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Siraprapa Kotmungkun; Wichuta Chompurach; Piriya Thaksanan – English Language Teaching Educational Journal, 2024
This study explores the writing quality of two AI chatbots, OpenAI ChatGPT and Google Gemini. The research assesses the quality of the generated texts based on five essay models using the T.E.R.A. software, focusing on ease of understanding, readability, and reading levels using the Flesch-Kincaid formula. Thirty essays were generated, 15 from…
Descriptors: Plagiarism, Artificial Intelligence, Computer Software, Essays
Dadi Ramesh; Suresh Kumar Sanampudi – European Journal of Education, 2024
Automatic essay scoring (AES) is an essential educational application in natural language processing. This automated process will alleviate the burden by increasing the reliability and consistency of the assessment. With the advances in text embedding libraries and neural network models, AES systems achieved good results in terms of accuracy.…
Descriptors: Scoring, Essays, Writing Evaluation, Memory
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
Husam M. Alawadh; Talha Meraj; Lama Aldosari; Hafiz Tayyab Rauf – SAGE Open, 2024
E-learning systems are transforming the educational sector and making education more affordable and accessible. Recently, many e-learning systems have been equipped with advanced technologies that facilitate the roles of educators and increase the efficiency of teaching and learning. One such technology is Automatic Essay Grading (AEG) or…
Descriptors: Essays, Writing Evaluation, Computer Software, Technology Uses in Education
McCarthy, Philip M.; Kaddoura, Noor W.; Al-Harthy, Ayah; Thomas, Anuja M.; Duran, Nicholas D.; Ahmed, Khawlah – Pegem Journal of Education and Instruction, 2022
This study analyzes the linguistic features of counter-arguments and support arguments using two computational linguistic tools: Coh-Metrix and Gramulator. The research question investigates whether counter-argument paragraphs and support paragraphs are different in terms of their linguistic features. To conduct this study, a corpus of 78…
Descriptors: Computational Linguistics, Connected Discourse, Discourse Analysis, Readability
Koji Osawa – RELC Journal: A Journal of Language Teaching and Research, 2024
With the recent rapid technological advance, second language (L2) educators have increasingly incorporated technologies into writing pedagogy. Two of the major technologies to promote L2 writing are e-portfolios and automated written corrective feedback (AWCF). Notably, feedback-rich portfolios facilitate L2 learners' self-regulation and writing…
Descriptors: Artificial Intelligence, Computer Software, Writing Instruction, Writing Evaluation
Granados, Adrián; Lorenzo-Espejo, Antonio; Lorenzo, Francisco – Language and Education, 2023
This study describes academic literacy development during mid-adolescence, when learners need to adjust to the demands of academic discourse as a gateway to linguistic adulthood. Unlike most research to date, which is cross-sectional and detached from disciplinary content, this study provides a two-year longitudinal description of academic…
Descriptors: Academic Language, Literacy Education, Longitudinal Studies, History Instruction
Mohammadi, Mojtaba; Zarrabi, Maryam; Kamali, Jaber – International Journal of Language Testing, 2023
With the incremental integration of technology in writing assessment, technology-generated feedback has found its way to take further steps toward replacing human corrective feedback and rating. Yet, further investigation is deemed necessary regarding its potential use either as a supplement to or replacement for human feedback. This study aims to…
Descriptors: Formative Evaluation, Writing Evaluation, Feedback (Response), Computer Assisted Testing
Hosseinpur, Rasoul Mohammad; Pour, Hossein Hosseini – TESL-EJ, 2022
A compelling body of evidence suggests that EFL students have problem with logical connectors' appropriate use in writing. This study explored Iranian EFL students' adversative connectors use in their essay writing course. To this end, a Learner Corpus of 60393 words consisting of 156 essays was compiled. LOCNESS was chosen as the criterion…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Native Language
Tywoniw, Rurik; Crossley, Scott – Language Education & Assessment, 2019
Cohesion features were calculated for a corpus of 960 essays by 480 test-takers from the Test of English as a Foreign Language (TOEFL) in order to examine differences in the use of cohesion devices between integrated (source-based) writing and independent writing samples. Cohesion indices were measured using an automated textual analysis tool, the…
Descriptors: English (Second Language), Language Tests, Second Language Learning, Connected Discourse
Chon, Yuah V.; Shin, Dongkwang – English Teaching, 2020
While learners may have access to reference tools during second language (L2) writing, the latest developments in machine translation (MT), such as "Google Translate" requires examination as to how using the tool may factor into the second language learners' writing products. To this end, the purpose of this study was to examine how MT…
Descriptors: Translation, Computational Linguistics, Second Language Learning, English (Second Language)
Granados, Adrián; Lorenzo-Espejo, Antonio; Lorenzo, Francisco – International Journal of Bilingual Education and Bilingualism, 2022
However influential the interdependence hypothesis has become in bilingual research, it still lacks full empirical support. This longitudinal study explores the parallels in the biliteracy development (L1 Spanish and L2 English) of 20 students in a European immersion programme (i.e. CLIL) over a two-year period. A bilingual learner corpus of…
Descriptors: Bilingualism, Literacy, Second Language Learning, Second Language Instruction
Shi, Zhan; Liu, Fengkai; Lai, Chun; Jin, Tan – Language Learning & Technology, 2022
Automated Writing Evaluation (AWE) systems have been found to enhance the accuracy, readability, and cohesion of writing responses (Stevenson & Phakiti, 2019). Previous research indicates that individual learners may have difficulty utilizing content-based AWE feedback and collaborative processing of feedback might help to cope with this…
Descriptors: Writing Instruction, Writing Evaluation, Feedback (Response), Accuracy
Matthews, Joshua; Wijeyewardene, Ingrid – Language Learning & Technology, 2018
Despite the current potential to use computers to automatically generate a large range of text-based indices, many issues remain unresolved about how to apply these data in established language teaching and assessment contexts. One way to resolve these issues is to explore the degree to which automatically generated indices, which are reflective…
Descriptors: Correlation, Robotics, Second Language Learning, Second Language Instruction
Al-Hamad, Raghda F.; Al-Jamal, Dina A. H.; Bataineh, Ruba F. – Digital Education Review, 2019
This paper examines the potential effectiveness of MALL for developing teens' writing performance. The results reveal substantial improvement in content and ideas, organization and mechanics, vocabulary, and language use in favor of the experimental groups (viz. Smart Teens and Amazing Teens).
Descriptors: Telecommunications, Handheld Devices, Second Language Learning, Second Language Instruction
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