Dialogue act (DA) classification plays an important role in understanding, interpreting and modeling dialogue. Dialogue acts (DAs) represent the intended meaning of an utterance, which is associated with the illocutionary force (or the speaker's intention), such as greetings, questions, requests, statements, and agreements. In natural language…

In this investigation we propose new machine learning methods for automated scoring models that predict the vocabulary acquisition in science and social studies of second grade English language learners, based upon free-form spoken responses. We evaluate performance on an existing dataset and use transfer learning from a large pre-trained language…

Advances in machine learning (ML) are poised to contribute to our understanding of the linguistic processes associated with successful reading comprehension, which is a critical aspect of children's educational success. We used ML techniques to investigate and compare associations between children's reading comprehension and 260 linguistic…

We examine the ability of supervised text classification models to identify several discourse properties from teachers' speech with an eye for providing teachers with meaningful automated feedback about the quality of their classroom discourse. We collected audio recordings from 28 teachers from 10 schools in 164 authentic classroom sessions,…

The purpose of the study is to provide a literature review of the work done on sign language (SL) around the world and in Pakistan and to develop a translation tool of speech and text to Pakistan Sign Language (PSL) with bilingual subtitles. Information and communication technology and tools development for teaching and learning purposes improve…

This article is an exploration of the available applications for speech to speech real-time translation software for use in the classroom. Three different types of machine language translation (MLT) software and devices are reviewed for their features and practical application in secondary education classrooms.