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Adam J. Royer – ProQuest LLC, 2021
When a subject NP has a singular head noun and a plural noun in some lower syntactic phrase (i.e. local noun), occasionally a plural verb will be produced in a sentence (i.e., agreement attraction) (Bock 1991,Bock et al. 2001). Evidence from production (Eberhard 2005) and comprehension (Badecker 2007, Wagers 2009) studies have conflicting accounts…
Descriptors: Intonation, Suprasegmentals, English, Grammar
Jing Liu; Qing Ma – Educational Technology & Society, 2025
This meta-analysis evaluated the effectiveness of data-driven learning (DDL) among low-proficiency L2 English learners, addressing the mixed results found in previous meta-analyses. The study incorporated 38 studies involving 2085 participants, yielding 37 effect sizes from control-experimental (C/E) studies and 42 from pre- and post-test (P/P)…
Descriptors: Computational Linguistics, Second Language Instruction, Second Language Learning, Language Proficiency
Florian Hesse; Gerrit Helm – Journal of Digital Learning in Teacher Education, 2025
AI is changing the way writing is learnt at university and taught in schools. Different institutions hence call for integrating programs on writing with AI in teacher education. These must be based on the needs of the participants, which are, however, still unexplored. This article fills this gap with findings from a February 2024 questionnaire…
Descriptors: Artificial Intelligence, Technology Uses in Education, Writing (Composition), Preservice Teacher Education
Mary Rice; Nicholas DePascal; Joaquín T. Argüello de Jesús; Helen McFeely; Amy Traylor; Lehman Heaviland – Professional Development in Education, 2025
With the introduction of artificial intelligence (AI), particularly Generative AI (GenAI) to school settings, teachers are likely to be drawn into professional learning scenarios where they will be expected to learn how to use programs and applications for remediation and tutoring of children. Previous research highlights how professional learning…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
Nan Tang – International Journal of Web-Based Learning and Teaching Technologies, 2025
Human-Machine Interaction (HMI) technology has revolutionized the landscape of oral English education, offering new possibilities for improving learning efficiency and experiences. This paper presents an innovative teaching system that integrates real-time speech recognition and feedback capabilities with advanced natural language processing (NLP)…
Descriptors: Language Proficiency, Oral Language, Technology Uses in Education, Natural Language Processing
Na Gao; Peng Zhou; Stephen Crain – Language Acquisition: A Journal of Developmental Linguistics, 2025
This study investigates how speakers of Mandarin interpret negative sentences with the conjunction ("he" 'and'). Our experiments test three predictions that follow from the proposal that the Mandarin conjunction is a positive polarity item (PPI) for both children and adults. On this account, the Mandarin conjunction should be interpreted…
Descriptors: Mandarin Chinese, Prediction, Form Classes (Languages), Phrase Structure
Andrew Potter; Mitchell Shortt; Maria Goldshtein; Rod D. Roscoe – Grantee Submission, 2025
Broadly defined, academic language (AL) is a set of lexical-grammatical norms and registers commonly used in educational and academic discourse. Mastery of academic language in writing is an important aspect of writing instruction and assessment. The purpose of this study was to use Natural Language Processing (NLP) tools to examine the extent to…
Descriptors: Academic Language, Natural Language Processing, Grammar, Vocabulary Skills
Dan Song; Alexander F. Tang – Language Learning & Technology, 2025
While many studies have addressed the benefits of technology-assisted L2 writing, limited research has delved into how generative artificial intelligence (GAI) supports students in completing their writing tasks in Mandarin Chinese. In this study, 26 university-level Mandarin Chinese foreign language students completed two writing tasks on two…
Descriptors: Artificial Intelligence, Second Language Learning, Standardized Tests, Writing Tests
Hui-Chun Chu; Yi-Chun Lu; Yun-Fang Tu – Educational Technology & Society, 2025
This study guided 97 undergraduates using generative artificial intelligence (GenAI) to conduct multimodal digital storytelling (M-DST) learning activities. Furthermore, the study examined the differences in M-DST ability and critical thinking awareness among undergraduates with different levels of learning motivation and their perceptions of this…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Undergraduate Students
Jiarui Hou; James F. Lee; Stephen Doherty – Journal of Computer Assisted Learning, 2025
Background: Recent research has demonstrated the potential of mobile-assisted learning to enhance learners' learning outcomes. In contrast, the learning processes in this regard are much less explored using eye tracking technology. Objective: This systematic review study aims to synthesise the relevant work to reflect the current state of eye…
Descriptors: State of the Art Reviews, Eye Movements, Electronic Learning, Handheld Devices
YiHsuan Wood; Jeffrey J. Green; Ellen Knell; Yu Liu – Language Awareness, 2025
This study used eye-tracking to investigate the real-time processing of phonetic and semantic radicals (components of Chinese characters that give clues to their pronunciation and meaning) by intermediate-level university Chinese foreign language (CFL) learners. Additionally, the study examined how knowledge and awareness of radicals affect…
Descriptors: Eye Movements, Chinese, Second Language Learning, Second Language Instruction
Xiaohong Liu; Baoxin Guo; Wei He; Xiaoyong Hu – Journal of Educational Computing Research, 2025
Generative artificial intelligence (GenAI) has significant potential for educational innovation, although its impact on students' learning outcomes remains controversial. This study aimed to examine the impact of GenAI on the learning outcomes of K-12 and higher education students, and explore the moderating factors influencing this impact. A…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
Feiwen Xiao; Ellen Wenting Zou; Jiaju Lin; Zhaohui Li; Dandan Yang – British Journal of Educational Technology, 2025
Large language model (LLM)-based conversational agents (CAs), with their advanced generative capabilities and human-like conversational interfaces, can serve as reading partners for children during dialogic reading and have shown promise in enhancing children's comprehension and conversational skills. However, there is limited research on the…
Descriptors: Childrens Literature, Electronic Books, Artificial Intelligence, Natural Language Processing
Tobias Wyrwich; Marcus Kubsch; Hendrik Drachsler; Knut Neumann – Physical Review Physics Education Research, 2025
Students struggle to acquire the needed energy understanding to meaningfully participate in the energy discourse about socially relevant topics, such as energy transformation or climate change. Identifying students on differing learning trajectories, as well as differences in knowledge used, is essential to help students achieve the needed energy…
Descriptors: Learning Processes, Physics, Energy, Science Instruction
Pauline Frizelle; Ana Oliveira-Buckley; Tricia Biancone; Jorge Oliveira; Paul Fletcher; Dorothy V. M. Bishop; Cristina McKean – International Journal of Language & Communication Disorders, 2025
Introduction: The present study investigated English-speaking 5-9 year olds' (n = 600, normative sample) comprehension of relative, adverbial and complement clauses using the Test of Complex Syntax-Electronic (TECS-E), an online interactive assessment. with strong test-retest reliability, concurrent validity and internal consistency. Method: Using…
Descriptors: Syntax, Child Language, Young Children, Language Tests

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