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Showing 1 to 15 of 23 results Save | Export
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Yishen Song; Qianta Zhu; Huaibo Wang; Qinhua Zheng – IEEE Transactions on Learning Technologies, 2024
Manually scoring and revising student essays has long been a time-consuming task for educators. With the rise of natural language processing techniques, automated essay scoring (AES) and automated essay revising (AER) have emerged to alleviate this burden. However, current AES and AER models require large amounts of training data and lack…
Descriptors: Scoring, Essays, Writing Evaluation, Computer Software
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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
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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Ahmet Can Uyar; Dilek Büyükahiska – International Journal of Assessment Tools in Education, 2025
This study explores the effectiveness of using ChatGPT, an Artificial Intelligence (AI) language model, as an Automated Essay Scoring (AES) tool for grading English as a Foreign Language (EFL) learners' essays. The corpus consists of 50 essays representing various types including analysis, compare and contrast, descriptive, narrative, and opinion…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Teaching Methods
Alexander James Kwako – ProQuest LLC, 2023
Automated assessment using Natural Language Processing (NLP) has the potential to make English speaking assessments more reliable, authentic, and accessible. Yet without careful examination, NLP may exacerbate social prejudices based on gender or native language (L1). Current NLP-based assessments are prone to such biases, yet research and…
Descriptors: Gender Bias, Natural Language Processing, Native Language, Computational Linguistics
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Swapna Haresh Teckwani; Amanda Huee-Ping Wong; Nathasha Vihangi Luke; Ivan Cherh Chiet Low – Advances in Physiology Education, 2024
The advent of artificial intelligence (AI), particularly large language models (LLMs) like ChatGPT and Gemini, has significantly impacted the educational landscape, offering unique opportunities for learning and assessment. In the realm of written assessment grading, traditionally viewed as a laborious and subjective process, this study sought to…
Descriptors: Accuracy, Reliability, Computational Linguistics, Standards
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Yuko Hayashi; Yusuke Kondo; Yutaka Ishii – Innovation in Language Learning and Teaching, 2024
Purpose: This study builds a new system for automatically assessing learners' speech elicited from an oral discourse completion task (DCT), and evaluates the prediction capability of the system with a view to better understanding factors deemed influential in predicting speaking proficiency scores and the pedagogical implications of the system.…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Japanese
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Ockey, Gary J.; Chukharev-Hudilainen, Evgeny – Applied Linguistics, 2021
A challenge of large-scale oral communication assessments is to feasibly assess a broad construct that includes interactional competence. One possible approach in addressing this challenge is to use a spoken dialog system (SDS), with the computer acting as a peer to elicit a ratable speech sample. With this aim, an SDS was built and four trained…
Descriptors: Oral Language, Grammar, Language Fluency, Language Tests
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Dalton, Sarah Grace; Stark, Brielle C.; Fromm, Davida; Apple, Kristen; MacWhinney, Brian; Rensch, Amanda; Rowedder, Madyson – Journal of Speech, Language, and Hearing Research, 2022
Purpose: The aim of this study was to advance the use of structured, monologic discourse analysis by validating an automated scoring procedure for core lexicon (CoreLex) using transcripts. Method: Forty-nine transcripts from persons with aphasia and 48 transcripts from persons with no brain injury were retrieved from the AphasiaBank database. Five…
Descriptors: Validity, Discourse Analysis, Databases, Scoring
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Uzun, Kutay – Contemporary Educational Technology, 2018
Managing crowded classes in terms of classroom assessment is a difficult task due to the amount of time which needs to be devoted to providing feedback to student products. In this respect, the present study aimed to develop an automated essay scoring environment as a potential means to overcome this problem. Secondarily, the study aimed to test…
Descriptors: Computer Assisted Testing, Essays, Scoring, English Literature
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Xu, Jing; Jones, Edmund; Laxton, Victoria; Galaczi, Evelina – Assessment in Education: Principles, Policy & Practice, 2021
Recent advances in machine learning have made automated scoring of learner speech widespread, and yet validation research that provides support for applying automated scoring technology to assessment is still in its infancy. Both the educational measurement and language assessment communities have called for greater transparency in describing…
Descriptors: Second Language Learning, Second Language Instruction, English (Second Language), Computer Software
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Han, Chao; Xiao, Xiaoyan – Language Testing, 2022
The quality of sign language interpreting (SLI) is a gripping construct among practitioners, educators and researchers, calling for reliable and valid assessment. There has been a diverse array of methods in the extant literature to measure SLI quality, ranging from traditional error analysis to recent rubric scoring. In this study, we want to…
Descriptors: Comparative Analysis, Sign Language, Deaf Interpreting, Evaluators
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Linlin, Cao – English Language Teaching, 2020
Through Many-Facet Rasch analysis, this study explores the rating differences between 1 computer automatic rater and 5 expert teacher raters on scoring 119 students in a computerized English listening-speaking test. Results indicate that both automatic and the teacher raters demonstrate good inter-rater reliability, though the automatic rater…
Descriptors: Language Tests, Computer Assisted Testing, English (Second Language), Second Language Learning
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Kang, Okim; Rubin, Don; Kermad, Alyssa – Language Testing, 2019
As a result of the fact that judgments of non-native speech are closely tied to social biases, oral proficiency ratings are susceptible to error because of rater background and social attitudes. In the present study we seek first to estimate the variance attributable to rater background and attitudinal variables on novice raters' assessments of L2…
Descriptors: Evaluators, Second Language Learning, Language Tests, English (Second Language)
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Buzick, Heather; Oliveri, Maria Elena; Attali, Yigal; Flor, Michael – Applied Measurement in Education, 2016
Automated essay scoring is a developing technology that can provide efficient scoring of large numbers of written responses. Its use in higher education admissions testing provides an opportunity to collect validity and fairness evidence to support current uses and inform its emergence in other areas such as K-12 large-scale assessment. In this…
Descriptors: Essays, Learning Disabilities, Attention Deficit Hyperactivity Disorder, Scoring
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