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Hsiao-Ling Hsu; Howard Hao-Jan Chen; Andrew G. Todd – Interactive Learning Environments, 2023
With advances in technology, intelligent personal assistants (IPAs) have become available to assist users with a variety of tasks using voice commands. Because IPAs may induce dialogic interactions, researchers speculated that they may benefit second language learning, especially regarding pronunciation, listening and speaking skills. So far, very…
Descriptors: Foreign Countries, College Students, English (Second Language), Artificial Intelligence
Ranalli, Jim; Yamashita, Taichi – Language Learning & Technology, 2022
To the extent automated written corrective feedback (AWCF) tools such as Grammarly are based on sophisticated error-correction technologies, such as machine-learning techniques, they have the potential to find and correct more common L2 error types than simpler spelling and grammar checkers such as the one included in Microsoft Word (technically…
Descriptors: Error Correction, Feedback (Response), Computer Software, Second Language Learning
Taylor, Joshua; Kochem, Timothy – Diaspora, Indigenous, and Minority Education, 2022
Technology has paved the way for new modalities in language learning; however, indigenous populations often lack access to these tools. This critical literature review examines how researchers have tried to overcome this hurdle by reaching out to marginalized indigenous populations and providing access to emerging technologies. We used 63 texts…
Descriptors: Second Language Learning, Second Language Instruction, Language Maintenance, Indigenous Populations
Qiao Wang; Ralph L. Rose; Ayaka Sugawara; Naho Orita – Vocabulary Learning and Instruction, 2025
VocQGen is an automated tool designed to generate multiple-choice cloze (MCC) questions for vocabulary assessment in second language learning contexts. It leverages several natural language processing (NLP) tools and OpenAI's GPT-4 model to produce MCC items quickly from user-specified word lists. To evaluate its effectiveness, we used the first…
Descriptors: Vocabulary Skills, Artificial Intelligence, Computer Software, Multiple Choice Tests
Tsiola, Anna – ProQuest LLC, 2021
Naturalistic language learning is contextually grounded. When people learn their first (L1) and often their second (L2) language, they do so in various contexts. In this dissertation I examine the effect of various contexts on language development. Part 1 describes the effects of textual, linguistic context in reading. I employed an eye-tracking…
Descriptors: Natural Language Processing, Second Language Learning, Language Processing, Language Acquisition
Stephanie Link; Robert Redmon; Yaser Shamsi; Martin Hagan – CALICO Journal, 2024
Artificial intelligence (AI) for supporting second language (L2) writing processes and practices has garnered increasing interest in recent years, establishing AI-mediated L2 writing as a new norm for many multilingual classrooms. As such, the emergence of AI-mediated technologies has challenged L2 writing instructors and their philosophies…
Descriptors: English for Academic Purposes, Teaching Methods, Second Language Learning, Second Language Instruction
Belda-Medina, Jose; Kokošková, Vendula – International Journal of Educational Technology in Higher Education, 2023
Recent advances in Artificial Intelligence (AI) have paved the way for the integration of text-based and voice-enabled chatbots as adaptive virtual tutors in education. Despite the increasing use of AI-powered chatbots in language learning, there is a lack of studies exploring the attitudes and perceptions of teachers and students towards these…
Descriptors: Technology Integration, Technology Uses in Education, Artificial Intelligence, Man Machine Systems
Writing to Increase Complexity: Spanish L2 Learners' Complexity Gains in a College Composition Class
Restrepo-Ramos, Falcon – Hispania, 2021
This study examines the linguistic complexity of Spanish as a second language (L2) in learners' essays across proficiency levels at two timelines of a composition class during a college semester. Data comes from 22 L2 learners of Spanish enrolled in two sections of a third-year composition class at the college level, who were assigned nine…
Descriptors: Spanish, Writing Instruction, Second Language Learning, Second Language Instruction
Keezhatta, Muhammed Salim – Arab World English Journal, 2019
Natural Language Processing (NLP) platforms have recently reported a higher adoption rate of Artificial Intelligence (AI) applications. The purpose of this research is to examine the relationship between NLP and AI in the application of linguistic tasks related to morphology, parsing, and semantics. To achieve this objective, a theoretical…
Descriptors: Models, Correlation, Natural Language Processing, Artificial Intelligence
Degraeuwe, Jasper; Goethals, Patrick – Research-publishing.net, 2022
This paper presents a reflection on the design of an Intelligent Computer-Assisted Language Learning (ICALL) 'ecosystem', integrated into an online learning environment for Spanish as a Foreign Language (SFL). The innovative dimension of the ecosystem lies in its triple focus: apart from enabling users to create and use intelligent language…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, Spanish
Zhongdi Wu; Eric Larson; Makoto Sano; Doris Baker; Nathan Gage; Akihito Kamata – Grantee Submission, 2023
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…
Descriptors: Prediction, Vocabulary Development, English (Second Language), Second Language Learning
Sari, Elif; Han, Turgay – Reading Matrix: An International Online Journal, 2021
Providing both effective feedback applications and reliable assessment practices are two central issues in ESL/EFL writing instruction contexts. Giving individual feedback is very difficult in crowded classes as it requires a great amount of time and effort for instructors. Moreover, instructors likely employ inconsistent assessment procedures,…
Descriptors: Automation, Writing Evaluation, Artificial Intelligence, Natural Language Processing
Tafazoli, Dara; María, Elena Gómez; Huertas Abril, Cristina A. – International Journal of Information and Communication Technology Education, 2019
Intelligent computer-assisted language learning (ICALL) is a multidisciplinary area of research that combines natural language processing (NLP), intelligent tutoring system (ITS), second language acquisition (SLA), and foreign language teaching and learning (FLTL). Intelligent tutoring systems (ITS) are able to provide a personalized approach to…
Descriptors: Intelligent Tutoring Systems, Computer Assisted Instruction, Teaching Methods, Interdisciplinary Approach
Kim, Byungsoo; Yu, Hangyeol; Shin, Dongmin; Choi, Youngduck – International Educational Data Mining Society, 2021
The needs for precisely estimating a student's academic performance have been emphasized with an increasing amount of attention paid to Intelligent Tutoring System (ITS). However, since labels for academic performance, such as test scores, are collected from outside of ITS, obtaining the labels is costly, leading to label-scarcity problem which…
Descriptors: Academic Achievement, Intelligent Tutoring Systems, Prediction, Scores
Timpe-Laughlin, Veronika; Sydorenko, Tetyana; Daurio, Phoebe – Computer Assisted Language Learning, 2022
Often, second/foreign (L2) language learners receive little opportunity to interact orally in the target language. Interactive, conversation-based spoken dialog systems (SDSs) that use automated speech recognition and natural language processing have the potential to address this need by engaging learners in meaningful, goal-oriented speaking…
Descriptors: Second Language Learning, Second Language Instruction, Oral Language, Dialogs (Language)

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