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Showing 1 to 15 of 52 results Save | Export
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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
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William Orwig; Emma R. Edenbaum; Joshua D. Greene; Daniel L. Schacter – Journal of Creative Behavior, 2024
Recent developments in computerized scoring via semantic distance have provided automated assessments of verbal creativity. Here, we extend past work, applying computational linguistic approaches to characterize salient features of creative text. We hypothesize that, in addition to semantic diversity, the degree to which a story includes…
Descriptors: Computer Assisted Testing, Scoring, Creativity, Computational Linguistics
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Despina Papadopoulou; Nikolaos Amvrazis; Gerakini Douka; Alexandros Tantos – Modern Language Journal, 2024
The article introduces triangulation to converge evidence from corpus and experimental data, by means of two case studies in second language (L2) learners of Greek. The first case study investigates the acquisition of gender agreement, while the second probes the development of relative clauses. In both studies, findings from the corpus are tested…
Descriptors: Greek, Phrase Structure, Second Language Learning, Second Language Instruction
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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
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Kunal Sareen – Innovations in Education and Teaching International, 2024
This study examines the proficiency of Chat GPT, an AI language model, in answering questions on the Situational Judgement Test (SJT), a widely used assessment tool for evaluating the fundamental competencies of medical graduates in the UK. A total of 252 SJT questions from the "Oxford Assess and Progress: Situational Judgement" Test…
Descriptors: Ethics, Decision Making, Artificial Intelligence, Computer Software
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Kyeng Gea Lee; Mark J. Lee; Soo Jung Lee – International Journal of Technology in Education and Science, 2024
Online assessment is an essential part of online education, and if conducted properly, has been found to effectively gauge student learning. Generally, textbased questions have been the cornerstone of online assessment. Recently, however, the emergence of generative artificial intelligence has added a significant challenge to the integrity of…
Descriptors: Artificial Intelligence, Computer Software, Biology, Science Instruction
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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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Hitoshi Nishizawa – Language Testing, 2024
Corpus-based studies have offered the domain definition inference for test developers. Yet, corpus-based studies on temporal fluency measures (e.g., speech rate) have been limited, especially in the context of academic lecture settings. This made it difficult for test developers to sample representative fluency features to create authentic…
Descriptors: High Stakes Tests, Language Tests, Second Language Learning, Computer Assisted Testing
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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Latifi, Syed; Gierl, Mark – Language Testing, 2021
An automated essay scoring (AES) program is a software system that uses techniques from corpus and computational linguistics and machine learning to grade essays. In this study, we aimed to describe and evaluate particular language features of Coh-Metrix for a novel AES program that would score junior and senior high school students' essays from…
Descriptors: Writing Evaluation, Computer Assisted Testing, Scoring, Essays
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Chinkina, Maria; Ruiz, Simón; Meurers, Detmar – ReCALL, 2020
How can state-of-the-art computational linguistic technology reduce the workload and increase the efficiency of language teachers? To address this question, we combine insights from research in second language acquisition and computational linguistics to automatically generate text-based questions to a given text. The questions are designed to…
Descriptors: Computational Linguistics, Computer Assisted Testing, Computer Assisted Instruction, Second Language Instruction
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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
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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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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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Blomquist, Christina; McMurray, Bob – Developmental Psychology, 2023
As a spoken word unfolds over time, similar sounding words ("cap" and "cat") compete until one word "wins". Lexical competition becomes more efficient from infancy through adolescence. We examined one potential mechanism underlying this development: lexical inhibition, by which activated candidates suppress…
Descriptors: Speech Communication, Language Acquisition, Age Differences, Word Recognition
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