver postsecondary education amid the COVID-19 pandemic has highlighted the potential for online learning, as well as important equity gaps to be addressed. For over ten years, McMaster University has delivered graduate global health education through a blended-learning approach. In partnership with…

Machine translation is currently undergoing a paradigm shift from statistical to neural network models. Neural machine translation (NMT) is difficult to conceptualise for translation students, especially without context. This article describes a short in-class evaluation exercise to compare statistical and neural MT, including details of student…

The 13th iteration of the International Conference on Educational Data Mining (EDM 2020) was originally arranged to take place in Ifrane, Morocco. Due to the SARS-CoV-2 (coronavirus) epidemic, EDM 2020, as well as most other academic conferences in 2020, had to be changed to a purely online format. To facilitate efficient transmission of…

The work of connectionist researchers is examined in order to understand better the implications for modeling second language learning processes. Connectionism is a biologically-oriented framework for understanding complex behavior, and provides a modeling tool (computer simulation) that behaves and learns without rules being explicitly wired into…

Outlines the history of semantically based programs that have influenced the design of computer assisted language instruction (CALI) programs. Describes early attempts to make intelligent CALI as well as current projects, including the Foreign Language Adventure Game, developed at the University of Delaware. Describes some important…

It is proposed that research on neurological organization, cognitive psychology, and artificial intelligence can contribute to understanding the relationship between second language learning processes and academic achievement. Relevant research in these areas and in the field of neurolinguistics is reviewed, with several themes or topics…