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Peter Baldwin; Victoria Yaneva; Kai North; Le An Ha; Yiyun Zhou; Alex J. Mechaber; Brian E. Clauser – Journal of Educational Measurement, 2025
Recent developments in the use of large-language models have led to substantial improvements in the accuracy of content-based automated scoring of free-text responses. The reported accuracy levels suggest that automated systems could have widespread applicability in assessment. However, before they are used in operational testing, other aspects of…
Descriptors: Artificial Intelligence, Scoring, Computational Linguistics, Accuracy
Schneider, Johannes; Richner, Robin; Riser, Micha – International Journal of Artificial Intelligence in Education, 2023
Autograding short textual answers has become much more feasible due to the rise of NLP and the increased availability of question-answer pairs brought about by a shift to online education. Autograding performance is still inferior to human grading. The statistical and black-box nature of state-of-the-art machine learning models makes them…
Descriptors: Grading, Natural Language Processing, Computer Assisted Testing, Ethics
Sangmin-Michelle Lee; Nayeon Kang – Language Learning & Technology, 2024
With recent improvements in machine translation (MT) accuracy, MT has gained unprecedented popularity in second language (L2) learning. Despite the significant number of studies on MT use, the effects of using MT on students' retention of learning or secondary school students' use of MT in L2 writing has rarely been researched. The current study…
Descriptors: Second Language Instruction, Writing (Composition), Middle School Students, Foreign Countries
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
Salem, Alexandra C.; Gale, Robert; Casilio, Marianne; Fleegle, Mikala; Fergadiotis, Gerasimos; Bedrick, Steven – Journal of Speech, Language, and Hearing Research, 2023
Purpose: ParAlg (Paraphasia Algorithms) is a software that automatically categorizes a person with aphasia's naming error (paraphasia) in relation to its intended target on a picture-naming test. These classifications (based on lexicality as well as semantic, phonological, and morphological similarity to the target) are important for…
Descriptors: Semantics, Computer Software, Aphasia, Classification
Yi Gui – ProQuest LLC, 2024
This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…
Descriptors: Writing Tests, Natural Language Processing, Writing Evaluation, Scoring
Carly Fox – ProQuest LLC, 2021
The purpose of the study was to investigate the feasibility of streamlining the transcription and scoring portion of language sample analysis (LSA) through computer-automation. LSA is a gold-standard procedure for examining childrens' language abilities that is underutilized by speech language pathologists due to its time-consuming nature. To…
Descriptors: Computational Linguistics, Error Patterns, Accuracy, Scoring
Christopher Saarna – International Journal of Technology in Education, 2024
This study seeks to clarify whether teachers are able to distinguish between essays written by English L2 students or generated by ChatGPT. 47 instructors who hold experience teaching English to native speakers of Japanese in universities or other higher education institutions were tested on whether they could identify between human written essays…
Descriptors: Identification, Artificial Intelligence, Computer Software, Grammar
McDonald, Margarethe; Kwon, Taeahn; Kim, Hyunji; Lee, Youngki; Ko, Eon-Suk – Journal of Speech, Language, and Hearing Research, 2021
Purpose: The algorithm of the Language ENvironment Analysis (LENA) system for calculating language environment measures was trained on American English; thus, its validity with other languages cannot be assumed. This article evaluates the accuracy of the LENA system applied to Korean. Method: We sampled sixty 5-min recording clips involving 38 key…
Descriptors: Computational Linguistics, Korean, Audio Equipment, Accuracy
Loboda, Krzysztof; Mastela, Olga – Interpreter and Translator Trainer, 2023
Mass adoption of neural machine translation (NMT) tools in the translation workflow has exerted a significant impact on the language services industry over the last decade. There are claims that with the advent of NMT, automated translation has reached human parity for translating news (see, e.g. Popel et al. 2020). Moreover, some machine…
Descriptors: Computer Software, Computational Linguistics, Polish, Folk Culture
Tuc C. Chau – ProQuest LLC, 2023
The purpose of the current dissertation is to map the relationships between first language (L1), writing quality, and syntactic complexity, accuracy, lexical complexity, and fluency (CALF) in second language (L2) writing. CALF are characteristics of language production that have been of significant interest in L2 writing research for the past few…
Descriptors: Correlation, Native Language, Second Language Learning, Second Language Instruction
Botarleanu, Robert-Mihai; Dascalu, Mihai; Watanabe, Micah; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2022
Age of acquisition (AoA) is a measure of word complexity which refers to the age at which a word is typically learned. AoA measures have shown strong correlations with reading comprehension, lexical decision times, and writing quality. AoA scores based on both adult and child data have limitations that allow for error in measurement, and increase…
Descriptors: Age Differences, Vocabulary Development, Correlation, Reading Comprehension
Song, Qiuyuan – English Language Teaching, 2021
This study aims to explore how corpus-based approaches can be used to address the distinctions of English near-synonyms effectively. Especially, it collected source data from the British National Corpus (BNC) and adopted Sketch Engine (SkE) as an analyzing tool to compare the near synonymous pair "damage" and "destroy" commonly…
Descriptors: Computational Linguistics, Phrase Structure, English, Language Usage
Tolchinsky, Liliana – Journal for the Study of Education and Development, 2021
Spelling is a language problem-space, not only a school subject. Successful spelling demands going beyond letter to sound mapping and gaining access to a full representation of the orthographic structure of words. We traced bilingual Catalan/Spanish speakers' spelling performance in Catalan across elementary school in two tasks: isolated words to…
Descriptors: Spelling, Verbal Communication, Romance Languages, Bilingualism
Simanjuntak, Faido – Online Submission, 2019
This study is a descriptive-qualitative study with an embedded-case study research design. The purpose of the study is to describe the quality of the translation on the accuracy in content, acceptability, and readability of translated text of English Idioms Errors Made by Jordanian EFL, Undergraduate Students abstract. The data of the research is…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Translation
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