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Almusharraf, Norah; Alotaibi, Hind – Technology, Knowledge and Learning, 2023
Evaluating written texts is believed to be a time-consuming process that can lack consistency and objectivity. Automated essay scoring (AES) can provide solutions to some of the limitations of human scoring. This research aimed to evaluate the performance of one AES system, Grammarly, in comparison to human raters. Both approaches' performances…
Descriptors: Writing Evaluation, Writing Tests, Essay Tests, Essays
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Chen, Binbin; Bao, Lina; Zhang, Rui; Zhang, Jingyu; Liu, Feng; Wang, Shuai; Li, Mingjiang – Journal of Educational Computing Research, 2024
Language learning has increasingly benefited from Computer-Assisted Language Learning (CALL) technologies, especially with Artificial Intelligence involved in recent years. CALL in writing learning acknowledged as the core of language learning is being realized by technologies like Automated Writing Evaluation (AWE), and Automated Essay Scoring…
Descriptors: Computer Assisted Instruction, English (Second Language), Second Language Learning, Writing Instruction
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Xinming Chen; Ziqian Zhou; Malila Prado – International Journal of Assessment Tools in Education, 2025
This study explores the efficacy of ChatGPT-3.5, an AI chatbot, used as an Automatic Essay Scoring (AES) system and feedback provider for IELTS essay preparation. It investigates the alignment between scores given by ChatGPT-3.5 and those assigned by official IELTS examiners to establish its reliability as an AES. It also identifies the strategies…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Automation
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Kornwipa Poonpon; Paiboon Manorom; Wirapong Chansanam – Contemporary Educational Technology, 2023
Automated essay scoring (AES) has become a valuable tool in educational settings, providing efficient and objective evaluations of student essays. However, the majority of AES systems have primarily focused on native English speakers, leaving a critical gap in the evaluation of non-native speakers' writing skills. This research addresses this gap…
Descriptors: Automation, Essays, Scoring, English (Second Language)
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Taichi Yamashita – Language Testing, 2025
With the rapid development of generative artificial intelligence (AI) frameworks (e.g., the generative pre-trained transformer [GPT]), a growing number of researchers have started to explore its potential as an automated essay scoring (AES) system. While previous studies have investigated the alignment between human ratings and GPT ratings, few…
Descriptors: Artificial Intelligence, English (Second Language), Second Language Learning, Second Language Instruction
Jiyeo Yun – English Teaching, 2023
Studies on automatic scoring systems in writing assessments have also evaluated the relationship between human and machine scores for the reliability of automated essay scoring systems. This study investigated the magnitudes of indices for inter-rater agreement and discrepancy, especially regarding human and machine scoring, in writing assessment.…
Descriptors: Meta Analysis, Interrater Reliability, Essays, Scoring
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Arefsadr, Sajjad; Babaii, Esmat; Hashemi, Mohammad Reza – International Journal of Language Testing, 2022
This study explored possible reasons why IELTS candidates usually score low in writing by investigating the effects of two different test designs and scoring criteria on Iranian IELTS candidates' obtained grades in IELTS and World Englishes (WEs) essay writing tests. To this end, first, a WEs essay writing test was preliminarily designed. Then, 17…
Descriptors: English (Second Language), Second Language Learning, Language Tests, Writing Evaluation
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Gaillat, Thomas; Simpkin, Andrew; Ballier, Nicolas; Stearns, Bernardo; Sousa, Annanda; Bouyé, Manon; Zarrouk, Manel – ReCALL, 2021
This paper focuses on automatically assessing language proficiency levels according to linguistic complexity in learner English. We implement a supervised learning approach as part of an automatic essay scoring system. The objective is to uncover Common European Framework of Reference for Languages (CEFR) criterial features in writings by learners…
Descriptors: Prediction, Rating Scales, English (Second Language), Second Language Learning
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Heidari, Nasim; Ghanbari, Nasim; Abbasi, Abbas – Language Testing in Asia, 2022
It is widely believed that human rating performance is influenced by an array of different factors. Among these, rater-related variables such as experience, language background, perceptions, and attitudes have been mentioned. One of the important rater-related factors is the way the raters interact with the rating scales. In particular, how raters…
Descriptors: Evaluators, Rating Scales, Language Tests, English (Second Language)
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Jones, Daniel Marc; Cheng, Liying; Tweedie, M. Gregory – Canadian Journal of Learning and Technology, 2022
This article reviews recent literature (2011-present) on the automated scoring (AS) of writing and speaking. Its purpose is to first survey the current research on automated scoring of language, then highlight how automated scoring impacts the present and future of assessment, teaching, and learning. The article begins by outlining the general…
Descriptors: Automation, Computer Assisted Testing, Scoring, Writing (Composition)
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Finn, Bridgid; Arslan, Burcu; Walsh, Matthew – Applied Measurement in Education, 2020
To score an essay response, raters draw on previously trained skills and knowledge about the underlying rubric and score criterion. Cognitive processes such as remembering, forgetting, and skill decay likely influence rater performance. To investigate how forgetting influences scoring, we evaluated raters' scoring accuracy on TOEFL and GRE essays.…
Descriptors: Epistemology, Essay Tests, Evaluators, Cognitive Processes
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Wind, Attila M.; Zólyomi, Anna – Language Learning in Higher Education, 2022
Although several studies have investigated the self-assessment (SA) of writing skills, most research has adopted a cross-sectional research design. Consequently, our knowledge about the longitudinal development of SA is limited. This study investigated whether SA instruction leads to improvement in SA accuracy and in second language (L2) writing.…
Descriptors: Self Evaluation (Individuals), Writing Skills, Second Language Learning, Second Language Instruction
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He, Tung-hsien – SAGE Open, 2019
This study employed a mixed-design approach and the Many-Facet Rasch Measurement (MFRM) framework to investigate whether rater bias occurred between the onscreen scoring (OSS) mode and the paper-based scoring (PBS) mode. Nine human raters analytically marked scanned scripts and paper scripts using a six-category (i.e., six-criterion) rating…
Descriptors: Computer Assisted Testing, Scoring, Item Response Theory, Essays
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Monteiro, Kátia R.; Crossley, Scott A.; Kyle, Kristopher – Applied Linguistics, 2020
Lexical items that are encountered more frequently and in varying contexts have important effects on second language (L2) development because frequent and contextually diverse words are learned faster and become more entrenched in a learner's lexicon (Ellis 2002a, b). Despite evidence that L2 learners are generally exposed to non-native input,…
Descriptors: English (Second Language), Language Tests, Second Language Learning, Benchmarking
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Rupp, André A.; Casabianca, Jodi M.; Krüger, Maleika; Keller, Stefan; Köller, Olaf – ETS Research Report Series, 2019
In this research report, we describe the design and empirical findings for a large-scale study of essay writing ability with approximately 2,500 high school students in Germany and Switzerland on the basis of 2 tasks with 2 associated prompts, each from a standardized writing assessment whose scoring involved both human and automated components.…
Descriptors: Automation, Foreign Countries, English (Second Language), Language Tests
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