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Lifang Bai; Yijia Wei – IEEE Transactions on Learning Technologies, 2024
ChatGPT can promptly reformulate a text and improve its quality in content and form while preserving the original meaning. Yet, little is known about how learners respond to such reformulations. Here, we employed a three-stage writing task (composing-comparison-rewriting) to investigate how learners notice, integrate, and perceive ChatGPT's…
Descriptors: English (Second Language), Second Language Learning, Writing Evaluation, Artificial Intelligence
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Thuy Thi-Nhu Ngo; Howard Hao-Jan Chen; Kyle Kuo-Wei Lai – Interactive Learning Environments, 2024
The present study performs a three-level meta-analysis to investigate the overall effectiveness of automated writing evaluation (AWE) on EFL/ESL student writing performance. 24 primary studies representing 85 between-group effect sizes and 34 studies representing 178 within-group effect sizes found from 1993 to 2021 were separately meta-analyzed.…
Descriptors: Writing Evaluation, Automation, Computer Software, English (Second Language)
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Ye, Wei; Ren, Wei – Reading and Writing: An Interdisciplinary Journal, 2023
Integrated writing has gained importance in both tertiary and secondary learning contexts. However, assessment tasks at secondary schools have received little attention. To obtain evidence of skill integration, a task-defining feature for integrated writing, we developed a comprehensive questionnaire study of an understudied task used in the…
Descriptors: English (Second Language), Second Language Learning, Writing Evaluation, Writing Skills
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Hakyung Sung; Sooyeon Cho; Kristopher Kyle – Language Assessment Quarterly, 2024
Lexical diversity (LD) is an important indicator of second language lexical development. Much research has investigated LD indices, with a focus on learners of English. However, further research is needed in languages that are typologically distinct from English, such as Korean. In this study, we evaluated the reliability and validity of LD…
Descriptors: Second Language Learning, Korean, Persuasive Discourse, Language Tests
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Khaled ElEbyary; Ramy Shabara; Deena Boraie – Language Testing in Asia, 2024
Despite the plethora of studies on the role of noticing in second language learning, little is known about the role of AI-operated feedback in noticing errors and uptake "during" and "after" writing. To address this gap, this study primarily aimed to investigate the impact of feedback modes and timing on L2 students' noticing…
Descriptors: Foreign Countries, Artificial Intelligence, Second Language Learning, English (Second Language)
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Yonggang Gao; Lu Gan; Kaiyuan Wang – Education and Information Technologies, 2025
This investigation sought to discern the impacts of different electronic note-taking strategies--collaborative, individual, and a hybrid of both--on the academic writing skills of Chinese EFL graduate students. The study engaged 185 participants, systematically assigned to one of four groups: those practicing collaborative electronic note-taking,…
Descriptors: Notetaking, Computer Uses in Education, Collaborative Writing, Writing Skills
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John Bankier – TESOL Quarterly: A Journal for Teachers of English to Speakers of Other Languages and of Standard English as a Second Dialect, 2025
The theory of language socialization and its subfield academic discourse socialization consider how newcomers are socialized into the practices and identities of communities through interaction with various communicative partners. Drawing on the framework of individual networks of practice, this case study considers the academic writing practices…
Descriptors: Foreign Countries, College Students, Second Language Learning, English (Second Language)
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Hetian Yu; Qin Xie – Language Teaching Research Quarterly, 2025
Generative AI has stormed the education community worldwide. Gen-AI's potential to assist teachers in providing feedback to students is the focus of the current research. Specifically, the research investigated how similar or different AI-generated feedback was from teacher feedback, and whether there were differences in students' responses to the…
Descriptors: Artificial Intelligence, Technology Uses in Education, Feedback (Response), Revision (Written Composition)
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Yuguo Ke; Xiaozhen Zhou – SAGE Open, 2025
Focusing efficiently on potential weaknesses in the validity argument of writing assessments--such as writing subjectivity, content coverage, criteria vagueness, and raters' incompetence--has been shown to positively enhance teachers' overall writing assessment competence (AC). In this study, we propose a computational bootstrapping model of…
Descriptors: Writing Evaluation, Persuasive Discourse, Validity, Writing Teachers
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Fatemeh Faryabi; Mohammad Rahimi; Kristin J. Davin – TESOL Journal, 2024
The present study adopted a praxis orientation to second language (L2) research and pedagogy to explore the professional development needs of three English as a foreign language (EFL) teachers after their first attempt at implementing dynamic assessment (DA) of essay writing. To date, few studies have examined how teachers learn to implement DA,…
Descriptors: Faculty Development, English (Second Language), Second Language Learning, Second Language Instruction
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Hongzhi Yang; Chuan Gao; Hui-zhong Shen – Education and Information Technologies, 2024
Recently, artificial intelligence (AI)-programmed automated writing evaluation (AWE) has attracted increasing attention in language research. Using a small data set arising from an analysis of five Chinese university-level English as a foreign language (EFL) students' submissions, this paper examined in detail how EFL students interacted with the…
Descriptors: Artificial Intelligence, Programming, Writing Evaluation, Computer Mediated Communication
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Razieh Mohammadi; Nasim Ghanbari; Abbas Abbasi – International Journal of Language Testing, 2024
As a formative assessment procedure, self-assessment aims to converge learners' and teachers' views in assessment. Hence, reducing the perceptual mismatches between the learners' and the teachers' assessments would positively affect the learning process. For this aim, the present study investigated to what extent the learners' assessment of their…
Descriptors: Foreign Countries, Evaluation Criteria, Differences, Students
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Teguh Budiharso; Imroatus Solikhah; Samsu Armadi; Rano Wandana – Novitas-ROYAL (Research on Youth and Language), 2024
This research uses Bloom's taxonomy in English-language writing and speaking skills assessment rubrics. A descriptive qualitative research method was adopted, and data were collected through observations, interviews, and English major students' course grades. Five lecturers and 25 students participated in the research, and the findings revealed…
Descriptors: Taxonomy, Scoring Rubrics, Evaluation Methods, Writing Evaluation
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Escalante, Juan; Pack, Austin; Barrett, Alex – International Journal of Educational Technology in Higher Education, 2023
The question of how generative AI tools, such as large language models and chatbots, can be leveraged ethically and effectively in education is ongoing. Given the critical role that writing plays in learning and assessment within educational institutions, it is of growing importance for educators to make thoughtful and informed decisions as to how…
Descriptors: Artificial Intelligence, Feedback (Response), English (Second Language), Second Language Learning
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Leyli Kashef; Nasser Ghafoori; Akbar Valizadeh Oghani; Azadeh Mehrpouyan – International Journal of Language Testing, 2024
The present study explored the effects of interactionist Dynamic Assessment (DA) and age on the writing accuracy of IELTS candidates. This research investigated the existence of an interactional effect between the age of learners and the type of treatment they received. First, 140 IELTS candidates were split into two age groups, adult and young.…
Descriptors: English (Second Language), Language Tests, Second Language Learning, Writing Evaluation
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