Publication Date
| In 2026 | 0 |
| Since 2025 | 3 |
| Since 2022 (last 5 years) | 10 |
| Since 2017 (last 10 years) | 19 |
| Since 2007 (last 20 years) | 20 |
Descriptor
| Artificial Intelligence | 20 |
| Linguistic Input | 20 |
| Computational Linguistics | 11 |
| Computer Software | 11 |
| Second Language Learning | 9 |
| Learning Processes | 8 |
| Models | 8 |
| Second Language Instruction | 8 |
| Teaching Methods | 8 |
| English (Second Language) | 7 |
| Foreign Countries | 7 |
| More ▼ | |
Source
Author
| Dascalu, Mihai | 2 |
| McNamara, Danielle S. | 2 |
| Nicula, Bogdan | 2 |
| Orcutt, Ellen | 2 |
| Alex Warstadt | 1 |
| Alireza Aghaei | 1 |
| Alsadoon, Reem | 1 |
| Anindita Dewangga Puri | 1 |
| Ayesha Juhi | 1 |
| Bonner, Euan | 1 |
| Chabchoub, Habib | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 13 |
| Reports - Research | 10 |
| Dissertations/Theses -… | 4 |
| Reports - Evaluative | 3 |
| Information Analyses | 2 |
| Books | 1 |
| Collected Works - General | 1 |
| Speeches/Meeting Papers | 1 |
| Tests/Questionnaires | 1 |
Education Level
| Higher Education | 6 |
| Postsecondary Education | 6 |
| Elementary Education | 1 |
| Elementary Secondary Education | 1 |
| Secondary Education | 1 |
Audience
| Teachers | 2 |
| Researchers | 1 |
Location
| Hong Kong | 2 |
| Greece | 1 |
| India | 1 |
| Indonesia | 1 |
| Saudi Arabia | 1 |
| South Africa | 1 |
| Spain | 1 |
| Thailand | 1 |
| Turkey | 1 |
| United Arab Emirates (Abu… | 1 |
Laws, Policies, & Programs
Assessments and Surveys
| International English… | 1 |
What Works Clearinghouse Rating
Preet Chandan Kaur; Leena Ragha – Education and Information Technologies, 2025
Video summarization is a method of deducing the content of video content for generating a summary in video format. The generated summary should have the significant segments of raw video. Recently, the content of video has been rapidly increasing, thus automatic video summarization is beneficial for individuals who want to keep time and learn more…
Descriptors: Semantics, Video Technology, Audio Equipment, Linguistic Input
Qihui Xu – ProQuest LLC, 2022
How early do children produce multiword utterances? Do children's early utterances reflect abstract syntactic knowledge or are they the result of data-driven learning? We examine this issue through corpus analysis, computational modeling, and adult simulation experiments. Chapter 1 investigates when children start producing multiword utterances;…
Descriptors: Language Acquisition, Speech Communication, Computational Linguistics, Syntax
FX. Risang Baskara; Anindita Dewangga Puri; Concilianus Laos Mbato – Language Teaching Research Quarterly, 2024
The rapid advancement of Artificial intelligence (AI) technologies has made new opportunities available in language education. This qualitative study investigates using generative AI tools by university English as a Foreign Language (EFL) students to create podcasts for language learning. The research was based on 80 undergraduate students who…
Descriptors: Audio Equipment, Teaching Methods, English (Second Language), Undergraduate Students
Montri Tangpijaikul – LEARN Journal: Language Education and Acquisition Research Network, 2025
Despite the significant impact of the lexical approach for vocabulary learning, its classroom implementation has not been uniform. While related activities share the common Observe-Hypothesize-Experiment (OHE) elements, practitioners and researchers do not highlight how language input from the observing stage is turned into output and at what…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Teaching Methods
Alex Warstadt – ProQuest LLC, 2022
Data-driven learning uncontroversially plays a role in human language acquisition--how large a role is a matter of much debate. The success of artificial neural networks in NLP in recent years calls for a re-evaluation of our understanding of the possibilities for learning grammar from data alone. This dissertation argues the case for using…
Descriptors: Language Acquisition, Artificial Intelligence, Computational Linguistics, Ethics
Himel Mondal; Juhu Kiran Krushna Karri; Swaminathan Ramasubramanian; Shaikat Mondal; Ayesha Juhi; Pratima Gupta – Advances in Physiology Education, 2025
Large language models (LLMs)-based chatbots use natural language processing and are a type of generative artificial intelligence (AI) that is capable of comprehending user input and generating output in various formats. They offer potential benefits in medical education. This study explored the student's feedback on the utilization of LLMs in…
Descriptors: Computational Linguistics, Physiology, Teaching Methods, Artificial Intelligence
Mahowald, Kyle; Kachergis, George; Frank, Michael C. – First Language, 2020
Ambridge calls for exemplar-based accounts of language acquisition. Do modern neural networks such as transformers or word2vec -- which have been extremely successful in modern natural language processing (NLP) applications -- count? Although these models often have ample parametric complexity to store exemplars from their training data, they also…
Descriptors: Models, Language Processing, Computational Linguistics, Language Acquisition
Chaudhry, Iffat Sabir; Sarwary, Sayed Ahmad M.; El Refae, Ghaleb A.; Chabchoub, Habib – Cogent Education, 2023
Artificial intelligence-based tools are rapidly revolutionizing the field of higher education, yet to be explored in terms of their impact on existing higher education institutions' (HEIs) practices adopted for continuous learning improvement, given the sparsity of the literature and empirical experiments in undergraduate degree programs. After…
Descriptors: Case Studies, Artificial Intelligence, Outcomes of Education, Instructional Effectiveness
Jennifer Hu – ProQuest LLC, 2023
Language is one of the hallmarks of intelligence, demanding explanation in a theory of human cognition. However, language presents unique practical challenges for quantitative empirical research, making many linguistic theories difficult to test at naturalistic scales. Artificial neural network language models (LMs) provide a new tool for studying…
Descriptors: Linguistic Theory, Computational Linguistics, Models, Language Research
Nicula, Bogdan; Dascalu, Mihai; Newton, Natalie N.; Orcutt, Ellen; McNamara, Danielle S. – Grantee Submission, 2021
Learning to paraphrase supports both writing ability and reading comprehension, particularly for less skilled learners. As such, educational tools that integrate automated evaluations of paraphrases can be used to provide timely feedback to enhance learner paraphrasing skills more efficiently and effectively. Paraphrase identification is a popular…
Descriptors: Computational Linguistics, Feedback (Response), Classification, Learning Processes
Nicula, Bogdan; Dascalu, Mihai; Newton, Natalie; Orcutt, Ellen; McNamara, Danielle S. – Grantee Submission, 2021
The ability to automatically assess the quality of paraphrases can be very useful for facilitating literacy skills and providing timely feedback to learners. Our aim is twofold: a) to automatically evaluate the quality of paraphrases across four dimensions: lexical similarity, syntactic similarity, semantic similarity and paraphrase quality, and…
Descriptors: Phrase Structure, Networks, Semantics, Feedback (Response)
Zhang, Qiuxin – English Language Teaching, 2021
With the rapid development of economy and technology, more and more fields are combined with electronic intelligence and artificial intelligence, and language teaching is no exception. As a research hot issue, computer-assisted language learning (CALL) has attracted more and more people's attention. Based on computer-aided technology, teachers can…
Descriptors: Second Language Learning, Second Language Instruction, Teaching Methods, Computer Assisted Instruction
Musa Nushi; Alireza Aghaei; Maryam Roshanbin – Vocabulary Learning and Instruction, 2021
This paper reviews WordUp, a mobile application which fosters English vocabulary learning through exposure to new words in authentic and engaging contexts such as excerpts of movies, songs, and news programme. The samples of use are introduced after the definition of the target words have been provided in both the learners' first language and…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Artificial Intelligence
Kohnke, Lucas – RELC Journal: A Journal of Language Teaching and Research, 2023
This innovations in practice article introduces a chatbot that was developed to support and motivate second language learners during the COVID-19 pandemic. The chatbot was designed to facilitate active, out-of-class language learning to supplement in-class input. It can adapt to learners' abilities and pace by chatting with them, thus providing…
Descriptors: Teaching Methods, Artificial Intelligence, Second Language Learning, Second Language Instruction
Alsadoon, Reem – English Language Teaching, 2021
In the AI field of language learning, chatterbots are an interesting area for language learning and practice. This research investigates Arabic EFL vocabulary learning using an interactive storytelling chatterbot. A chatterbot was created and equipped with four vocabulary tools: a dictionary, images, an L1 translation tool, and a concordancer. The…
Descriptors: Vocabulary Development, Second Language Learning, Second Language Instruction, English (Second Language)
Previous Page | Next Page ยป
Pages: 1 | 2
Peer reviewed
Direct link
