Publication Date
In 2025 | 55 |
Since 2024 | 702 |
Descriptor
Source
Author
Danielle S. McNamara | 6 |
Mihai Dascalu | 5 |
Stefan Ruseti | 4 |
Aras Bozkurt | 3 |
Boxuan Ma | 3 |
Christina Clark | 3 |
Dragan Gaševic | 3 |
Irene Picton | 3 |
Mutahar Qassem | 3 |
Sílvia Perpiñán | 3 |
Anna Siyanova-Chanturia | 2 |
More ▼ |
Publication Type
Education Level
Audience
Researchers | 3 |
Teachers | 3 |
Practitioners | 2 |
Policymakers | 1 |
Location
China | 44 |
Canada | 12 |
United Kingdom | 12 |
Australia | 11 |
Hong Kong | 11 |
Germany | 10 |
Turkey | 10 |
South Korea | 9 |
Taiwan | 9 |
India | 7 |
Spain | 7 |
More ▼ |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Tao Zeng; Chang Xu; Jia Hu; Xiuzhi Fu – SAGE Open, 2024
This research investigated the impact of processing instruction (PI) on the acquisition of the English third-person singular present tense by Chinese English-as-a-foreign-language (EFL) learners and whether this effect would extend to the acquisition of other language components. This study featured the pretest-immediate-posttest design and…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Transfer of Training
Edith Kaan; Haoyun Dai; Xiaodong Xu – Second Language Research, 2024
According to rational adaptation approaches of language processing, readers adjust their expectations of upcoming information depending on the distributional properties of the preceding language input. However, adaptation to sentence structures has not been systematically attested, especially not in second-language (L2) processing. To further our…
Descriptors: Second Language Learning, Brain Hemisphere Functions, Diagnostic Tests, Sentences
Marisa Nagano; Gita Martohardjono – Second Language Research, 2024
Research on second language (L2) pronoun use in null-argument languages has traditionally focused on whether or not a speaker's first language (L1) also allows null pronouns. However, recent studies have pointed out that it is equally important to consider the specific linguistic properties of overt pronouns in the L1 and L2, which may differ even…
Descriptors: Form Classes (Languages), Native Language, Second Language Instruction, Second Language Learning
Ahmed Tlili; Michael Agyemang Adarkwah; Chung Kwan Lo; Aras Bozkurt; Daniel Burgos; Curtis J. Bonk; Eamon Costello; Sanjaya Mishra; Christian M. Stracke; Ronghuai Huang – Journal of Learning for Development, 2024
The development, use, and timely promotion of Open Education (OE) has been effective in addressing myriad educational concerns, including inclusivity, accessibility and learning achievement, among many others. However, limited information exists in the literature concerning how OE could enhance Generative Artificial Intelligence (GenAI), which is…
Descriptors: Open Education, Instructional Effectiveness, Safety, Artificial Intelligence
Qian Du; Tamara Tate – CATESOL Journal, 2024
ChatGPT has been at the center of media coverage since its public release at the end of 2022. Given ChatGPT's capacity for generating human-like text on a wide range of subjects, it is not surprising that educators, especially those who teach writing, have raised concerns regarding the implications of generative AI tools on issues of plagiarism…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Plagiarism
Ilker Cingillioglu – Studies in Higher Education, 2024
This study provides an empirical approach to utilizing an Artificial Intelligence (AI)-based system for identifying students' university choice factors that impact their matriculation decision. We created an AI-based chatbot that gathered both qualitative and quantitative data from nearly 1200 participants worldwide. The entire human-AI…
Descriptors: Admission (School), Decision Making, Student Attitudes, College Choice
Laura Vilkaite-Lozdiene; Algirdas Dinigevicius – Vocabulary Learning and Instruction, 2024
Previous research has shown that L1-L2 congruency is a facilitative factor in collocation processing. The present study explores the congruency effect between learners' L2 and L3. Thirty-three proficient Norwegian learners with Lithuanian as their L1 and English as their L2 completed a phase acceptability task consisting of three groups of…
Descriptors: Multilingualism, Phrase Structure, Norwegian, Second Language Learning
Shabnam Behzad – ProQuest LLC, 2024
Second language learners constitute a significant and expanding portion of the global population and there is a growing demand for tools that facilitate language learning and instruction across various levels and in different countries. The development of large language models (LLMs) has brought about a significant impact on the domains of natural…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Second Language Learning
Zhibin Shan; Hao Xu – Journal of Multilingual and Multicultural Development, 2024
Despite much research on how multilingual learners view the linguistic properties of language, how they perceive languages as cultural capital has been far less investigated. Drawing on the theories of social cognition, this study explores how multiple foreign language learners' impressions, as a lens to observe their multilingual awareness, are…
Descriptors: Multilingualism, Metalinguistics, Second Language Learning, Second Language Instruction
Yen-Chen Hao – Second Language Research, 2024
The current study examined the phonolexical processing of Mandarin segments and tones by English speakers at different Mandarin proficiency levels. Eleven English speakers naive to Mandarin, 15 intermediate and 9 advanced second language (L2) learners participated in a word-learning experiment. After learning the sound and meaning of 16 Mandarin…
Descriptors: English, Native Speakers, Mandarin Chinese, Second Language Learning
Daisuke Akiba; Rebecca Garte – Journal of Interactive Learning Research, 2024
The emergence of AI-powered Large Language Models (LLMs), such as ChatGPT and Google Gemini, presents both opportunities and challenges for higher education, particularly regarding academic integrity in writing instruction. This exploratory study examines a novel pedagogical approach that integrates LLMs as required feedback tools in a…
Descriptors: Artificial Intelligence, Technology Uses in Education, Writing Instruction, Integrity
Petra Polakova; Blanka Klimova – Cogent Education, 2024
Thanks to the continuous development of artificial intelligence (AI), more and more tools are available to help students to practice their language skills. Nowadays, there are various ways of using AI-driven technology in the process of language learning, one example is the use of chatbots. This pilot study aims to investigate the impact of the…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Second Language Learning
Yuxin Chen; Yaqiong Wang – Language Teaching Research Quarterly, 2024
This study investigates how academic disciplines impact second language (L2) lexical competencies. Prior L2 research has often overlooked the broader effects of disciplinary backgrounds on lexical development. To address this gap, this study utilized lexical decision, memory, and semantic fluency tasks to examine lexicon recognition, memory, and…
Descriptors: Semantics, Second Language Learning, Reaction Time, Accuracy
Napasri Timyam – LEARN Journal: Language Education and Acquisition Research Network, 2024
Studies of English academic writing have revealed a shift to a compressed style, with preferences for lexical and phrasal types of noun modifiers over clausal modifiers. However, condensed noun phrases may result in a loss of explicitness since they lack grammatical markers specifying the semantic relations between head nouns and modifiers. This…
Descriptors: Nouns, Phrase Structure, English (Second Language), Second Language Learning
Alexander Tobias Neumann; Yue Yin; Sulayman Sowe; Stefan Decker; Matthias Jarke – IEEE Transactions on Education, 2025
Contribution: This research explores the benefits and challenges of developing, deploying, and evaluating a large language model (LLM) chatbot, MoodleBot, in computer science classroom settings. It highlights the potential of integrating LLMs into LMSs like Moodle to support self-regulated learning (SRL) and help-seeking behavior. Background:…
Descriptors: Computer Science Education, Databases, Information Systems, Classroom Environment