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Zhang, Mengxue; Heffernan, Neil; Lan, Andrew – International Educational Data Mining Society, 2023
Automated scoring of student responses to open-ended questions, including short-answer questions, has great potential to scale to a large number of responses. Recent approaches for automated scoring rely on supervised learning, i.e., training classifiers or fine-tuning language models on a small number of responses with human-provided score…
Descriptors: Scoring, Computer Assisted Testing, Mathematics Instruction, Mathematics Tests
Géring, Zsuzsanna; Tamássy, Réka; Király, Gábor; Rakovics, Márton – Higher Education: The International Journal of Higher Education Research, 2023
In this paper, we investigate how highly ranked business schools construct their legitimacy claims by analysing their online organisational communication. We argue that in the case of higher education institutions in general, and business schools in particular, the discursive formation of these legitimacy claims is strongly connected to the…
Descriptors: Futures (of Society), Business Schools, Computational Linguistics, Discourse Analysis
Ya'nan, Wang; Zhiling, Tian; Jinghua, Wang – International Education Studies, 2023
Based on Jef Verschueren's Adaptation Theory, Lakoff's definition and Prince et al.'s classification of hedges, this paper takes New York Times and China Daily from January 23rd to April 8th, 2020 as corpus sources, randomly selects 39 COVID-19 reports, and makes a contrastive study of hedges among them, aiming at exploring the similarities and…
Descriptors: Contrastive Linguistics, Newspapers, Language Usage, COVID-19
Omidian, Taha; Ballance, Oliver James; Siyanova-Chanturia, Anna – Language Teaching, 2023
Accurate description of language use is central to English for academic purposes (EAP) practice. Thanks to the development of corpus tools, it has been possible to undertake systematic studies of language in academic contexts. This line of research aims to provide detailed and accurate characterization of academic communication and to ultimately…
Descriptors: Computational Linguistics, English for Academic Purposes, Second Language Learning, Second Language Instruction
McDonough, Kim; Lindberg, Rachael; Trofimovich, Pavel; Tekin, Oguzhan – Language Teaching, 2023
This replication study seeks to extend the generalizability of an exploratory study (McDonough et al., 2019) that identified holds (i.e., temporary cessation of dynamic movement by the listener) as a reliable visual cue of non-understanding. Conversations between second language (L2) English speakers in the Corpus of English as a Lingua Franca…
Descriptors: Second Language Learning, Second Language Instruction, English (Second Language), Computational Linguistics
Lijin Zhang; Xueyang Li; Zhiyong Zhang – Grantee Submission, 2023
The thriving developer community has a significant impact on the widespread use of R software. To better understand this community, we conducted a study analyzing all R packages available on CRAN. We identified the most popular topics of R packages by text mining the package descriptions. Additionally, using network centrality measures, we…
Descriptors: Computer Software, Programming Languages, Data Analysis, Visual Aids
Mai Al-Khatib – ProQuest LLC, 2023
Linguistic meaning is generated by the mind and can be expressed in multiple languages. One may assume that equivalent texts/utterances in two languages by means of translation generate equivalent meanings in their readers/hearers. This follows if we assume that meaning calculated from the linguistic input is solely objective in nature. However,…
Descriptors: Semantics, Linguistic Input, Bilingualism, Language Processing
Andrea Bruera; Yuan Tao; Andrew Anderson; Derya Çokal; Janosch Haber; Massimo Poesio – Cognitive Science, 2023
The meaning of most words in language depends on their context. Understanding how the human brain extracts contextualized meaning, and identifying where in the brain this takes place, remain important scientific challenges. But technological and computational advances in neuroscience and artificial intelligence now provide unprecedented…
Descriptors: Neurosciences, Brain Hemisphere Functions, Artificial Intelligence, Diagnostic Tests
Steven J. Pentland; Christie M. Fuller; Lee A. Spitzley; Douglas P. Twitchell – International Journal of Social Research Methodology, 2023
The analysis of spoken language has been integral to a breadth of research in social science and beyond. However, for analyses to occur with efficiency, language must be in the form of computer-readable text. Historically, the speech-to-text process has occurred manually using human transcriptionists. Automated speech recognition (ASR) is…
Descriptors: Accuracy, Social Science Research, Classification, Reading Processes
Kristian Roncero – Language Documentation & Conservation, 2023
This paper discusses levels of access in language archives and their implications for assessment. In the absence of well-established criteria, part of the evaluation of language archives is often based on accessibility; roughly, the more "unrestricted" or "open access" content, the better the archive. In this paper, I argue…
Descriptors: Dialects, Language Research, Computational Linguistics, Ethics
Thanachporn Varapongsittikul; Sujinat Jitwiriyanont – LEARN Journal: Language Education and Acquisition Research Network, 2025
This study aims to investigate the VOT values of English wordinitial plosive consonants produced by young Thai learners to understand current trends in English pronunciation among Thai speakers and its future direction. The study analyzes how phonological mismatches between Thai and English affect the pronunciation of Thai learners, using a speech…
Descriptors: Phonemes, Thai, Native Language, Second Language Instruction
Mariusz Kruk; Agnieszka Kaluzna – European Journal of Education, 2025
The integration of artificial intelligence (AI) in L2 teaching and learning is poised to revolutionise educational practices by enhancing both instructional methods and language development for L2 learners. This study employed a mixed-methods design to comprehensively examine the impact of AI tools, machine translation systems, and traditional…
Descriptors: Artificial Intelligence, Translation, Language Skills, Emotional Experience
Ha Nguyen; Jake Hayward – Journal of Science Education and Technology, 2025
High-quality science assessments are multi-dimensional. They promote disciplinary practices, core ideas, cross-cutting concepts, and science sense-making. In this paper, we investigate the feasibility of using generative artificial intelligence (GenAI), specifically multimodal large language models (MLLMs), to annotate and provide improvement…
Descriptors: Science Tests, Criticism, Artificial Intelligence, Technology Uses in Education
Andrew Williams – International Journal of Research in Education and Science, 2025
The possibilities for integrating generative artificial intelligence (AI) and large language models (LLMs) into higher education may revolutionise approaches to pedagogical practices and curriculum design, while LLMs could be transformative in how students approach their learning. This conversation with ChatGPT, and associated critical evaluation,…
Descriptors: Science Education, Higher Education, Integrity, Artificial Intelligence
Fears, Nicholas E.; Walsh, Leah E.; Lockman, Jeffrey J. – Reading and Writing: An Interdisciplinary Journal, 2020
Children's ability to write letters automatically has been linked to academic achievement. Despite the importance of handwriting, handwriting instruction is often neglected and teachers use inconsistent practices to teach handwriting. Specifically, the frequency that children are presented opportunities to write individual block letters in…
Descriptors: Alphabets, Handwriting, Workbooks, Teaching Methods

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